# **Additive Manufacturing (AM) for Advanced Materials and Structures Green and Intelligent Development Trend**

Edited by Hao Yi, Huajun Cao, Menglin Liu and Le Jia Printed Edition of the Special Issue Published in *Crystals*

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## **Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend**

## **Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend**

Editors

**Hao Yi Huajun Cao Menglin Liu Le Jia**

MDPI Basel Beijing Wuhan Barcelona Belgrade Manchester Tokyo Cluj Tianjin

*Editors* Hao Yi College of Mechanical and Vehicle Engineering Chongqing University Chongqing China Le Jia College of Mechanical and Vehicle Engineering Chongqing University Chongqing China

Huajun Cao College of Mechanical and Vehicle Engineering Chongqing University Chongqing China

Menglin Liu College of Mechanical and Vehicle Engineering Chongqing University Chongqing China

*Editorial Office* MDPI St. Alban-Anlage 66 4052 Basel, Switzerland

This is a reprint of articles from the Special Issue published online in the open access journal *Crystals* (ISSN 2073-4352) (available at: www.mdpi.com/journal/crystals/special issues/additive manufacturing green).

For citation purposes, cite each article independently as indicated on the article page online and as indicated below:

LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. *Journal Name* **Year**, *Volume Number*, Page Range.

**ISBN 978-3-0365-6335-0 (Hbk) ISBN 978-3-0365-6334-3 (PDF)**

© 2023 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications.

The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND.

## **Contents**



## **About the Editors**

## **Hao Yi**

Dr. Hao Yi is an Associate Professor (Doctoral Supervisor) at the College of Mechanical and Vehicle Engineering at Chongqing University, China. He serves as an Editorial Board Member of *Virtual and Physical Prototyping, International Journal of Precision Engineering and Manufacturing-Green Technology, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science,* etc. His main research interests focus on 3D Printing and Additive Manufacturing, Green Manufacturing, Production Research, etc.

## **Huajun Cao**

Dr. Huajun Cao is a Full Professor in the College of Mechanical and Vehicle Engineering, Chongqing University, China. His research interests mainly include green manufacturing and remanufacturing, green and intelligent factories, and high-speed dry machining technology and equipment.

## **Menglin Liu**

Menglin Liu is currently a Ph.D. in the College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China. His research activities are mainly focused on additive manufacturing and 3D printing.

## **Le Jia**

Le Jia is currently a Ph.D. in the College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing, China. His research activities are mainly focused on additive manufacturing and 3D printing.

## *Editorial* **Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend**

**Menglin Liu 1,2 , Hao Yi 1,2,3,\* and Huajun Cao 1,2**


Additive manufacturing (AM) is an emerging and rapidly evolving technology that has revolutionized the way products are developed, fabricated and commercialized. This has enabled the disruption of long-running manufacturing processes, leading to economic and societal change. Many design and manufacturing technologies are receiving widespread attention to advance AM technology towards high efficiency, high precision, high performance, and low cost in an environmentally friendly manner. This Special Issue focuses on exploring topical issues in additive manufacturing processes, material design, structure design, process planning, and performance evaluation. The call for articles for this Special Issue resulted in an enthusiastic response from the research community, who contributed an excellent series of high quality and technically diverse manuscripts. This Special Issue "Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend" covers topics surrounding the structural design of complex components, the integrated, advanced design for the preparation and manufacture of high-performance materials, and performance optimization; containing a mix of 20 communications, original articles, and review articles.

In the ever-expanding field of additive manufacturing processes, Chao et al. [1] have proposed a novel high-resolution fused deposition 3D printing technique based on electric field-driven (EFD) jet deposition. An experimental approach based this process was devised to print polycaprolactone (PCL) porous scaffold structures. To explore the application prospects of this technique in the fabrication of microchannel structures, Chao et al. [2] have successfully printed waxy structures with a size of tens of microns.

Laser-based additive manufacturing processes are of long-standing interest among emerging additive manufacturing processes. For example, in laser powder bed fusion (LPBF) technology, scholars have conducted extensive research into structural design, material and part properties, and process strategies. With regard to structural design, Li et al. [3] have developed an optimization method for a body-centered cubic with Z support (BCCZ) lattice based on parametric modeling. The designed BCCZ structures were able to maintain their strength whilst also retaining light weights. Ma et al. [4] have prepared diamond lattice structures with different material distributions using selected laser melting techniques. The mechanical behavior of the structures was investigated under quasi-static and dynamic loading, and the gradient sheet diamond (GSHD) was found to possess the highest yield strength. With regard to material and part properties, Shen et al. [5] used LPBF to fabricate SiC-reinforced Al–Zn–Mg–Cu composites in situ. The results showed that the organization of the composites was regulated, the matrix grains were refined, and the grain orientation growth was suppressed. In a similar fashion, to improve the mechanical properties of the AlSi10Mg alloy prepared by LPBF, Lu et al. [6] have investigated the effect of nano-Si3N4 reinforcement on the densification behavior, microstructure, and tensile properties of AlSi10Mg. It was revealed that the tensile and yield

**Citation:** Liu, M.; Yi, H.; Cao, H. Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend. *Crystals* **2023**, *13*, 92. https:// doi.org/10.3390/cryst13010092

Received: 30 December 2022 Accepted: 3 January 2023 Published: 4 January 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

strengths of the composites steadily increased with increasing nano-Si3N<sup>4</sup> content, while the elongation decreased. Li et al. [7] have analyzed the fracture behavior of 316L stainless steel fabricated with defects by selective laser melting using a near-field kinetic approach. They demonstrated that crack sprouting is caused by the defects and crack branching contributes to complex multi-crack extensions. The effect of scanning strategy on the quality of the manufactured part is also important in process optimization. Cao et al. [8] have examined the effect of the transient temperature field of the molten layer in LPBF under linear and annular laser scanning strategies on the forming accuracy and quality of the manufactured part. Their analysis identified that annular scanning was more suitable than linear bidirectional scanning for the high-precision fabrication of thin-walled Fe–Cr–Al overlays. Other laser-based additive manufacturing processes such as laser cladding have also been the focus of attention. Wang et al. [9] used this technique to produce WC (hard tungsten carbide) Co–Cr alloy coatings with different mass fractions on 316L substrates. It was found that laser cladding of the Co–Cr–WC composite layer could significantly improve the wear and corrosion resistance of the 316L substrate. Lasers also have the important ability to fabricate micro/nanostructures. Du et al. [10] have manufactured Se-doped silicon thin films by irradiating Si–Se bilayer-coated silicon with femtosecond (fs) and picosecond (ps) lasers. Their work revealed that the changes brought about by ps laser processing are significant for ultrafast laser processing of brass-doped silicon in silicon-based integrated circuits. Ultrafast lasers can effectively process special materials and improve the mechanical properties of parts, giving them the advantage over short pulse lasers and continuous wave lasers. Finally, Wu et al. [11] have reviewed the interaction mechanisms between ultrafast lasers and metallic materials and discussed the current status and challenges of ultrafast laser application in the formation of special materials.

Aside from laser-based additive manufacturing processes, fused deposition modeling (FDM), projection stereolithography, and resistive additive manufacturing are also discussed. Tura et al. [12] have used adaptive neuro-fuzzy methods and artificial neural networks to predict the tensile strength of ABS parts manufactured using fused deposition models. The results showed that an enhanced mechanical strength can be achieved by optimizing the process parameters. Based on FDM technology, Yang et al. [13] have explored an additive manufacturing process based on continuous carbon fiber-reinforced polylactic acid (PLA) composite prepreg filaments, resulting in the direct additive manufacture of lightweight and high-strength composite honeycomb load-bearing structures. Regarding stereolithography, Wen et al. [14] introduced a structure optimization-based compensation method to improve the geometric accuracy of microstructures printed by projective stereolithography. As for resistive additive manufacturing, Li et al. [15] have optimized the relative process parameters and analyzed their effects on the morphology of coating formation.

The concept of additive manufacturing can also be extended to high-performance coating preparation, which has received increasing attention in recent years. Zhang et al. [16] have researched the tribological properties of different crystalline diamond coatings prepared by the microwave plasma chemical vapor deposition (MPCVD) method in dry and seawater environments, providing important insights into the wear behavior of diamond coatings in seawater. Zhou et al. [17] investigated the nanomechanical properties of Ni-Co-Al-Ce coatings fabricated by velocity oxygen-fuel (HVOF) spraying, providing vital predictions for the erosion resistance of MCrAlY coatings. Li et al. [18] have synthesized two types of cemented carbide tools based on WC–Co–Zr and WC–Ni–Zr, namely cemented carbide tools and functional gradient cemented carbide (FGC) tools with FCC-phase ZrN-rich surfaces, which have potential in future hybrid additive/subtractive manufacturing applications.

Green, intelligent, and high-performance manufacturing processes are the focus of this Special Issue; therefore, several other studies on manufacturing trends are herein presented. The influence of inclusions on the mechanical properties of spring steels is significant; thus, Li et al. [19] have investigated the effect of alkalinity and Al2O<sup>3</sup> content on slag viscosity and structure to explore their effect on inclusion removal from steel. The generation of coal fly ash (CFA) in manufacturing is a serious barrier in the development of eco-friendly process

manufacturing. Qi et al. [20] have constructed three different regression models to quickly and accurately predict the generation of CFA, thus saving time in planning of CFA disposal.

This Special Issue, "Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend," can be considered as a review of the progress of additive manufacturing over the past year in the areas of advanced materials, structural design, and manufacturing processes.

**Conflicts of Interest:** The author declares no conflict of interest.

## **References**


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## *Article* **Specific Sensitivity Analysis and Imitative Full Stress Method for Optimal BCCZ Lattice Structure by Additive Manufacturing**

**Haonan Li <sup>1</sup> , Weidong Yang 1,\* , Qianchao Ma <sup>1</sup> , Zhihan Qian <sup>1</sup> and Li Yang 2,\***


**Abstract:** Additive manufacturing (AM) can quickly and easily obtain lattice structures with light weight and excellent mechanical properties. Body-centered cubic (BCC) lattice structure is a basic type of lattice structure. BCC with Z strut (BCCZ) lattice structure is a derivative structure of BCC lattice structure, and it has good adaptability to AM. Generally, the thickness of each pillar in the BCCZ lattice structure is uniform, which results in the uneven stress distribution of each pillar. This makes the potential of light weight and high strength of the BCCZ lattice structure not fully played, and the utilization rate of materials can be further improved. This paper designs an optimization method. Through the structural analysis of a BCCZ lattice structure, an optimization method of a BCCZ lattice structure based on parametric modeling parameters is presented. The section radius of all pillars in the BCCZ lattice is taken as a design variable, and the specific sensitivity analysis method and simulated full stress optimization idea are successively used to determine the optimal section radius of each pillar. Finally, the corresponding model is designed and samples are manufactured by LPBF technology for simulation and experimental verification. The results of simulation and experiment show that the strength limit of the optimized parts increased by 18.77% and 18.43%, respectively, compared with that before optimization.

**Keywords:** additive manufacturing; lattice structures; BCCZ; specific sensitivity analysis; imitative full stress method

## **1. Introduction**

Based on the principle of discrete stacking, AM realizes model design through computer aided design (CAD) and direct manufacturing driven by 3D data [1]. As an advanced manufacturing technology, AM has subverted the traditional manufacturing concept and has incomparable unique advantages in manufacturing complexity and special structures, bringing conceptual innovation to the entire manufacturing industry [2]. Compared with traditional manufacturing methods, AM makes up for the vacancy of traditional manufacturing methods, enabling parts that in the past were difficult to manufacture or could not be manufactured or had high manufacturing costs to be processed and manufactured [3]. One of the most outstanding advantages of AM is that it increases the degree of freedom of design, which is very helpful for the manufacturing of lattice structures. In the past two decades, AM has been rapidly developed and applied. Powder bed fusion (PBF) is a group of AM techniques. When equipped with lasers as energy sources, the processes are also known as laser powder bed fusion (LPBF). LPBF is also commercially known as selective laser melting (SLM) or direct metal laser melting, which is shown in Figure 1 [4]. LPBF can fabricate complex components by melting metal powders layer by layer using a high-energy laser beam and generally can be used for producing complicated parts [5]. The forming size is getting smaller and smaller, reaching the millimeter level. The printing material has also achieved the transition from the past titanium alloy to the present aluminum alloy [6]. At the same time, relevant enterprises around the world have also begun to increase

**Citation:** Li, H.; Yang, W.; Ma, Q.; Qian, Z.; Yang, L. Specific Sensitivity Analysis and Imitative Full Stress Method for Optimal BCCZ Lattice Structure by Additive Manufacturing. *Crystals* **2022**, *12*, 1844. https:// doi.org/10.3390/cryst12121844

Academic Editors: Hao Yi, Huajun Cao, Menglin Liu and Le Jia

Received: 24 November 2022 Accepted: 14 December 2022 Published: 16 December 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the research and development of AM equipment, and have made relatively successful progress, and are gradually realizing the commercialization of AM equipment [7]. With the upgrading and development of AM equipment, the gap between structural design and manufacturing has been further narrowed, and the manufacturing problems of millimeter scale complex structures have been solved. Structural design benefiting from AM has gradually entered the perspective of designers [8]. The design method for AM reduces the manufacturing constraints in the traditional design concept, making the forming of millimeter scale complex structures more simple and direct forming possible, which helps to achieve parametric control of complex structures [9]. The lattice structure benefits from the development of AM, and its shortcomings that were difficult to manufacture in the past have been solved to a large extent. It has many characteristics such as light weight, high strength, excellent energy absorption, good thermal performance, sound insulation and noise reduction, and biocompatibility [10–13]. Different from the traditional civil construction industry, the lattice structure oriented to AM is usually at the millimeter level. The appearance of AM makes the lattice structure design break through the size constraints and can realize the design and manufacturing at the millimeter level [14]. In recent years, successful cases of the combination of lattice structure design and AM have been emerging, and the feasibility of this scheme is constantly being verified. The emergence and development of AM provide a new solution to the problem that the lattice structure has been difficult to be manufactured by traditional manufacturing methods, and provide support and help for the design of millimeter level lattice structure [15–17]. made relatively successful progress, and are gradually realizing the commercialization of AM equipment [7]. With the upgrading and development of AM equipment, the gap be‐ tween structural design and manufacturing has been further narrowed, and the manufac‐ turing problems of millimeter scale complex structures have been solved. Structural de‐ sign benefiting from AM has gradually entered the perspective of designers [8]. The de‐ sign method for AM reduces the manufacturing constraints in the traditional design con‐ cept, making the forming of millimeter scale complex structures more simple and direct forming possible, which helps to achieve parametric control of complex structures [9]. The lattice structure benefits from the development of AM, and its shortcomings that were difficult to manufacture in the past have been solved to a large extent. It has many char‐ acteristics such as light weight, high strength, excellent energy absorption, good thermal performance, sound insulation and noise reduction, and biocompatibility [10–13]. Differ‐ ent from the traditional civil construction industry, the lattice structure oriented to AM is usually at the millimeter level. The appearance of AM makes the lattice structure design break through the size constraints and can realize the design and manufacturing at the millimeter level [14]. In recent years, successful cases of the combination of lattice struc‐ ture design and AM have been emerging, and the feasibility of this scheme is constantly being verified. The emergence and development of AM provide a new solution to the problem that the lattice structure has been difficult to be manufactured by traditional manufacturing methods, and provide support and help for the design of millimeter level lattice structure [15–17].

to the present aluminum alloy [6]. At the same time,relevant enterprises around the world have also begun to increase the research and development of AM equipment, and have

*Crystals* **2022**, *12*, x FOR PEER REVIEW 2 of 19

**Figure 1.** Laser powder bed fusion process. **Figure 1.** Laser powder bed fusion process.

The research on the combination scheme of AM and lattice structure design in aero‐ space [18], automotive industry [19], biomedicine [20] and other aspects shows that AM and lattice structure design show a very broad development prospect in the field of light weight. With the help of AM, the design model of lattice structure has been greatly guar‐ anteed for manufacturing, and the lattice structure design for AM also provides research‐ ers with greater imagination space. At the same time, the steps of the entire AM process are more concise, which can greatly save manufacturing time and reduce manufacturing costs from the design end of the computer equipment to the manufacturing equipment [21]. The lattice structure produced by AM can meet the size and shape requirements and achieve millimeterlevel precision manufacturing, greatly ensure the performance require‐ ments, reduce material loss and improve material utilization. In economic development, large machines (such as aircraft, automobiles, etc.), after using the parts produced by the lattice structure design scheme for AM, reduce their own weight and energy consump‐ tion, so as to reduce all kinds of pollution caused by energy consumption and help to The research on the combination scheme of AM and lattice structure design in aerospace [18], automotive industry [19], biomedicine [20] and other aspects shows that AM and lattice structure design show a very broad development prospect in the field of light weight. With the help of AM, the design model of lattice structure has been greatly guaranteed for manufacturing, and the lattice structure design for AM also provides researchers with greater imagination space. At the same time, the steps of the entire AM process are more concise, which can greatly save manufacturing time and reduce manufacturing costs from the design end of the computer equipment to the manufacturing equipment [21]. The lattice structure produced by AM can meet the size and shape requirements and achieve millimeter level precision manufacturing, greatly ensure the performance requirements, reduce material loss and improve material utilization. In economic development, large machines (such as aircraft, automobiles, etc.), after using the parts produced by the lattice structure design scheme for AM, reduce their own weight and energy consumption, so as to reduce all kinds of pollution caused by energy consumption and help to achieve green development with AM as the core [22].

achieve green development with AM as the core [22]. BCC lattice structure is characterized by simple topology, strong designability, strong manufacturability, and excellent mechanical properties [23]. Moreover, it is worth noting that the success rate of BCC lattice structure in AM is very high in millimeter scale manufacturing, which is mainly due to the tilt angle of the pillar in the BCC lattice struc‐ ture. Leary et al. [24,25] quantified manufacturability of aluminum lattice strut elements by experiment. They set four possible strut inclination angles: 0, 35.26, 45 and 90 degrees BCC lattice structure is characterized by simple topology, strong designability, strong manufacturability, and excellent mechanical properties [23]. Moreover, it is worth noting that the success rate of BCC lattice structure in AM is very high in millimeter scale manufacturing, which is mainly due to the tilt angle of the pillar in the BCC lattice structure. Leary et al. [24,25] quantified manufacturability of aluminum lattice strut elements by experiment. They set four possible strut inclination angles: 0, 35.26, 45 and 90 degrees in a unit cell with equal side length and found that the manufacturability of struts at other angles was well beyond 0 degrees. BCCZ lattice structure is a derivative structure of BCC lattice structure. On the basis of retaining the advantages of BCC lattice structure with strong design, good

manufacturing and a high success rate in AM, its related performance has been greatly improved compared with BCC lattice structure due to the existence of a strengthened Z pillar [26–28]. Chua et al. [29] used the finite element analysis method to study the mechanical properties of lattice structure in order to avoid cracks and pores that may occur in the process of AM. Chen et al. [30] used the MIST optimization algorithm to optimize the pillar size inside the cell. Jin et al. [31] completed the parametric design by obtaining the cell length diameter ratio distribution matrix and mapping the matrix to the pillar size of the unit cell. In the above research, the manufacturability and optimization methods of struts in lattice structures were studied. However, in the current research, the optimization design of the BCCZ lattice structure for AM needs to be strengthened. At present, the thickness of each pillar in the BCZZ lattice structure is uniform, which easily leads to uneven stress distribution of each pillar. The advantage of the BCCZ lattice structure in light weight and great strength has not been fully utilized, and the utilization rate of materials can be further improved in order to further take advantage of the combination of AM and lattice structure to better release constraints. This paper takes BCCZ lattice structure as the research object. On the basis of a structural analysis of the BCCZ lattice structure, the section radius of all pillars in the BCCZ lattice structure is taken as the design variable. A BCCZ lattice structure optimization method based on the combination of specific sensitivity analysis and the idea of imitative full stress is proposed to maximize the material utilization of each pillar in the BCCZ lattice structure. Last, the optimization method in this paper is explained and verified by finite element simulation and experiment. Through the designed method in this paper, the dangerous stress in the BCCZ structure can be controlled within the allowable stress range, and the strength of the whole structure can be improved. The designed BCCZ structure can maintain better strength on the basis of light weight. strengthened Z pillar [26–28]. Chua et al. [29] used the finite element analysis method to study the mechanical properties of lattice structure in order to avoid cracks and pores that may occur in the process of AM. Chen et al. [30] used the MIST optimization algorithm to optimize the pillar size inside the cell. Jin et al. [31] completed the parametric design by obtaining the cell length diameter ratio distribution matrix and mapping the matrix to the pillar size of the unit cell. In the above research, the manufacturability and optimization methods of struts in lattice structures were studied. However, in the current research, the optimization design of the BCCZ lattice structure for AM needs to be strengthened. At present, the thickness of each pillar in the BCZZ lattice structure is uniform, which easily leads to uneven stress distribution of each pillar. The advantage of the BCCZ lattice struc‐ ture in light weight and great strength has not been fully utilized, and the utilization rate of materials can be furtherimproved in orderto furthertake advantage of the combination of AM and lattice structure to better release constraints. This paper takes BCCZ lattice structure as the research object. On the basis of a structural analysis of the BCCZ lattice structure, the section radius of all pillars in the BCCZ lattice structure is taken as the de‐ sign variable. A BCCZ lattice structure optimization method based on the combination of specific sensitivity analysis and the idea of imitative full stress is proposed to maximize the material utilization of each pillar in the BCCZ lattice structure. Last, the optimization method in this paper is explained and verified by finite element simulation and experi‐ ment. Through the designed method in this paper, the dangerous stress in the BCCZ struc‐ ture can be controlled within the allowable stress range, and the strength of the whole structure can be improved. The designed BCCZ structure can maintain better strength on the basis of light weight.

in a unit cell with equal side length and found that the manufacturability of struts at other angles was well beyond 0 degrees. BCCZ lattice structure is a derivative structure of BCC lattice structure. On the basis of retaining the advantages of BCC lattice structure with strong design, good manufacturing and a high success rate in AM, its related performance has been greatly improved compared with BCC lattice structure due to the existence of a

*Crystals* **2022**, *12*, x FOR PEER REVIEW 3 of 19

#### **2. Analysis of BCCZ Lattice Structure 2. Analysis of BCCZ Lattice Structure**

The lattice structure can be seen as a porous structure composed of many cells according to the set distribution rules. Chen et al. [32] summarized that the unit cell had an important impact on the characteristics of lattice structures, such as mechanical response, specific surface area, stiffness, pore size. Therefore, the unit cell is very representative in the lattice structure analysis [33]. Therefore, this section analyzes the BCCZ lattice structure from the perspective of the BCCZ unit cell. The lattice structure can be seen as a porous structure composed of many cells ac‐ cording to the set distribution rules. Chen et al. [32] summarized that the unit cell had an important impact on the characteristics of lattice structures, such as mechanical response, specific surface area, stiffness, pore size. Therefore, the unit cell is very representative in the lattice structure analysis [33]. Therefore, this section analyzes the BCCZ lattice struc‐ ture from the perspective of the BCCZ unit cell.

#### *2.1. BCCZ Unit Cell Topology Analysis 2.1. BCCZ Unit Cell Topology Analysis*

The BCCZ lattice structure is generally composed of BCCZ cells through X, Y and Z arrays. Figure 2 shows the BCCZ lattice structure and its corresponding unit cell structure diagram. The BCCZ lattice structure in Figure 2a is generated by BCCZ cells in Figure 2b through repeated arrays in X, Y and Z directions, and contains 5 × 3 × 2 cells, respectively. The BCCZ lattice structure is generally composed of BCCZ cells through X, Y and Z arrays. Figure 2 shows the BCCZ lattice structure and its corresponding unit cell structure diagram. The BCCZ lattice structure in Figure 2a is generated by BCCZ cells in Figure 2b through repeated arrays in X, Y and Z directions, and contains 5 × 3 ×2 cells, respectively.

**Figure Figure 2. 2.** ( ( **aa**) ) BCCZ lattice structure diagram; ( BCCZ lattice structure diagram; (**b b** ) ) BCCZ unit cell diagram. BCCZ unit cell diagram.

As shown in Figure 2a, the BCCZ lattice structure composed of BCCZ cells can be regarded as a micro truss structure, whose structural elements are composed of pillars and nodes. The topological structure of the BCCZ unit cell has little change compared with the BCC unit cell. Figure 3 shows the topology of the BCC unit cell and BCCZ unit cell, as well

as the numbering sequence of nodes and pillars inside the unit cells. The BCC unit cell central node (N9) and 8 outer nodes (N1–N8) are connected in the form of pillars, and the location of the central node is determined by Formula (1). On the basis of inheriting the topological configuration of the BCCZ unit cell, the BCCZ unit cell can be constructed by adding a strengthened Z pillar in the direction parallel to the load. That is, on the basis of node N1–N9, add P9 to P12 between nodes N1 to N5, N2 to N6, N3 to N7, and N4 to N8. *Crystals* **2022**, *12*, x FOR PEER REVIEW 4 of 19 As shown in Figure 2a, the BCCZ lattice structure composed of BCCZ cells can be regarded as a micro truss structure, whose structural elements are composed of pillars

$$\begin{cases} x\_{\theta} = \frac{1}{8} \sum\_{i=1}^{8} x\_i \\ y\_{\theta} = \frac{1}{8} \sum\_{i=1}^{8} y\_i \\ z\_{\theta} = \frac{8}{8} \sum\_{i=1}^{8} z\_i \end{cases} \tag{1}$$

where (*x*9, *y*9, *z*9) is the coordinate of central node N9, and (*x<sup>i</sup>* , *y<sup>i</sup>* , *zi*) corresponds to the coordinate of outer nodes N1–N8. structed by adding a strengthened Z pillar in the direction parallel to the load. That is, on the basis of node N1–N9, add P9 to P12 between nodes N1 to N5, N2 to N6, N3 to N7, and N4 to N8.

**Figure 3.** Topological structure comparison diagram of BCC unit cell and BCCZ unit cell and num‐ bering sequence of each pillar: (**a**) BCC; (**b**) BCCZ. **Figure 3.** Topological structure comparison diagram of BCC unit cell and BCCZ unit cell and numbering sequence of each pillar: (**a**) BCC; (**b**) BCCZ.

଼

#### *2.2. Parametric Modeling*

as a cube [34].

outer pillar is

ᇱ

⎨ ⎪ ⎪ ⎪ ⎧ଽ ൌ <sup>1</sup> <sup>8</sup> ୀଵ ଽ ൌ <sup>1</sup> <sup>8</sup> ଼ ୀଵ (1) The topological analysis of Section 2.1 is helpful to realize the parametric modeling of the BCCZ unit cell, and then the parametric modeling of the BCCZ lattice structure can be realized. In the current research, the modeling precondition is to set the section shape of the BCCZ lattice structure pillar as a circle, and the external geometry of BCCZ unit cell as a cube [34].

⎩ ⎪ ⎪ ⎪ ଽ ൌ <sup>1</sup> <sup>8</sup> ଼ ୀଵ where ሺଽ, ଽ, ଽሻ is the coordinate of central node N9, and ሺ, , ሻ corresponds to the coordinate of outer nodes N1–N8. *2.2. Parametric Modeling* The topological analysis of Section 2.1 is helpful to realize the parametric modeling of the BCCZ unit cell, and then the parametric modeling of the BCCZ lattice structure can Figure 4 shows the BCCZ lattice structure decomposition steps. The BCCZ lattice structure can be divided into many BCCZ cells. The BCCZ unit cell can be divided into eight inclined pillars of cylinders and four outer pillars of 1/4 cylinders. Among them, each outer pillar intersects two inclined pillars, and eight inclined pillars intersect at the central node. The side length of the cell is set as *S*, the length of the inclined pillar is *li*(*i* = 1, 2, . . . . . . , 8), the section radius of the inclined pillar is *ri*(*i* = 1, 2, . . . . . . , 8), the length of the outer pillar is *l* 0 *i* (*i* = 9, 10, 11, 12), and the section radius of the outer pillar is *r* 0 *i* (*i* = 9, 10, 11, 12). Formulas (2)–(4) show the fixed geometric relationship in the BCCZ unit cell:

be realized. In the current research, the modeling precondition is to set the section shape of the BCCZ lattice structure pillar as a circle, and the external geometry of BCCZ unit cell

Figure 4 shows the BCCZ lattice structure decomposition steps. The BCCZ lattice structure can be divided into many BCCZ cells. The BCCZ unit cell can be divided into eight inclined pillars of cylinders and four outer pillars of 1/4 cylinders. Among them, each outer pillar intersects two inclined pillars, and eight inclined pillars intersect at the central node. The side length of the cell is set as , the length of the inclined pillar is ሺ ൌ unit cell:

(2) Outer pillar length

**Figure 4.** Analysis of design parameters of BCCZ lattice structure. **Figure 4.**Analysis of design parameters of BCCZ lattice structure.

(1) Inclined pillar length and unit cell side length : (1) Inclined pillar length *l<sup>i</sup>* and unit cell side length *S*:

$$l\_i = \frac{\sqrt{3}}{2} \text{S} \tag{2}$$

 ൌ <sup>√</sup><sup>3</sup> <sup>2</sup> (2) <sup>ᇱ</sup> and unit cell side length : (2) Outer pillar length *l* 0 *i* and unit cell side length *S*:

$$l'\_i = \mathbb{S} \tag{3}$$

 <sup>ᇱ</sup> ൌ (3) (3) Angle between inclined pillar and horizontal direction *θ*:

$$\theta = \sin^{-1} \frac{1}{\sqrt{3}} \tag{4}$$

 ൌ sinିଵ <sup>1</sup> <sup>√</sup><sup>3</sup> (4) To sum up, the parametric modeling of the BCCZ unit cell can be completed through unit cell side length , the section radius ሺ ൌ 1,2, … … ,8ሻ of the inclined pillar and the section radius ᇱ ሺ ൌ 9,10,11,12ሻ of the outer pillar. By assigning the above design pa‐ rameters, BCCZ cells with different structural parameters can be obtained. The BCCZ unit cell is an outstanding representative of the BCCZ lattice structure. According to the struc‐ tural relationship between the two, the structural parameters of the BCCZ lattice structure can be summarized as unit cell side length , the section radius ሺ ൌ 1,2, … … ,8ሻ of the To sum up, the parametric modeling of the BCCZ unit cell can be completed through unit cell side length *S*, the section radius *ri*(*i* = 1, 2, . . . . . . , 8) of the inclined pillar and the section radius *r* 0 *i* (*i* = 9, 10, 11, 12) of the outer pillar. By assigning the above design parameters, BCCZ cells with different structural parameters can be obtained. The BCCZ unit cell is an outstanding representative of the BCCZ lattice structure. According to the structural relationship between the two, the structural parameters of the BCCZ lattice structure can be summarized as unit cell side length *S*, the section radius *ri*(*i* = 1, 2, . . . . . . , 8) of the inclined pillar, the section radius *r* 0 *i* (*i* = 9, 10, 11, 12) of the outer pillar, X, Y and the number of cells in Z direction x, y and z.

#### inclined pillar, the section radius ᇱ ሺ ൌ 9,10,11,12ሻ of the outer pillar, X, Y and the num‐ **3. Optimization Method**

ber of cells in Z direction x, y and z. **3. Optimization Method** The current optimization of lattice structure can be summarized in the following two aspects. On the one hand, a few researchers changed the cell strut into a curve by remov‐ ing the constraint that the section radius of the cell strut is equal everywhere. On the macro level, it reflects that the shape of the lattice structure pillar has changed, and the optimi‐ zation at the cell level has been realized by reducing the impact of stress concentration, which has realized the innovation of cell configuration to a certain extent [35]. On the other hand, because it is difficult to propose new unit cell configurations, most researchers still use various optimization methods (such as topology optimization) to optimize and design lattice structures with better performance on the basis of existing unit cells [36,37]. According to the above two kinds of optimization ideas, this paper synthesizes their re‐ spective characteristics, and on the basis of the existing cell elements and the analysis in The current optimization of lattice structure can be summarized in the following two aspects. On the one hand, a few researchers changed the cell strut into a curve by removing the constraint that the section radius of the cell strut is equal everywhere. On the macro level, it reflects that the shape of the lattice structure pillar has changed, and the optimization at the cell level has been realized by reducing the impact of stress concentration, which has realized the innovation of cell configuration to a certain extent [35]. On the other hand, because it is difficult to propose new unit cell configurations, most researchers still use various optimization methods (such as topology optimization) to optimize and design lattice structures with better performance on the basis of existing unit cells [36,37]. According to the above two kinds of optimization ideas, this paper synthesizes their respective characteristics, and on the basis of the existing cell elements and the analysis in Section 2, takes the section radius of each pillar of BCCZ lattice structure as an independent design variable and relieves the constraint that the section radius between the pillars is equal. A BCCZ lattice structure optimization method combining specific sensitivity analysis and imitative full stress design method is proposed. Figure 5 shows the design process of this method.

Section 2, takes the section radius of each pillar of BCCZ lattice structure as an independ‐ ent design variable and relieves the constraint that the section radius between the pillars

is equal. A BCCZ lattice structure optimization method combining specific sensitivity analysis and imitative full stress design method is proposed. Figure 5 shows the design

**Figure 5.** Procedures for the optimization design of specific sensitivity analysis and imitative full stress design. **Figure 5.** Procedures for the optimization design of specific sensitivity analysis and imitative full stress design.

#### *3.1. Specific Sensitivity Analysis 3.1. Specific Sensitivity Analysis*

process of this method.

According to the analysis in Section 2.2, the number of pillars of the BCCZ lattice structure is large, which leads to many variables to be designed. As a result, BCCZ lattice structure optimization is difficult to design, and complex design problems and a reason‐ able optimization design scheme are difficult to determine. To solve this problem, this paper uses the method of specific sensitivity analysis to distinguish the design variables and solve the optimization direction of each design variable, so as to carry out the follow‐ According to the analysis in Section 2.2, the number of pillars of the BCCZ lattice structure is large, which leads to many variables to be designed. As a result, BCCZ lattice structure optimization is difficult to design, and complex design problems and a reasonable optimization design scheme are difficult to determine. To solve this problem, this paper uses the method of specific sensitivity analysis to distinguish the design variables and solve the optimization direction of each design variable, so as to carry out the follow-up optimization work.

up optimization work. The concept of sensitivity is often used in rigid frame structures in practical projects. It can be used to express the degree of influence on a certain performance of the overall structure when a variable changes [38]. In this paper, the design variable is the section radius of each pillar of the BCCZ lattice structure, that is, the section radius of inclined pillar and the section radius <sup>ᇱ</sup> of outer pillar, and the influence performance can be a mechanical property of the BCCZ lattice structure [39]. The mathematical model of sensi‐ tivity is shown in Formula (5). The concept of sensitivity is often used in rigid frame structures in practical projects. It can be used to express the degree of influence on a certain performance of the overall structure when a variable changes [38]. In this paper, the design variable is the section radius of each pillar of the BCCZ lattice structure, that is, the section radius *r<sup>i</sup>* of inclined pillar and the section radius *r* 0 *i* of outer pillar, and the influence performance can be a mechanical property of the BCCZ lattice structure [39]. The mathematical model of sensitivity is shown in Formula (5).

$$P = p\left(r\_{1\prime}, \dots, r\_{\dot{1}\prime}, \dots, r\_{\mathfrak{m}\prime}, r\_{1\prime}^{\prime}, \dots, r\_{\dot{1}\prime}^{\prime}, \dots, \dots, r\_{\mathfrak{n}\prime}^{\prime}\right) \tag{5}$$

where is the performance function of BCCZ lattice structure, is the number of in‐ clined pillars and is the number of outer pillars. where *P* is the performance function of BCCZ lattice structure, *m* is the number of inclined pillars and *n* is the number of outer pillars.

The change in the BCCZ lattice structure performance caused by the increment or <sup>ᇱ</sup> of any pillar section radius change is , namely: The change in the BCCZ lattice structure performance caused by the increment *dr<sup>i</sup>* or *dr*0 *i* of any pillar section radius change is *dP*, namely:

$$dP = \frac{\partial p}{\partial r\_1} dr\_1 + \dots + \frac{\partial p}{\partial r\_l} dr\_l + \dots + \frac{\partial p}{\partial r\_m} dr\_m + \frac{\partial p}{\partial r'\_1} dr'\_1 + \dots + \frac{\partial p}{\partial r'\_l} dr'\_l + \dots + \frac{\partial p}{\partial r'\_n} dr'\_n = \sum\_{i=1}^m \frac{\partial p}{\partial r'\_i} dr\_i + \sum\_{i=5}^n \frac{\partial p}{\partial r'\_i} dr'\_i \tag{6}$$

where the partial derivative of the performance function of the BCCZ lattice structure to the section radius or <sup>ᇱ</sup> of the pillar is the performance sensitivity of the BCCZ lat‐ tice structure. where the partial derivative of the performance function *P* of the BCCZ lattice structure to the section radius *r<sup>i</sup>* or *r* 0 *i* of the pillar is the performance sensitivity of the BCCZ lattice structure.

The performance sensitivity analysis can be used to determine the design variables that have a significant impact on the overall performance of the BCCZ lattice structure among the BCCZ lattice structure optimization design variables, and formulate an The performance sensitivity analysis can be used to determine the design variables that have a significant impact on the overall performance of the BCCZ lattice structure among the BCCZ lattice structure optimization design variables, and formulate an optimization design scheme to improve the optimization efficiency. However, the advantage of the BCCZ lattice structure over strength cannot be fully exploited by analyzing performance sensitivity only. Xu et al. [40] designed some lattice structures with different relative densities (0.15–0.5) and carried out experimental monitoring. They systematically studied the effect of relative density on the compressive properties of lattice structures, including mechanical properties, failure mechanisms and energy absorption capacity. The results show that the compressibility of the lattice structure changes significantly with the change of the relative density, and the performance of the lattice structure can usually be improved by simply increasing the section radius. In other words, when the section radius is very sensitive to the performance and mass, if the design variable is optimized, the BCCZ lattice structure performance will be improved as well as the BCCZ lattice structure mass. That is, the reason for the BCCZ lattice structure performance improvement may be achieved by adding materials, which violates the original optimization intention of greatly improving the material utilization. In this paper, the concept of specific sensitivity is introduced to find out the performance sensitivity of design variables under unit mass and the mass sensitivity of design variables under unit performance.

In this paper, the specific sensitivity is defined as the ratio of the sensitivity of the BCCZ lattice structure performance to the pillar section radius and the sensitivity of the BCCZ lattice structure mass to the pillar section radius, namely:

$$
\eta\_i = \frac{\varepsilon\_i}{a\_i} \tag{7}
$$

where *η<sup>i</sup>* is the specific sensitivity, *ε<sup>i</sup>* is the performance sensitivity and *α<sup>i</sup>* is the mass sensitivity.

Because it is difficult to obtain the sensitivity value directly through the theoretical formula, at the same time, there is a complex stress concentration phenomenon at the node of the BCCZ lattice structure, and the coupling between design variables is also complex, there are many problems and difficulties in applying the analytical method directly [41,42]. Therefore, this paper used finite element analysis tools to extract the values of performance sensitivity and mass sensitivity. The following example is to illustrate the method.

According to Formula (6), if the variable is *x<sup>i</sup>* , the performance function is *p<sup>i</sup>* ; when the variable is increased by one unit, the performance function corresponding to *xi*+<sup>1</sup> is *pi*+<sup>1</sup> .

$$\begin{cases} dP = p\_{i+1} - p\_i \\ d\mathbf{x}\_i = \mathbf{x}\_{i+1} - \mathbf{x}\_i = 1 \end{cases} \tag{8}$$

That is, when the mass unit changes,

$$
\varepsilon\_i = \frac{\partial p}{\partial x\_i} = dP \tag{9}
$$

The values of *pi*+<sup>1</sup> and *p<sup>i</sup>* are extracted by finite element analysis tools, and the performance sensitivity value of any design variable *x<sup>i</sup>* can be obtained by Formulas (8) and (9).

The mass sensitivity can also be obtained by the above method, and the specific sensitivity can be obtained by Formula (7). At the same time, in order to make the specific sensitivity value more accurate, this paper obtains the final specific sensitivity value by setting multiple groups of data and curve fitting multiple groups of results. According to the specific sensitivity value obtained, the optimal design scheme can be further formulated on the basis of determining the design variables. Its purpose is:


## *3.2. Imitative Full Stress Optimization Method*

Through the analysis of Section 3.1, the design variables and their optimization directions can be determined, and the optimization design scheme can be preliminarily obtained. For the design variables to be optimized, this paper refers to the idea of imitative full stress design and proposes an optimization method for the cross section dimensions of each

pillar of the BCCZ lattice structure. The basic idea of imitative full stress is to make the most unfavorable stress in structural members approach or reach the allowable stress of materials, so as to make full use of materials. The mathematical model of this method is established as follows.

1. Optimization design variables: the BCCZ lattice structure section radius *r<sup>i</sup>* of inclined pillar and section radius *r* 0 *i* of outer pillar.

$$R = \left(r\_{1'} \dots r\_{m'} r'\_{1'} \dots r'\_{n}\right) \tag{10}$$

2. Objective function: the overall mass of the BCCZ lattice structure. The objective of optimization is to minimize the objective function.

$$\min \ W \approx \frac{\sqrt{3}}{2} \sum\_{i=1}^{m} \pi r\_i^2 \mathcal{S} + \sum\_{i=1}^{n} \pi r\_i^{\mu^2} \mathcal{S} \tag{11}$$

3. Constraint 1: the strength of each pillar approximates the allowable stress value.

$$\mathbb{C}(\mathbf{x}) = \sigma\_{\text{imax}} - [\sigma\_{\text{i}}] \cong \mathbf{0} \tag{12}$$

In the formula, ∼= is a symbol to describe the imitative full stress, which means that the value on the left of the symbol is infinitely close to but not more than the value on the right of the symbol, *σimax* is the maximum von Mises stress of pillar *i* under a certain condition, and [*σ<sup>i</sup>* ] is the allowable stress of pillar materials of the BCCZ lattice structure.

4. Constraint 2: The value range of each pillar radius of the BCCZ lattice structure shall be between the minimum manufacturing size and the maximum space size of AM.

$$\begin{cases} r\_{i\_{\min}} \le r\_i \le r\_{i\_{\max}}\\ r'\_{i\_{\min}} \le r'\_i \le r'\_{i\_{\max}} \end{cases} \tag{13}$$

where *rimin* and *r* 0 *imin* are the minimum manufacturing dimensions of AM, set as 0.5 mm according to [24,25,43], and *rimax* and *r* 0 *imax* are the maximum space dimensions of AM. Considering the application scope of the pillar, 30% of the pillar length is selected as the upper limit of the section radius.

Therefore, the steps of the imitative full stress optimization method in this paper are as follows.

1. In the initial stage, set a reasonable set of section radius of each pillar.

$$R^0 = \left\{ r\_1^0, \dots, r\_m^0, r\_1^0, \dots, r\_n^0 \right\} \tag{14}$$

where *R* 0 represents the set of initial section radius of each pillar, and *r* 0 *i r* 0 0 *i* represents the initial value of pillar *i*.

2. Structural analysis. Similar to the difficulties encountered in applying the analytical method to the specific sensitivity analysis, this paper chooses to use the finite element analysis tool to obtain the maximum von Mises stress value and the minimum von Mises stress value of each pillar of the BCCZ lattice structure, namely *σimax* and *σimin*, and sort them in descending and ascending order, respectively, and set

$$\begin{cases} \sigma\_{\max} = \max \{ \sigma\_{i \max} \} (i = 1, 2, \dots, m + n) \\ \sigma\_{\min} = \min \{ \sigma\_{i \min} \} (i = 1, 2, \dots, m + n) \end{cases} \tag{15}$$

where *σmax* and *σmin* are the maximum von Mises stress and minimum von Mises stress of the BCCZ lattice structure as a whole, respectively.

	- 4. When *σmax* > [*σ<sup>i</sup>* ], it indicates that the overall strength of the BCCZ lattice structure under the current section radius of each pillar is too large, and the section radius of the pillar where the maximum von Mises stress is located must be increased, and then go to step 2 again to update the structural analysis results. When the condition *σmax* ≤ [*σ<sup>i</sup>* ] is met, jump out of the cycle and output the value of the current section radius of each pillar. If the end of cycle condition cannot be satisfied all the time, the optimization is terminated because there is no feasible solution to the problem. 3. Strength verification. Compare the ௫ obtained in step 2 with the allowable stress ሾሿ, and enter the corresponding iteration cycles 4 and 5 according to the comparison results. 4. When ௫ ሾሿ, it indicates that the overall strength of the BCCZ lattice structure under the current section radius of each pillar is too large, and the section radius of the pillar where the maximum von Mises stress is located must be increased, and then go to step 2 again to update the structural analysis results. When the condition
	- 5. When *σmax* ≤ [*σ<sup>i</sup>* ], it indicates that the materials of some pillars may not be fully utilized under the current section radius of each pillar, so it is necessary to find out the corresponding pillar and reduce the section radius of the corresponding pillar, and turn to step 2 again. According to the new structure analysis results, it can be divided into the following two cases: ௫ ሾሿ is met, jump out of the cycle and output the value of the current section radius of each pillar. If the end of cycle condition cannot be satisfied all the time, the optimization is terminated because there is no feasible solution to the problem. 5. When ௫ ሾሿ, it indicates that the materials of some pillars may not be fully uti‐ lized under the current section radius of each pillar, so it is necessary to find out the
		- (1) *σmax* ≤ [*σ<sup>i</sup>* ]: It shows that the material is still not fully utilized under the current section radius of each pillar, so the section radius of the pillar where the current minimum von Mises stress is located must be reduced, and go to step 2. If *σmax* ≤ [*σ<sup>i</sup>* ] is still satisfied until the minimum value of the optimization variable is obtained, the minimum value is output. corresponding pillar and reduce the section radius of the corresponding pillar, and turn to step 2 again. According to the new structure analysis results, it can be divided into the following two cases: (1) ௫ ሾሿ: It shows that the material is still not fully utilized under the current section radius of each pillar, so the section radius of the pillar where the current
		- (2) *σmax* > [*σ<sup>i</sup>* ]: It shows that the pillar with the reduced section radius in the previous step has reached the material utilization limit. It is necessary to sort out the results of the structural analysis in the previous step according to the minimum von Mises stress value, find the pillar with the next von Mises stress and reduce its section radius, and then turn to step 2. If the section radius of all optimized pillars is reduced once by continuous traversal, the cycle will be skipped and the section radius of each pillar meeting *σmax* ≤ [*σ<sup>i</sup>* ] will be output. minimum von Mises stress is located must be reduced, and go to step 2. If ௫ ሾሿ is still satisfied until the minimum value of the optimization varia‐ ble is obtained, the minimum value is output. (2) ௫ ሾሿ: It shows that the pillar with the reduced section radius in the previ‐ ous step has reached the material utilization limit. It is necessary to sort out the results of the structural analysis in the previous step according to the minimum von Mises stress value, find the pillar with the next von Mises stress and reduce its section radius, and then turn to step 2. If the section radius of all optimized pillars is reduced once by continuous traversal, the cycle will be skipped and the
	- 6. The values of each pillar obtained in Cycle 4 and Cycle 5 constitute the final optimization results. section radius of each pillar meeting ௫ ሾሿ will be output. 6. The values of each pillar obtained in Cycle 4 and Cycle 5 constitute the final optimi‐ zation results.

$$R^m = \left\{ r\_{1'}^\mu \dots \dots r\_{m'}^\mu r\_{5'}^\nu \dots r\_n^{\nu} \right\} \tag{16}$$

where *u* and *v* are the number of iterations in the two cycles, respectively. ൌ ൛ଵ <sup>௨</sup>,…, <sup>௨</sup>, ହ , … ൟ (16)

Figure 6 shows the step flow chart of the imitative full stress optimization method. where and are the number of iterations in the two cycles, respectively. Figure 6 shows the step flow chart of the imitative full stress optimization method.

**Figure 6. Figure 6.** Flow Flow chart of imitative full stress optimization method. chart of imitative full stress optimization method.

#### **4. Example 4. Example**

#### *4.1. Models for the Test 4.1. Models for the Test*

In this paper, numerical examples are given to verify the effectiveness of the proposed optimization method for the BCCZ lattice structure parameters. The optimization goal is to improve the compressive strength of the test model. As unit cell is very representative in the study of lattice structure, the BCCZ unit cell was selected as a test case to illustrate. The BCCZ unit cell size was set as 5 mm, the initial section radius of each pillar was 0.5 mm, and the allowable stress [*σ<sup>i</sup>* ] was set as 120 MPa. The numbering sequence of the BCCZ unit cell is shown in Figure 3. The BCCZ unit cell numerical model was designed based on this, and the model diagram is shown in Figure 7. In this paper, numerical examples are given to verify the effectiveness of the pro‐ posed optimization method for the BCCZ lattice structure parameters. The optimization goal is to improve the compressive strength of the test model. As unit cell is very repre‐ sentative in the study of lattice structure, the BCCZ unit cell was selected as a test case to illustrate. The BCCZ unit cell size was set as 5 mm, the initial section radius of each pillar was 0.5 mm, and the allowable stress ሾሿ was set as 120 MPa. The numbering sequence of the BCCZ unit cell is shown in Figure 3. The BCCZ unit cell numerical model was de‐ signed based on this, and the model diagram is shown in Figure 7.

**Figure 7.** Test case—BCCZ unit cell initial model. **Figure 7.** Test case—BCCZ unit cell initial model.

#### *4.2. Optimization Results 4.2. Optimization Results*

According to the analysis conclusion in Section 2.2, the BCCZ unit cell test case was analyzed for specific sensitivity, and each pillar was taken as an independent variable to evaluate the impact of the section radius of each pillar on the overall performance. The results of specific sensitivity from pillar P1 to pillar P12 are shown in Table 1. According to the analysis conclusion in Section 2.2, the BCCZ unit cell test case was analyzed for specific sensitivity, and each pillar was taken as an independent variable to evaluate the impact of the section radius of each pillar on the overall performance. The results of specific sensitivity from pillar P1 to pillar P12 are shown in Table 1.


P11 −5.18 P12 −4.97

**Table 1.** Specific sensitivity result of pillars P1 to P12. **Table 1.** Specific sensitivity *η<sup>i</sup>* result of pillars P1 to P12.

According to the specific sensitivity analysis results shown in Table 1, the following optimization design scheme can be obtained according to the specific sensitivity analysis results processing method in Section 3.1. optimization design scheme can be obtained according to the specific sensitivity analysis results processing method in Section 3.1. (1) The section radius of P1–P8 is reduced, so that the mass of BCCZ unit cell is reduced

According to the specific sensitivity analysis results shown in Table 1, the following


According to the above design scheme, the optimization of the BCCZ unit cell can be divided into two directions. First, the initial BCCZ unit cell was analyzed by the finite element method. At this time, the maximum equivalent stress was greater than the allowable stress. The BCCZ unit cell strength needs to be improved according to the optimal design scheme (2). After the imitative full stress optimization iteration at this stage, the section radius of the pillars P9–P12 was increased, making the maximum equivalent stress less than the allowable stress, so that the test case met the strength requirements. Secondly, after the strength requirements were met, the pursuit of minimizing the overall mass was started. At this time, the mass of BCCZ unit cell should be reduced according to the optimal design scheme (1) under the framework where the maximum equivalent stress is less than the allowable stress. After the imitative full stress optimization iteration at this stage, the minimum section radius of the P1–P8 pillars under the strength requirements was calculated. Finally, the optimization results of the two stages were combined to output the optimization results of the imitative full stress of pillars P1–P12. The final optimization results are shown in Table 2 and Figure 8. divided into two directions. First, the initial BCCZ unit cell was analyzed by the finite element method. At this time, the maximum equivalent stress was greater than the allow‐ able stress. The BCCZ unit cell strength needs to be improved according to the optimal design scheme (2). After the imitative full stress optimization iteration at this stage, the section radius of the pillars P9–P12 was increased, making the maximum equivalent stress less than the allowable stress, so that the test case met the strength requirements. Sec‐ ondly, after the strength requirements were met, the pursuit of minimizing the overall mass was started. At this time, the mass of BCCZ unit cell should be reduced according to the optimal design scheme (1) under the framework where the maximum equivalent stress is less than the allowable stress. After the imitative full stress optimization iteration at this stage, the minimum section radius of the P1–P8 pillars under the strength require‐ ments was calculated. Finally, the optimization results of the two stages were combined to output the optimization results of the imitative full stress of pillars P1–P12. The final optimization results are shown in Table 2 and Figure 8.


*Crystals* **2022**, *12*, x FOR PEER REVIEW 11 of 19


P12 0.9

**Figure Figure 8. 8.** BCCZ BCCZ unit cell comparison before and after imitative full stress optimization. unit cell comparison before and after imitative full stress optimization.

## **5. Numerical Simulation and Experimental Verification**

*Crystals* **2022**, *12*, x FOR PEER REVIEW 12 of 19

In order to verify the effectiveness of the proposed optimization method, the optimized BCCZ unit cell obtained in Section 4.2 was simulated and verified by experiments. In terms of the manufacturing of experimental samples, Yu et al. [44], Tang et al. [45] and Dong et al. [46] used, respectively, the electron beam powder bed fusion (EBPBF), binder jetting (BJ) and fused deposition modeling (FDM) techniques to manufacture corresponding experimental samples for their own research experiments. In order to ensure that the samples have high accuracy, this paper selected LPBF technology to manufacture the corresponding experimental samples. In recent years, AlSi10Mg material has been used more and more for the fabrication of AM'ed parts, which has good molding effect and cheaper cost, and low-density and high strength. At the same time, it is suitable for manufacturing lattice structures [24,47]. The experimental sample in this paper was formed by LPBF with a light weight structure, considering the economic rationality. Therefore, light material AlSi10Mg alloy powder with good welding formability, thermal conductivity and corrosion resistance was selected [7]. The chemical composition and physicomechanical properties of the AlSi10Mg alloy powder used for simulation and experiment are shown in Tables 3 and 4. **5. Numerical Simulation and Experimental Verification** In order to verify the effectiveness of the proposed optimization method, the opti‐ mized BCCZ unit cell obtained in Section 4.2 was simulated and verified by experiments. In terms of the manufacturing of experimental samples, Yu et al. [44], Tang et al. [45] and Dong et al. [46] used, respectively, the electron beam powder bed fusion (EBPBF), binder jetting (BJ) and fused deposition modeling (FDM) techniques to manufacture correspond‐ ing experimental samples for their own research experiments. In order to ensure that the samples have high accuracy, this paper selected LPBF technology to manufacture the cor‐ responding experimental samples. In recent years, AlSi10Mg material has been used more and more for the fabrication of AM'ed parts, which has good molding effect and cheaper cost, and low‐density and high strength. At the same time, it is suitable for manufacturing lattice structures [24,47]. The experimental sample in this paper was formed by LPBF with a light weight structure, considering the economic rationality. Therefore, light material AlSi10Mg alloy powder with good welding formability, thermal conductivity and corro‐ sion resistance was selected [7]. The chemical composition and physicomechanical prop‐ erties of the AlSi10Mg alloy powder used for simulation and experiment are shown in Ta‐

**Table 3.** Chemical composition of AlSi10Mg. bles 3 and 4.


**Table 4.** Physicomechanical properties of AlSi10Mg. **Table 4.** Physicomechanical properties of AlSi10Mg.


AlSi10Mg bal 11.7 0.39 0.15 0.05 0.45 0.05 0.10 0.05 0.05 0.15

#### *5.1. Numerical Simulation 5.1. Numerical Simulation*

In order to compare with the experiment and simulate the quasi-static compression process in the actual experiment, this paper designed the BCCZ unit cell simulation model before and after optimization, as shown in Figure 9. The pressing plate was set at both ends of the BCCZ unit cell to simulate the pressure head in the experiment, and the ANSYS Workbench was used for simulation analysis. In order to compare with the experiment and simulate the quasi‐static compression process in the actual experiment, this paper designed the BCCZ unit cell simulation model before and after optimization, as shown in Figure 9. The pressing plate was set at both ends of the BCCZ unit cell to simulate the pressure head in the experiment, and the AN‐ SYS Workbench was used for simulation analysis.

**Figure 9.** Simulation model of BCCZ unit cell. **Figure 9.** Simulation model of BCCZ unit cell.

According to the experimental conditions of quasi‐static compression, the BCCZ unit cell and the compression platform were in static friction contact during compression, and the friction coefficient between metals was 0.15. The upper platen applied a one‐way ver‐ tical displacement load of 1.5 mm, the lower platen was set as a fixed constraint, and large According to the experimental conditions of quasi-static compression, the BCCZ unit cell and the compression platform were in static friction contact during compression, and the friction coefficient between metals was 0.15. The upper platen applied a one-way vertical displacement load of 1.5 mm, the lower platen was set as a fixed constraint, and

deformation was opened during simulation. After the use of the ANSYS intelligent grid

large deformation was opened during simulation. After the use of the ANSYS intelligent grid division, through comparison, it was found that further increasing the number of grids had little impact on the simulation results. This showed that the grid was independent at this time, so this paper used the intelligent grid generation function of ANSYS for simulation analysis. The results of the simulation analysis are shown in Table 5. **Table 5.** Simulation analysis results of BCCZ unit cell before and after optimization. **Strength Limit (MPa)** BCCZ Initial After optimization Optimize efficiency

lation analysis. The results of the simulation analysis are shown in Table 5.

division, through comparison, it was found that further increasing the number of grids had little impact on the simulation results. This showed that the grid was independent at this time, so this paper used the intelligent grid generation function of ANSYS for simu‐

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**Table 5.** Simulation analysis results of BCCZ unit cell before and after optimization. 668.72 794.22 18.77%


#### *5.2. Sample Preparation* Ltd. (Tianjin, China) was selected as the experimental equipment for manufacturing ex‐

The LiM-X260A metal 3D printer produced by Tianjin LiM Laser Technology Co., Ltd. (Tianjin, China) was selected as the experimental equipment for manufacturing experimental samples, and the equipment is shown in Figure 10. The equipment has the advantages of high precision, high forming efficiency, high automation, high reliability, high efficiency and stability. Table 6 shows the process manufacturing parameters of manufacturing samples. During manufacturing, the outer pillars of the samples were placed vertically with the printing plane, as shown in Figure 11. perimental samples, and the equipment is shown in Figure 10. The equipment has the advantages of high precision, high forming efficiency, high automation, high reliability, high efficiency and stability. Table 6 shows the process manufacturing parameters of man‐ ufacturing samples. During manufacturing, the outer pillars of the samples were placed vertically with the printing plane, as shown in Figure 11.

**Figure 10.** LiM‐X260A metal 3D printer produced by Tianjin LiM Laser Technology Co., Ltd. **Figure 10.** LiM-X260A metal 3D printer produced by Tianjin LiM Laser Technology Co., Ltd.

**Table 6.** Process parameters for sample manufacturing.


Laser wavelength 1060~1080 nm Spot diameter 85 μm

Oxygen content ≤1000 ppm

*Crystals* **2022**, *12*, x FOR PEER REVIEW 14 of 19

**Figure 11.** Schematic diagram of sample placement during AM. Left: before optimization, Right: after optimization. **Figure 11.** Schematic diagram of sample placement during AM. Left: before optimization, Right: after optimization. We printed three experimental samples for each digital model, and the BCCZ unit

We printed three experimental samples for each digital model, and the BCCZ unit cell structure physical diagram manufactured by the LPBF process is shown in Figure 12. The overall printing of the sample was complete, and there was no incomplete phenome‐ non such as bar fracture. According to the measurement, all dimensions were consistent with the theoretical dimensions. We printed three experimental samples for each digital model, and the BCCZ unit cell structure physical diagram manufactured by the LPBF process is shown in Figure 12. The overall printing of the sample was complete, and there was no incomplete phenomenon such as bar fracture. According to the measurement, all dimensions were consistent with the theoretical dimensions. cell structure physical diagram manufactured by the LPBF process is shown in Figure 12. The overall printing of the sample was complete, and there was no incomplete phenome‐ non such as bar fracture. According to the measurement, all dimensions were consistent with the theoretical dimensions.

For the experimental samples manufactured by LPBF technology, the WDW‐20 elec‐ tronic universal testing machine was selected for a quasi‐static compression test to quan‐ **Figure 12.** Printed sample. **Figure 12.** Printed sample.

#### tify the compressive strength of the BCCZ unit cells [48]. During the compression test, we *5.3. Experimental Process and Results*

set the loading speed of the indenter to 1 mm/min to simulate the quasi‐static conditions. In the software, we set the force sensor to detect that the force reached 0.001 KN and rec‐ orded the deformation data. During the test, we observed the load displacement curve and recorded the test process with a camera. When the sample was about to be compacted, we stopped the machine and saved the experimental data. Figure 13 shows the experi‐ mental process of the compression experiment. *5.3. Experimental Process and Results* For the experimental samples manufactured by LPBF technology, the WDW‐20 elec‐ tronic universal testing machine was selected for a quasi‐static compression test to quan‐ tify the compressive strength of the BCCZ unit cells [48]. During the compression test, we set the loading speed of the indenter to 1 mm/min to simulate the quasi‐static conditions. In the software, we set the force sensor to detect that the force reached 0.001 KN and rec‐ orded the deformation data. During the test, we observed the load displacement curve For the experimental samples manufactured by LPBF technology, the WDW-20 electronic universal testing machine was selected for a quasi-static compression test to quantify the compressive strength of the BCCZ unit cells [48]. During the compression test, we set the loading speed of the indenter to 1 mm/min to simulate the quasi-static conditions. In the software, we set the force sensor to detect that the force reached 0.001 KN and recorded the deformation data. During the test, we observed the load displacement curve and recorded the test process with a camera. When the sample was about to be compacted, we stopped the machine and saved the experimental data. Figure 13 shows the experimental process of the compression experiment.

and recorded the test process with a camera. When the sample was about to be compacted, we stopped the machine and saved the experimental data. Figure 13 shows the experi‐

mental process of the compression experiment.

**Figure 13.** Experimental process of quasi‐static compression experiment. **Figure 13.**Experimental process of quasi-static compression experiment.In the compression experiment, the BCCZ unit cell was deformed due to the falling

*Crystals* **2022**, *12*, x FOR PEER REVIEW 15 of 19

In the compression experiment, the BCCZ unit cell was deformed due to the falling of the pressing plate, and these results were obtained through the sensor. At the same time, the load at each moment could be captured through the force sensor, so that multiple groups of corresponding experimental data could be obtained. All the compression ex‐ periments were completed, and the load displacement curve was drawn after sorting out several groups of experimental data. In this paper, the contact area between the compres‐ sion platform and the sample was read through the theoretical model. After processing, the stress–strain curve of the sample before and after optimization was obtained. For the same type of BCCZ unit cell model, three repeated tests were carried out, and it was found that the curve change trend of the three experiments was basically consistent. Figure 14 shows the stress–‐strain response of the BCCZ unit cell under compression before and In the compression experiment, the BCCZ unit cell was deformed due to the falling of the pressing plate, and these results were obtained through the sensor. At the same time, the load at each moment could be captured through the force sensor, so that multiple groups of corresponding experimental data could be obtained. All the compression experiments were completed, and the load displacement curve was drawn after sorting out several groups of experimental data. In this paper, the contact area between the compression platform and the sample was read through the theoretical model. After processing, the stress–strain curve of the sample before and after optimization was obtained. For the same type of BCCZ unit cell model, three repeated tests were carried out, and it was found that the curve change trend of the three experiments was basically consistent. Figure 14 shows the stress—strain response of the BCCZ unit cell under compression before and after optimization. of the pressing plate, and these results were obtained through the sensor. At the same time, the load at each moment could be captured through the force sensor, so that multiple groups of corresponding experimental data could be obtained. All the compression ex‐ periments were completed, and the load displacement curve was drawn after sorting out several groups of experimental data. In this paper, the contact area between the compres‐ sion platform and the sample was read through the theoretical model. After processing, the stress–strain curve of the sample before and after optimization was obtained. For the same type of BCCZ unit cell model, three repeated tests were carried out, and it was found that the curve change trend of the three experiments was basically consistent. Figure 14 shows the stress–‐strain response of the BCCZ unit cell under compression before and after optimization.

**Figure 14.** Stress–strain curves of BCCZ unit cell before and after optimization obtained through quasi-static compression experiments. Black: before optimization, it corresponds to Figure 8 (**left**); Red: after optimization, it corresponds to Figure 8 (**right**).

The following conclusions can be drawn by observing the stress–strain curve shown in Figure 14:


**Table 7.** Comparison of strength and mass of BCCZ cells before and after optimization after three quasi-static compression tests.


## **6. Conclusions**

In order to solve the problem of uniform pillar thickness and uneven stress distribution in the BCCZ lattice structure, so as to better play the performance advantages of the BCCZ lattice structure in light weight and high strength, and improve the utilization rate of materials. This paper proposes an optimization method of BCCZ lattice structure based on parametric modeling parameters. The main work of this paper is as follows.


and quasi-static compression experiments are used to compare the BCCZ unit cell before and after optimization. The comparison results show that the strength limit of the BCCZ unit cell after optimization is increased by 18.77% and 18.43%, respectively, indicating that the optimization results have strong consistency.

The advantage of the optimization method in this paper is that the stress can be selected according to the setting, and the results of the section radius of each pillar of BCCZ lattice structure with the minimum mass meeting the strength requirements can be output. In the test case in this paper, the objective of simulation is compressive strength. Under other load conditions, the optimization method in this paper also has reference value. Besides the BCCZ lattice structure, this optimization method can also be used for reference for other node structure lattice structures. In addition, the experimental results of this optimization method also prove the advantages of non-uniform design, and non-uniform lattice structures can have higher strength than uniform lattice structures. These two kinds of situations will be considered in our next work.

**Author Contributions:** Conceptualization, H.L. and W.Y.; methodology, H.L.; validation, H.L. and Z.Q.; formal analysis, Q.M. and H.L.; investigation, H.L. and Z.Q.; resources, W.Y.; writing—original draft preparation, H.L. and Q.M.; writing—review and editing, W.Y. and L.Y.; supervision, W.Y.; funding acquisition, W.Y. All authors have read and agreed to the published version of the manuscript.

**Funding:** The authors are thankful for the support from the National Natural Science Foundation of China, under the Grant No. 52175313, and Key Science and Technology Project of Hebei Province, China, under the Grant No. 21284901Z.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** These experiments were completed in the Advanced Materials Testing and Analysis Center of HEBUT. At the same time, thanks to the scientific research platform provided by the National Engineering Research Center for Technical Innovation Method and Tool. The authors thank them for their help.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Communication* **Effects of SiC Content on Wear Resistance of Al-Zn-Mg-Cu Matrix Composites Fabricated via Laser Powder Bed Fusion**

**Zhigang Shen <sup>1</sup> , Ning Li 2,3,\*, Ting Wang 2,3 and Zhisheng Wu <sup>1</sup>**


**Abstract:** In this paper, in situ SiC-reinforced Al-Zn-Mg-Cu composites were fabricated by laser powder bed fusion (LPBF). The effects of SiC content on the microstructure, phase composition, microhardness, and wear resistance of as-printed composites were preliminarily investigated. Results show that the microstructure was regulated, the matrix grains were refined, and the tendency to orientation grain growth was suppressed. SiC particles reacted in situ with the Al matrix to produce Si, Al4C<sup>3</sup> , and Al4SiC<sup>4</sup> phases. The microhardness and wear resistance of as-printed composites increased with SiC content due to the fine grain strengthening of the matrix and the second phase strengthening of precipitates and reinforcements.

**Keywords:** laser powder bed fusion; aluminum matrix composites; microstructure evolution; microhardness; wear resistance

## **1. Introduction**

Aluminum matrix composites (AMCs) have attracted much attention because of their higher specific strength, specific stiffness, and wear resistance compared with aluminum alloys [1,2]. Silicon carbide (SiC) particles are used as reinforcement for AMCs due to their high hardness, wear resistance, and good metallurgical compatibility with aluminum alloy [3,4]. High-strength Al-Zn-Mg-Cu alloy is a pivotal raw material for structural parts, but its high cracking susceptibility during crystallization limits its application [5,6]. SiC-reinforced aluminum matrix composites are the most popular and representative of this system [7]. The mature methods for preparing AMCs include melt stirring, squeeze casting, pressurized infiltration, and vacuum infiltration [8]. However, the mechanical properties of AMCs are often affected by the segregation and settling of SiC particles and weak interfacial bonding between SiC particles and the matrix [9]. Many scholars have proposed improved methods to prepare AMCs with higher performance [10]. Laser powder bed fusion (LPBF) is an innovative strategy for fabricating AMCs due to the advantages of high precision, adjustable raw powder compositions, and direct formability of components [11,12]. Gu et al. [13,14] have prepared AlSi10Mg alloy, AlN/AlSi10Mg composites, and SiC/AlSi10Mg composites by LPBF. Results show that AlSi10Mg alloy has good printability, and the mechanical properties of as-printed composites can be optimized by ceramic reinforcements. However, the low-strength Al-Si alloys could not meet the actual performance requirements. The high-strength Al-Zn-Mg-Cu alloys are a better matrix for the aluminum matrix composites. In this study, SiC-reinforced Al-Zn-Mg-Cu composites were fabricated via LPBF. The effects of SiC content on the microstructure, microhardness, and wear resistance of as-printed composites were investigated. This study made a preliminary attempt to prepare wear-resistant Al-Zn-Mg-Cu composites by LPBF.

**Citation:** Shen, Z.; Li, N.; Wang, T.; Wu, Z. Effects of SiC Content on Wear Resistance of Al-Zn-Mg-Cu Matrix Composites Fabricated via Laser Powder Bed Fusion. *Crystals* **2022**, *12*, 1801. https://doi.org/10.3390/ cryst12121801

Academic Editors: Hao Yi, Huajun Cao, Menglin Liu and Le Jia

Received: 23 November 2022 Accepted: 8 December 2022 Published: 10 December 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

## **2. Materials and Methods**

Commercial Al-Zn-Mg-Cu alloy powders (D<sup>50</sup> = 38 µm) with a composition of Al-5.64Zn-2.31Mg-1.40Cu-0.32Fe-0.22Cr-0.08Mn-0.05Si (wt.%) and SiC ceramic powders (D<sup>50</sup> = 10 µm) were used as raw materials. The morphologies and particle size histograms are shown in Figure 1a,b, respectively. The homogeneous composite powders with different SiC fractions (0 wt.%~4 wt.%) were prepared by a planetary shaker-mixer, and the mixing time was two hours. The morphology of 4 wt.% SiC/Al-Zn-Mg-Cu composite powder is shown in Figure 1c. The sphericity of Al-Zn-Mg-Cu alloy powders was not damaged, and SiC particles were uniformly dispersed in Al-Zn-Mg-Cu powders. Table 1 lists the sample labels of the as-printed composites and the corresponding composite powder compositions. Samples for metallographic and performance characterization were printed directly on EOS M290 (Germany, EOS). The schematic of sample orientation is illustrated in Figure 1d. The optimized LPBF parameters for obtaining the high-density as-printed composites are as follows: laser power 340 W, laser scanning speed 800 mm/s, layer thickness 30 µm, and hatch distance 100 µm. The strip-scanning method was adopted with a strip width of 8 mm and a rotation angle of 67◦ . The schematic of the laser scanning strategy is demonstrated in Figure 1e. Metallographic samples were sanded and mechanically polished layer by layer and then etched with Keller's reagent before being observed. Scanning electron microscopy (SEM, Zeiss) was conducted to scrutinize the microstructure, and the accompanying electron backscattering diffraction (EBSD, EDAX) was employed to analyze the crystallographic features. Samples for EBSD need to be electropolished with a 10% perchloric acid alcohol solution. X-ray diffraction (XRD, DX-2700) was used to analyze the phase composition. Under the loading time of 10 s and loading amount of 100 g, the microhardness of metallographic specimens was measured by Vickers (HV-1000). Wear resistance was investigated on the friction and wear tester (HF-1000), and the schematic is presented in Figure 1f. Before the test, the samples were processed into circular samples with a diameter of 10 mm, polished with 2000 # sandpaper, and cleaned with alcohol. The parameters used are 500 g (load), 560 r/min (rotational speed), and 5 mm (friction diameter). Silicon nitride balls with a diameter of 6 mm and a hardness of 20 GPa were used as the anti-abrasive material. Three groups of tests were conducted to ensure accuracy. The mass before and after testing was measured to obtain the loss of abrasive debris and used to characterize wear resistance. *Crystals* **2022**, *12*, x FOR PEER REVIEW 3 of 8

**Figure 1.** Surface morphologies of (**a**) Al-Zn-Mg-Cu alloy powders, (**b**) SiC powders, and (**c**) 4 wt.% SiC/Al-Zn-Mg-Cu composite powders with insert showing the particle size distribution histogram. Schematics of (**d**) sample orientation, (**e**) laser scanning strategy, and (**f**) friction and wear test. **Figure 1.** Surface morphologies of (**a**) Al-Zn-Mg-Cu alloy powders, (**b**) SiC powders, and (**c**) 4 wt.% SiC/Al-Zn-Mg-Cu composite powders with insert showing the particle size distribution histogram. Schematics of (**d**) sample orientation, (**e**) laser scanning strategy, and (**f**) friction and wear test.

**Sample Label Powder Composition** 

Figure 2 shows the SEM images of as-printed samples with different SiC contents. Fusion lines, cracks, pores, and grain boundaries were scrutinized in the as-printed Al-Zn-Mg-Cu alloy (Figure 2a). These cracks were typical solidification cracks that cracked along the grain boundaries [15]. From the insert (Figure 2b), no precipitates were found at the grain boundaries, and poor intergranular bonding was revealed. Figure 2c presents the microstructure of the S2 sample, where the number of cracks was significantly reduced. A small number of intergranular precipitates were found at the grain boundaries. When the SiC content was 4 wt.%, no cracks were observed within the as-printed composites, as shown in Figure 2d. The irregular SiC reinforcements were uniformly embedded in the matrix without evident agglomeration. Figure 2f shows the XRD diffraction patterns of as-printed samples with different SiC contents. Without SiC reinforcement modification, only the Al phase was detected in the as-printed S0 sample. The as-printed SiC-reinforced Al-Zn-Mg-Cu composites consisted of the Al, SiC, Mg2Si, Al4C3, Al4SiC4, and Si phases. During the LPBF process, SiC particles reacted in situ with the Al matrix as follows

S1 Al-Zn-Mg-Cu alloy + 1 wt.% SiC reinforcement S2 Al-Zn-Mg-Cu alloy + 2 wt.% SiC reinforcement S3 Al-Zn-Mg-Cu alloy + 3 wt.% SiC reinforcement S4 Al-Zn-Mg-Cu alloy + 4 wt.% SiC reinforcement

4Al + 4SiC = 3Si + Al4SiC4 (1)

4Al + 3SiC = 3Si + Al4C3 (2)

**Table 1.** Sample labels of as-printed Al-Zn-Mg-Cu alloy and SiC/Al-Zn-Mg-Cu composites.

**3. Results and Discussion** 

[16,17].

*3.1. Morphologies and Microstructure* 


**Table 1.** Sample labels of as-printed Al-Zn-Mg-Cu alloy and SiC/Al-Zn-Mg-Cu composites.

### **3. Results and Discussion**

#### *3.1. Morphologies and Microstructure*

Figure 2 shows the SEM images of as-printed samples with different SiC contents. Fusion lines, cracks, pores, and grain boundaries were scrutinized in the as-printed Al-Zn-Mg-Cu alloy (Figure 2a). These cracks were typical solidification cracks that cracked along the grain boundaries [15]. From the insert (Figure 2b), no precipitates were found at the grain boundaries, and poor intergranular bonding was revealed. Figure 2c presents the microstructure of the S2 sample, where the number of cracks was significantly reduced. A small number of intergranular precipitates were found at the grain boundaries. When the SiC content was 4 wt.%, no cracks were observed within the as-printed composites, as shown in Figure 2d. The irregular SiC reinforcements were uniformly embedded in the matrix without evident agglomeration. Figure 2f shows the XRD diffraction patterns of as-printed samples with different SiC contents. Without SiC reinforcement modification, only the Al phase was detected in the as-printed S0 sample. The as-printed SiC-reinforced Al-Zn-Mg-Cu composites consisted of the Al, SiC, Mg2Si, Al4C3, Al4SiC4, and Si phases. During the LPBF process, SiC particles reacted in situ with the Al matrix as follows [16,17].

$$4\text{Al} + 4\text{SiC} = 3\text{Si} + \text{Al}\_4\text{SiC}\_4 \tag{1}$$

$$\text{4Al} + \text{3SiC} = \text{3Si} + \text{Al}\_4\text{C}\_3 \tag{2}$$

Al4C3, Al4SiC4, and Si phases were generated in the molten pool, and some of the generated Si reacted with Mg to form the Mg2Si phase. Short rod-like Al4SiC<sup>4</sup> and granular Si-eutectic phases were observed to fill the grain boundaries, as shown in Figure 2e.

Figure 3 illustrates the grain maps, grain size distribution histograms, and pole figures (PFs) of the as-printed S0 and S4 samples, revealing the effects of SiC reinforcement on the matrix grains. The unidentified black regions in Figure 3a,d are cracks and SiC reinforcement, respectively. The coarse columnar crystals (Figure 3a) were refined into fine columnar and equiaxed crystals (Figure 3d) with SiC particles. The size distribution of matrix grains followed unimodal distribution, and the average size was refined from 37.15 µm (S0 sample) to 20.50 µm (S4 sample). Figure 3c,f compare the effect of SiC reinforcement on crystallization textures of the as-printed materials, where A1 is the building direction (BD). The fiber texture of the S0 sample along the [001] crystal orientation parallel to the BD was observed in Figure 3c, predicting the preferential growth of Al grains in the as-printed Al-Zn-Mg-Cu alloy. The maximum value of multiple uniform densities (MUD) was 5.427, which appeared in the (100) crystal plane of the [001] pole figure. The matrix texture was weakened by incorporating SiC particles. For the as-printed S4 sample, the maximum value of MUD was 4.646. For the unmodified Al-Zn-Mg-Cu alloy, the grains were nucleated by attaching to the anterior molten pool and solidified in the building direction. The heterogeneous nucleation effect was noticeable when SiC ceramic particles were introduced.

Al4C3, Al4SiC4, and Si phases were generated in the molten pool, and some of the generated Si reacted with Mg to form the Mg2Si phase. Short rod-like Al4SiC4 and granular Si-eutectic phases were observed to fill the grain boundaries, as shown in Figure 2e.

**Figure 2.** SEM images of the as-printed (**a**,**b**) S0 sample, (**c**) S2 sample, and (**d**,**e**) S4 sample. (**f**) XRD diffraction patterns of the as-printed samples. **Figure 2.** SEM images of the as-printed (**a**,**b**) S0 sample, (**c**) S2 sample, and (**d**,**e**) S4 sample. (**f**) XRD diffraction patterns of the as-printed samples. direction. The heterogeneous nucleation effect was noticeable when SiC ceramic particles were introduced.

**Figure 3.** Grain maps, grain size distribution histograms, and PFs along the lateral section of the asprinted (**a**–**c**) S0 and (**d**–**f**) S4 samples. **Figure 3.** Grain maps, grain size distribution histograms, and PFs along the lateral section of the as-printed (**a**–**c**) S0 and (**d**–**f**) S4 samples.

Figure 4 indicates the microhardness of as-printed samples in the lateral and top sections, revealing the effect of SiC particles on the microhardness. The microhardness of the

forcement. The microhardness of the S4 sample was 156.8 ± 6.4 HV0.1 and 161.4 ± 10.5 HV0.1, respectively. Fine grain strengthening of the matrix and particle strengthening of the reinforcement and precipitates were the main reasons for the increased microhardness. The heterogeneity of microhardness was observed along the lateral and top sections, and the top section was higher than the side section. This phenomenon was related to the directional growth of the matrix grains and gradually decreased with increasing SiC content. For the as-printed S0 sample, the lateral section was composed of coarse columnar crystals, and the top section was the fine equiaxed crystal. Fine grain strengthening could be responsible for the difference in microhardness. With the introduction of SiC reinforcement, the columnar grain on the side was gradually refined, and the difference in micro-

hardness was gradually reduced.

*3.2. Microhardness* 

#### *3.2. Microhardness*

Figure 4 indicates the microhardness of as-printed samples in the lateral and top sections, revealing the effect of SiC particles on the microhardness. The microhardness of the unmodified S0 sample in the side and top sections was 93 ± 5 HV0.1 and 102 ± 10 HV0.1, respectively. The microhardness gradually increased with the incorporation of SiC reinforcement. The microhardness of the S4 sample was 156.8 ± 6.4 HV0.1 and 161.4 ± 10.5 HV0.1, respectively. Fine grain strengthening of the matrix and particle strengthening of the reinforcement and precipitates were the main reasons for the increased microhardness. The heterogeneity of microhardness was observed along the lateral and top sections, and the top section was higher than the side section. This phenomenon was related to the directional growth of the matrix grains and gradually decreased with increasing SiC content. For the asprinted S0 sample, the lateral section was composed of coarse columnar crystals, and the top section was the fine equiaxed crystal. Fine grain strengthening could be responsible for the difference in microhardness. With the introduction of SiC reinforcement, the columnar grain on the side was gradually refined, and the difference in microhardness was gradually reduced. *Crystals* **2022**, *12*, x FOR PEER REVIEW 6 of 8

**Figure 4.** Microhardness histograms of as-printed S0-S4 samples in the lateral and top sections. **Figure 4.** Microhardness histograms of as-printed S0-S4 samples in the lateral and top sections.

#### *3.3. Wear Behavior 3.3. Wear Behavior*

The effect of SiC reinforcement on the wear resistance of as-printed AMCs was investigated, and the results are shown in Figure 5. The coefficient of friction (COF) curves are shown in Figure 5a. COF curves showed a similar evolution, characterized by dramatic fluctuations and gradually decreasing with time. Fluctuations might be due to cracks and SiC reinforcement, which could lead to the stripping of the matrix and reinforcement from the sample during friction. The COF curves tended to be stable as the debris with poor binding to the matrix gradually fell off. The average COF values of S0 to S4 samples were 0.507, 0.473, 0.389, 0.348, and 0.288, respectively. The weight loss of the as-printed materials is shown in Figure 5b. The average weight loss for the as-printed S0 to S4 samples were 14.3 ± 1.7 mg, 13.8 ± 1.8 mg, 12.7 ± 2 mg, 9.9 ± 1.2 mg, and 7.6 ± 0.9 mg, respectively. Combining the results of COF and weight loss, the wear resistance of as-printed composites was reinforced with the incorporation of SiC reinforcement. The increase in wear resistance of as-printed composites was mainly due to the synergistic effect of matrix and reinforcement. The hardened SiC ceramic particles could resist the abrasive pressing and improve the deformation resistance of the as-printed composites. The strength of the ma-The effect of SiC reinforcement on the wear resistance of as-printed AMCs was investigated, and the results are shown in Figure 5. The coefficient of friction (COF) curves are shown in Figure 5a. COF curves showed a similar evolution, characterized by dramatic fluctuations and gradually decreasing with time. Fluctuations might be due to cracks and SiC reinforcement, which could lead to the stripping of the matrix and reinforcement from the sample during friction. The COF curves tended to be stable as the debris with poor binding to the matrix gradually fell off. The average COF values of S0 to S4 samples were 0.507, 0.473, 0.389, 0.348, and 0.288, respectively. The weight loss of the as-printed materials is shown in Figure 5b. The average weight loss for the as-printed S0 to S4 samples were 14.3 ± 1.7 mg, 13.8 ± 1.8 mg, 12.7 ± 2 mg, 9.9 ± 1.2 mg, and 7.6 ± 0.9 mg, respectively. Combining the results of COF and weight loss, the wear resistance of as-printed composites was reinforced with the incorporation of SiC reinforcement. The increase in wear resistance of as-printed composites was mainly due to the synergistic effect of matrix and reinforcement. The hardened SiC ceramic particles could resist the abrasive pressing and improve the deformation resistance of the as-printed composites. The strength of the matrix was increased due to crack inhibition and grain refinement.

**Figure 5.** Results of friction and wear. (**a**) The variation curves of friction coefficient vs. sliding time

and (**b**) the weight loss of the as-printed S0–S4 samples.

trix was increased due to crack inhibition and grain refinement.

trix was increased due to crack inhibition and grain refinement.

**Figure 5.** Results of friction and wear. (**a**) The variation curves of friction coefficient vs. sliding time and (**b**) the weight loss of the as-printed S0–S4 samples. **Figure 5.** Results of friction and wear. (**a**) The variation curves of friction coefficient vs. sliding time and (**b**) the weight loss of the as-printed S0–S4 samples.

**Figure 4.** Microhardness histograms of as-printed S0-S4 samples in the lateral and top sections.

The effect of SiC reinforcement on the wear resistance of as-printed AMCs was investigated, and the results are shown in Figure 5. The coefficient of friction (COF) curves are shown in Figure 5a. COF curves showed a similar evolution, characterized by dramatic fluctuations and gradually decreasing with time. Fluctuations might be due to cracks and SiC reinforcement, which could lead to the stripping of the matrix and reinforcement from the sample during friction. The COF curves tended to be stable as the debris with poor binding to the matrix gradually fell off. The average COF values of S0 to S4 samples were 0.507, 0.473, 0.389, 0.348, and 0.288, respectively. The weight loss of the as-printed materials is shown in Figure 5b. The average weight loss for the as-printed S0 to S4 samples were 14.3 ± 1.7 mg, 13.8 ± 1.8 mg, 12.7 ± 2 mg, 9.9 ± 1.2 mg, and 7.6 ± 0.9 mg, respectively. Combining the results of COF and weight loss, the wear resistance of as-printed composites was reinforced with the incorporation of SiC reinforcement. The increase in wear resistance of as-printed composites was mainly due to the synergistic effect of matrix and reinforcement. The hardened SiC ceramic particles could resist the abrasive pressing and improve the deformation resistance of the as-printed composites. The strength of the ma-

## **4. Conclusions**

*3.3. Wear Behavior* 

In this paper, the in situ SiC-reinforced Al-Zn-Mg-Cu composites were prepared by LPBF. The microhardness and wear resistance were reinforced while suppressing the hot cracks. SiC particles reacted in situ with the Al matrix to form Al4SiC4, Al4C3, and Si phases in the molten pool, which precipitated near the grain boundary during solidification. Crack suppression was mainly due to grain refinement, disordered grain growth, and grain boundary structure optimization. The fine grain strengthening of the Al matrix and the second phase strengthening of precipitates and reinforcement were the main reasons for the increase in microhardness and wear resistance.

**Author Contributions:** Investigation, data curation, Z.S.; investigation, data curation, and writing original draft preparation, N.L.; supervision, T.W.; equipment management, Z.W. All authors have read and agreed to the published version of the manuscript.

**Funding:** Please add: This research was funded by the Shandong Provincial Key Research and Development Program, grant number 2019JZZY010439 and the National Natural Science Foundation of China, grant number 52175308.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**


## *Article* **Effect of Slag Adjustment on Inclusions and Mechanical Properties of Si-Killed 55SiCr Spring Steel**

**Yang Li, Changyong Chen \* , Hao Hu, Hao Yang, Meng Sun and Zhouhua Jiang \***

Department of Special Steel Metallurgy, School of Metallurgy, Northeastern University, Shenyang 110819, China **\*** Correspondence: 1610456@stu.neu.edu.cn (C.C.); jiangzh@smm.neu.edu.cn (Z.J.); Tel.: +024-8367-8691 (C.C.); +024-8368-6453 (Z.J.)

**Abstract:** The effects of the Al2O<sup>3</sup> content and basicity of CaO–SiO2–Al2O3–10 wt.% MgO refining slag on inclusions removal in 55SiCr spring steel were investigated. The viscosity of slag was studied using a viscometer, while the microstructure investigation involved using a water-quenching furnace and a Fourier-transform infrared spectrometer. The influence mechanism of the slag adjustment on inclusions was explored through thermodynamic calculations and kinetic analysis. The results indicated that the viscosity of the molten slag increased gradually with the content of Al2O<sup>3</sup> increasing due to it increasing the degree of polymerization of the slag network structure, especially the [AlO<sup>4</sup> ] 5− and [Si-O-Si] structures. In contrast, the viscosity of molten slag experienced the opposite pattern, with the basicity of molten slag increasing. This was due to the fact that Ca2+ can significantly reduce the degree of polymerization of a slag network structure, especially the percentages of the [SiO<sup>4</sup> ] <sup>4</sup>−, [AlO<sup>4</sup> ] <sup>5</sup><sup>−</sup> and [Si-O-Si] network structures. Finally, the changes in physical properties and structure of slag significantly affected the removal effect of the inclusions in molten steel. As a result, the number, size distribution, composition distribution and morphology of the inclusions displayed significant changes when the content of Al2O<sup>3</sup> increased from 3 wt.% to 12 wt.% and the basicity of the slag gradually increased from 0.5 to 1.2.

**Keywords:** 55SiCr steel; spring steel; refining slag; non-metallic inclusions; high temperature viscosity

## **1. Introduction**

High strength, fatigue resistance and impact resistance are important properties of spring steels [1,2]. Non-metallic inclusion is one of the most important factors that cause fatigue fractures in spring steel [3,4]. Inclusions with high hardness and melting points, such as alumina and spinel, often act as crack sources of fatigue failure [5–7]. The total oxygen (T.O) of steel, as well as the type, number, size, morphology and distribution of inclusions in steel, play essential roles in spring steel cleanness, and an improvement in cleanliness can effectively prolong the fatigue life of the steel [8–10].

Ladle furnace (LF) slag refining is a widely used technology to control inclusions in spring steel production [11,12]. Appropriate optimization of the refining slag composition can reduce the T.O and the number and size of inclusions in spring steel, as well as control the composition of inclusions located in the low melting area [13,14]. Zhang et al. [15] studied the low-melting-point region (at 1673 K) in a MnO−CaO−SiO2−Al2O<sup>3</sup> system with the largest area when the Al2O<sup>3</sup> content in this system was 25 wt.%. He et al. [16] showed that the inclusions are plastic at the end of the refining process, the basicity (R = wt.%CaO/wt.% SiO2) of refining slag is in the range of 1.0~1.2 and the Al2O<sup>3</sup> content of slag is in the range of 3~9 wt.%. Yang et al. [17] showed that the inclusions located in the low-melting-point region when the basicity was in the range of 1.00 to 1.19 had a C/A value (wt.% CaO/wt.% Al2O3) above 9 at 1673 K. Similar results were mentioned in other studies [18–20].

Wu et al. [21] studied the effect of refining slag with low basicity on the inclusions in 55SiCr suspension spring steel. The results indicate that the composition of

**Citation:** Li, Y.; Chen, C.; Hu, H.; Yang, H.; Sun, M.; Jiang, Z. Effect of Slag Adjustment on Inclusions and Mechanical Properties of Si-Killed 55SiCr Spring Steel. *Crystals* **2022**, *12*, 1721. https://doi.org/10.3390/ cryst12121721

Academic Editors: Hao Yi, Huajun Cao, Menglin Liu and Le Jia

Received: 5 November 2022 Accepted: 23 November 2022 Published: 27 November 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

the CaO–SiO2–Al2O<sup>3</sup> ternary system inclusions is located at the center of the low-meltingpoint zone, and the plastic deformation ability of the inclusions is good. Nevertheless, the authors did not study the influence of viscosity and structure of refining slag on removing non-metallic inclusions in spring steel.

Du et al. [22] studied the influence of refining slag with high basicity on inclusions in 55SiCr suspension spring steel. The results showed that the number of inclusions decreased sharply as the basicity of the slag gradually increased, and the diameter of most of the inclusions was less than 10 µm. Similarly, the authors did not study the influence of the alkalinity of refining slag on its viscosity and structure.

Non-metallic inclusions have significant effects on many mechanical properties of suspension spring steel, including the strength, plasticity, toughness and fatigue properties. Li et al. [23] studied the effect of inclusions on the tensile fracture properties of 55CrSi spring steel. The results demonstrated that interior inclusions have a significant effect on the ductility and a minimal effect on the tensile strength of spring steel. However, the authors only selected the samples obtained under a single smelting condition as the research object, and the change rules of mechanical properties of spring steel treated with refining slag with different compositions have not been studied.

As for the influence of basicity and Al2O<sup>3</sup> content on the inclusions in spring steel, most researchers only made a one-sided analysis from the perspective of thermodynamics. Few researchers elaborated on the influence of basicity and Al2O<sup>3</sup> content on inclusions in steel from the perspective of dynamics according to their influence on the physical properties and structure of slag. Therefore, in this study, the effects of basicity and Al2O<sup>3</sup> content on the viscosity and structure of slag were studied in detail, and their effects on the removal of inclusions in steel were explored. In addition, the effects of inclusions on the mechanical properties of spring steel are discussed.

#### **2. Materials and Methods**

#### *2.1. Materials*

The effect of the Al2O<sup>3</sup> content and basicity in refining slag on the inclusions in spring steel was investigated in a MoSi<sup>2</sup> high-temperature resistance furnace. Table 1 shows the main chemical composition of the 55SiCr spring steel.



### *2.2. Experimental Equipment and Procedure*

Seven sample types were created by treating different synthetic LF refining slags with four different Al2O<sup>3</sup> contents of 3.0 wt.%, 5.0 wt.%, 8.0 wt.% and 12.0 wt.% and four basicities of 0.5, 0.8, 1.0 and 1.2, as shown in Table 2.


**Table 2.** Chemical compositions of the low-basicity refining slag (wt.%).

Note: R = CaO/SiO2.

Experiments were carried out in a MoSi<sup>2</sup> high-temperature resistance furnace. An argon atmosphere was kept in the experiments all the time, blowing from the bottom of the furnace tube to the top. The experimental procedures were carried out as follows. First, a 1.00 kg steel rod was placed into a MgO crucible with a 60 <sup>×</sup> <sup>10</sup>−<sup>3</sup> m inner diameter and an <sup>80</sup> <sup>×</sup> <sup>10</sup>−<sup>3</sup> m depth. Then, the crucible was placed in a graphite crucible to prevent liquid metal from leaking. After the whole crucible was placed in the chamber, the power was switched on and the furnace was heated to the experimental temperature of 1873 K. Alloys were added into the molten steel when the temperature reached 1873 K, and the molten steel was deoxidized using Si. After that, 0.05 kg of synthetic LF refining slag powder was put into the surface of the molten steel. The refining time was constant at 45 min for all of the experiments.

A direct reading spectrometer was utilized to detect the compositions of Si, Mn, Cr, V, Mo, Ni, Al, P and S. For C and S, an infrared C/S analyzer was applied. Furthermore, a LECO® TC 500 O2/N<sup>2</sup> analyzer was selected to detect O and N. The ASPEX (FEI Company, Hillsboro, USA) was used to indicate the number, size and compositional distribution of the inclusions. Finally, SEM-EDS was selected to analyze the morphology of the inclusions.

The sample treatment method for inclusion observation and mechanical properties is shown in Figure 1. A cylindrical ingot was cut into two semi-cylinders along the diameter. One was forged and a heat treatment was conducted for a tensile test, and the other was used to acquire samples for inclusion observation. The forging process started at 1200 °C after heat preservation for 2 h, and was finally air-cooled to room temperature The crosssection of the forging cylinder had an 18 mm diameter. Forged steel was austenized at 880 °C for 30 min and oil-quenched to room temperature, followed by tempering at 450 °C for 120 min. The atmosphere of the heat treatment process was air. For the mechanical property characterization, tensile tests were conducted on a Shimadzu AGS-X100KN (Shimadzu, Kyodo, Japan) electronic tensile testing machine following standard GB/T 228.1-2010 (ISO 6892-1:2009, MOD) [24].

ing.

#### *2.3. Equipment and Specific Experimental Steps for the Viscosity Measurements of Refining Slag*

*2.3. Equipment and Specific Experimental Steps for the Viscosity Measurements of Refining Slag* In this study, a Brookfield DVT rotary viscometer was selected to measure the viscosity of the slag. A schematic diagram of the equipment is shown in Figure 2. The error range of the viscosity measurement was ±1%, and the reproducibility of the experimental data was ±0.2%. The crucible material used in the experiment was molybdenum, and the size of the crucible was Φ 31 mm × 61 mm. The material of the adopted rotor was molybdenum, and its size was Φ 17 mm × 25 mm, with an angle of 120° at the top and tail of the rotor. During the experiment, the distance between the top of the rotor and the molybdenum crucible was 3 mm. In order to ensure that the slag liquid level did not exceed In this study, a Brookfield DVT rotary viscometer was selected to measure the viscosity of the slag. A schematic diagram of the equipment is shown in Figure 2. The error range of the viscosity measurement was ±1%, and the reproducibility of the experimental data was ±0.2%. The crucible material used in the experiment was molybdenum, and the size of the crucible was Φ 31 mm × 61 mm. The material of the adopted rotor was molybdenum, and its size was Φ 17 mm × 25 mm, with an angle of 120◦ at the top and tail of the rotor. During the experiment, the distance between the top of the rotor and the molybdenum crucible was 3 mm. In order to ensure that the slag liquid level did not exceed 3~5 mm from the tail of the rotor during the experiment, 65 g of slag was weighed for each experiment.

each experiment.

3~5 mm from the tail of the rotor during the experiment, 65 g of slag was weighed for

**Figure 2.** Diagram of the high-temperature viscometer and its auxiliary device. **Figure 2.** Diagram of the high-temperature viscometer and its auxiliary device.

The detailed steps of the viscosity test were as follows: (1) Preparation of experiment: 65 g of slag was prepared and put into the molybdenum crucible after the compression. (2) Zero adjustment of the viscometer: the viscometer was left to idle for the zero calibration without hanging the rotor. (3) Power on and temperature increase: after the zero calibration, the equipment was sealed, the power was turned on, the temperature was increased and the vacuum pumping began to work. After a vacuum was achieved, the shielding Ar gas was introduced at the flow rate of 100 mL·min−1 (to prevent the rotor fluctuation caused by excessive air flow and experimental error). Cooling water was fed into the circulation when the furnace temperature reached 673 K. (4) Measuring the viscosity: the temperature was kept constant for half an hour when the temperature reached 1873 K, and then the rotor was lowered to 3 mm from the bottom of the molybdenum crucible and the slag viscosity was measured at the speed of 100 r·min−1, where viscosity data was recorded every 10 s and continued for 5 min. (5) Viscosity measurement during the cooling process: the temperature was decreased by 20 K each time after the viscosity at 1873 K was measured. The temperature was kept constant for 10 min, and then the viscosity of the slag was measured at this temperature at the speed of 100 r·min−1. (6) Finally, the temperature was increased again to 1773 K, and the rotor was lifted to stop measuring the viscosity when the torque was greater than 100%. The The detailed steps of the viscosity test were as follows: (1) Preparation of experiment: 65 g of slag was prepared and put into the molybdenum crucible after the compression. (2) Zero adjustment of the viscometer: the viscometer was left to idle for the zero calibration without hanging the rotor. (3) Power on and temperature increase: after the zero calibration, the equipment was sealed, the power was turned on, the temperature was increased and the vacuum pumping began to work. After a vacuum was achieved, the shielding Ar gas was introduced at the flow rate of 100 mL·min−<sup>1</sup> (to prevent the rotor fluctuation caused by excessive air flow and experimental error). Cooling water was fed into the circulation when the furnace temperature reached 673 K. (4) Measuring the viscosity: the temperature was kept constant for half an hour when the temperature reached 1873 K, and then the rotor was lowered to 3 mm from the bottom of the molybdenum crucible and the slag viscosity was measured at the speed of 100 r·min−<sup>1</sup> , where viscosity data was recorded every 10 s and continued for 5 min. (5) Viscosity measurement during the cooling process: the temperature was decreased by 20 K each time after the viscosity at 1873 K was measured. The temperature was kept constant for 10 min, and then the viscosity of the slag was measured at this temperature at the speed of 100 r·min−<sup>1</sup> . (6) Finally, the temperature was increased again to 1773 K, and the rotor was lifted to stop measuring the viscosity when the torque was greater than 100%. The viscometer was powered off and cooled down. The switches of the Ar gas and cooling water were closed when the furnace temperature reached 873 K and 673 K, respectively.

#### *2.4. Apparatus and Specific Experimental Steps for the Structure Measurement of Refining Slag 2.4. Apparatus and Specific Experimental Steps for the Structure Measurement of Refining Slag*

viscometer was powered off and cooled down. The switches of the Ar gas and cooling water were closed when the furnace temperature reached 873 K and 673 K, respectively.

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A schematic diagram of the water bath quenching equipment is shown in Figure 3. The graphite crucible (20 mm diameter, 40 mm height) containing the refined slag sample was hung in the furnace with platinum wire while ensuring it was located in the constant temperature zone. A basin of ice water was placed at the vertical bottom of the furnace. The power was turned on and the switches for the cooling water and argon gas were turned on at the same time. The temperature increased gradually following the program that was set in the equipment. The furnace was kept at a constant temperature for 1 hour when the temperature reached 1873 K, and then the switch for the platinum wire was released to make the graphite crucible quickly fall into the ice water at the bottom of the furnace. The slag could maintain its structure in the molten state because the liquid refining slag was rapidly cooled from 1873 K to 273 K. A schematic diagram of the water bath quenching equipment is shown in Figure 3. The graphite crucible (20 mm diameter, 40 mm height) containing the refined slag sample was hung in the furnace with platinum wire while ensuring it was located in the constant temperature zone. A basin of ice water was placed at the vertical bottom of the furnace. The power was turned on and the switches for the cooling water and argon gas were turned on at the same time. The temperature increased gradually following the program that was set in the equipment. The furnace was kept at a constant temperature for 1 hour when the temperature reached 1873 K, and then the switch for the platinum wire was released to make the graphite crucible quickly fall into the ice water at the bottom of the furnace. The slag could maintain its structure in the molten state because the liquid refining slag was rapidly cooled from 1873 K to 273 K.

**Figure 3.** Schematic diagram of the vertical resistance furnace used in the water quenching ex-**Figure 3.** Schematic diagram of the vertical resistance furnace used in the water quenching experiment.

The refining slag was dried after it was removed from ice water, and then it was ground to a particle size below 200 mesh. Finally, the structure of the refining slag was detected using Fourier-transform infrared spectrometry (FTIR).

periment.

#### **3. Results and Discussion**

*3.1. Number and Size of Inclusions*

The chemical compositions of the 55SiCr steels are shown in Table 3.


**Table 3.** Chemical compositions of the 55SiCr steels (wt.%).

The T.O and [Al]s contents increased from 0.0016 wt.% to 0.0023 wt.% and from 0.0012 wt.% to 0.0015 wt.%, respectively, as the content of Al2O<sup>3</sup> increased from 3 wt.% to 12 wt.%. In contrast, the T.O content decreased from 0.0020 wt.% to 0.0015 wt.% as the basicity increased from 0.5 to 1.2.

The number and size distribution of inclusions in the 1#~7# steel samples is shown in Table 4. Obviously, the quantity density gradually increased from 8.81 to 8.96, while the percentage of inclusions with sizes smaller than 5 µm increased from 61% to 77% with increasing Al2O3. In contrast, the quantity density gradually decreased from 8.92 to 8.54, while the percentage of inclusions with a size smaller than 5 µm decreased from 76% to 55% as the basicity increased.


**Table 4.** Results of the inclusions in the 1#~7# cast samples.

The size distribution of the inclusions in the 1#~7# steel samples is shown in Table 5. For the 1#~4# samples with different Al2O<sup>3</sup> contents, the percentage of inclusions with a diameter larger than 10 µm decreased from 13% to 4%. In contrast, the percentage of inclusions with a diameter smaller than 2 µm increased from 20% to 33%. For the 2# , 5# , 6 # and 7# samples with different basicities, the percentage of inclusions with a diameter larger than 10 µm increased from 6% to 19%. In contrast, the percentage of inclusions with a diameter smaller than 2 µm increased from 31% to 17%.


**Table 5.** The size distribution of the inclusions in the 1#~7# steel samples (percentage). **Table 5.** The size distribution of the inclusions in the 1#~7# steel samples (percentage).

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#### *3.2. Composition and Morphology of Typical Inclusions 3.2. Composition and Morphology of Typical Inclusions*

SEM-EDS was selected to analyze the composition and morphology of the inclusions. Several randomly selected inclusions were tested and analyzed regarding the composition of the inclusions. The mapping method of typical composite inclusions was carried out to accurately analyze the elemental distribution and structure of the structural inclusions. According to the results, four kinds of typical inclusions were observed in the steel samples, namely, CaO–SiO2–Al2O3–MgO, CaO–SiO2–Al2O3–MgO–MnS, MnS, and SiO2, as shown in Figure 4. SEM-EDS was selected to analyze the composition and morphology of the inclusions. Several randomly selected inclusions were tested and analyzed regarding the composition of the inclusions. The mapping method of typical composite inclusions was carried out to accurately analyze the elemental distribution and structure of the structural inclusions. According to the results, four kinds of typical inclusions were observed in the steel samples, namely, CaO–SiO2–Al2O3–MgO, CaO–SiO2–Al2O3–MgO–MnS, MnS, and SiO2, as shown in Figure 4.

**Figure 4.** *Cont*.

**Figure 4.** The typical inclusions in steel samples. 1#: (**a**–**c**); 2#: (**d**–**f**); 3#: (**g**–**i**); 4#: (**j**–**l**); 5#: (**m**–**o**); 6#: (**p**–**r**); 7#: (**s**–**u**). **Figure 4.** The typical inclusions in steel samples. 1# : (**a**–**c**); 2# : (**d**–**f**); 3# : (**g**–**i**); 4# : (**j**–**l**); 5# : (**m**–**o**); 6 # : (**p**–**r**); 7# : (**s**–**u**).

Most of the compounds contained oxide inclusions, especially the CaO–SiO2–Al2O3– MgO inclusions with a diameter of 10 μm. The MnS inclusions generally formed during solidification with a diameter larger than 5 μm. In contrast, the SiO2 inclusions had a smaller diameter of approximately 1 μm. Most of the compounds contained oxide inclusions, especially the CaO–SiO2–Al2O3–MgO inclusions with a diameter of 10 µm. The MnS inclusions generally formed during solidification with a diameter larger than 5 µm. In contrast, the SiO<sup>2</sup> inclusions had a smaller diameter of approximately 1 µm.

The multi-component composite inclusions were generally uniform; that is, the elements in the inclusions were evenly distributed in the whole inclusion without delamination, as shown in Figure 5. Generally, these inclusions would not cause obvious harm to spring steel. In addition, the structure of the layered composite inclusions was usually a homogeneous composite with a layer of MnS inclusions wrapped around the edges. This kind of inclusion will be separated during the hot rolling and cold drawing of spring steel due to the composition and plasticity of the inner and outer layers being The multi-component composite inclusions were generally uniform; that is, the elements in the inclusions were evenly distributed in the whole inclusion without delamination, as shown in Figure 5. Generally, these inclusions would not cause obvious harm to spring steel. In addition, the structure of the layered composite inclusions was usually a homogeneous composite with a layer of MnS inclusions wrapped around the edges. This kind of inclusion will be separated during the hot rolling and cold drawing of spring steel due to the composition and plasticity of the inner and outer layers being different; they would appear as long strips along the rolling direction or drawing direction.

**Figure 5.** Elemental mapping of inclusions in steel samples. **Figure 5.** Elemental mapping of inclusions in steel samples.

#### *3.3. Composition Distribution of Typical Inclusions 3.3. Composition Distribution of Typical Inclusions*

The composition distribution of inclusions overlayed on a phase diagram with different Al2O<sup>3</sup> contents and different basicities in the refining slag are shown in Figure 6 and Figure 7, respectively. The "small symbols" are the compositions of each inclusion in a ternary phase diagram, and the "colored square" is the average composition of all the inclusions in the 1 #~7# steel samples. The detail composition of typical inclusions in samples were shows in **Table 6**. The composition distribution of inclusions overlayed on a phase diagram with different Al2O<sup>3</sup> contents and different basicities in the refining slag are shown in Figures 6 and 7, respectively. The "small symbols" are the compositions of each inclusion in a ternary phase diagram, and the "colored square" is the average composition of all the inclusions in the 1 #~7# steel samples. The detail composition of typical inclusions in samples were shows in Table 6.

different; they would appear as long strips along the rolling direction or drawing direc-

Figure 6 shows that the content of Al2O3(inc) in the inclusions and aluminosilicate inclusions had a tendency of increasing with the content of Al2O3(slag) increasing in the slag. The compound oxide inclusions were mainly concentrated in low-melting-point regions for all of the steel samples. In detail, the average contents of inclusions were SiO2(inc): 48.27%, CaO(inc)+MgO(inc): 34.39%, Al2O3(inc): 17.34%; SiO2(inc): 48.87%, CaO(inc)+MgO(inc): 30.01%, Al2O3(inc): 21.12%; SiO2(inc): 53.46%, CaO(inc)+MgO(inc): 17.44%, Al2O3(inc): 29.10%, SiO2(inc): 49.63%, CaO(inc)+MgO(inc): 18.40% and Al2O3(inc): 31.97%.

**Figure 6.** Inclusion distribution overlaid on a phase diagram with the refining slags at fixed Al2O3 contents of (**a**) 3 wt.%, (**b**) 5 wt.%, (**c**) 8 wt.% and (**d**) 12 wt.%. **Figure 6.** Inclusion distribution overlaid on a phase diagram with the refining slags at fixed Al2O<sup>3</sup> contents of (**a**) 3 wt.%, (**b**) 5 wt.%, (**c**) 8 wt.% and (**d**) 12 wt.%. **Figure 6.** Inclusion distribution overlaid on a phase diagram with the refining slags at fixed Al2O3 contents of (**a**) 3 wt.%, (**b**) 5 wt.%, (**c**) 8 wt.% and (**d**) 12 wt.%.

basicities of (**a**) 0.5, (**b**) 0.8, (**c**) 1.0 and (**d**) 1.2. **Figure 7.** Inclusion distribution overlaid on a phase diagram with the refining slags with different basicities of (**a**) 0.5, (**b**) 0.8, (**c**) 1.0 and (**d**) 1.2. **Figure 7.** Inclusion distribution overlaid on a phase diagram with the refining slags with different basicities of (**a**) 0.5, (**b**) 0.8, (**c**) 1.0 and (**d**) 1.2.


**Table 6.** Chemical compositions of typical inclusions in the experimental steel samples (mass fraction, %).

Figure 7 shows that most inclusions were located in the low-melting-point region, the inclusions distribution was dispersed in the 5# steel sample with a basicity of 0.5 in the slag, and the inclusions distribution was concentrated in the 2# , 6# and 7# steel samples with basicities of 0.8, 1.0 and 1.2 in the slag, respectively. In detail, the average contents of inclusions in these steel samples were SiO2(inc): 60.26%, CaO(inc)+MgO(inc): 15.49%, Al2O3(inc): 24.25%; SiO2(inc): 48.87%, CaO(inc)+MgO(inc): 30.01%, Al2O3(inc): 21.12%; SiO2(inc): 54.56%, CaO(inc)+MgO(inc): 18.27%, Al2O3(inc): 27.17%, SiO2(inc): 49.06%, CaO(inc)+MgO(inc): 24.34% and Al2O3(inc): 26.60%.

#### *3.4. Mechanical Properties of the Experiment Steels*

The mechanical properties of the experimental steels are shown in Table 7. It is obvious that the tensile strength gradually increased from 1357.83 MPa to 1437.04 MPa as the content of Al2O<sup>3</sup> in the slag increased from 3 wt.% (1# ) to 12 wt.% (4# ). In contrast, the reduction in area and elongation slightly decreased from 27.58% and 10.24% to 24.31% and 9.36%, respectively.



The fracture morphologies are shown in Figure 8. From the macroscopic appearance of the fractures, the fractures of the four samples were typically cup-shaped and were divided into a fiber area, radiation area and shear lip area from the center to the edge. The radiation areas of the fractures of samples 1# and 2# were relatively flat, and there were few secondary microcracks, showing certain brittle fracture characteristics. In particular, many long and deep but directionless cracks appeared in the radiation area of sample 1# , as shown in the white triangle area in the figure. In addition, the area of the radiation area tended to gradually increase; in contrast, the area of the shear lip gradually decreased. Moreover, the shape of the radiation area also gradually changed from an irregular shape and ellipse to a more regular circle. Finally, the number of secondary microcracks in the radiation area of the fracture surface of samples 3# and 4# significantly increased, radiating from the center to the edge along the radial direction. Furthermore, the length and depth of the secondary crack gradually became more uniform.

Comparing the microstructures of the four steel samples' fractures, it was found that they all contained three kinds of microstructures, namely, secondary microcracks, tear dimples and fine equiaxed dimples. There was no significant difference in the fracture morphology of the four steel samples.

The tensile strength decreased gradually from 1442.12 MPa to 1367.84 MPa as the basicity of slag increased from 0.5 (5# ) to 1.2 (7# ). In contrast, the reduction in area and elongation slightly increased from 24.23% to 27.32% and from 9.36% to 9.96%, respectively.

The fracture morphologies of samples 5# , 2# , 6# and 7# are shown in Figure 9. By comparing the macro morphology of these four samples, it can be seen that all the fracture morphologies were typical cup-shaped vertebrae, which was their common point. The 5# sample had the largest radiation area, and the shape tended to be a regular circle. Secondary microcracks with high density were evenly distributed in the radiation area. This indicated that the sample's structure was relatively uniform. The radiation area of sample 2# was an irregular oval with a small area. In contrast, the shear lip area was large. Moreover, the fracturing of the 2# sample was relatively flat, with only a small number of secondary cracks, which generally presented the characteristics of brittle fracture. The fiber area at the fracture of the 6# sample was near the center of the circle, and the shape of the radiation area was a regular circle with a large area. The regularity of the fracture morphology of sample 7# was the worst, where the fiber area was far away from the center of the circle, the morphology of the radiation area was irregular, and the radiation area was very uneven with a large number and distribution of long and deep cracks. In addition, the area of the shear lip was large.

**Figure 8.** Micro and macro fracture morphologies of the steel samples. **Figure 8.** Micro and macro fracture morphologies of the steel samples.

Comparing the microstructures of the four steel samples' fractures, it was found that they all contained three kinds of microstructures, namely, secondary microcracks, tear dimples and fine equiaxed dimples. There was no significant difference in the fracture morphology of the four steel samples. The tensile strength decreased gradually from 1442.12 MPa to 1367.84 MPa as the basicity of slag increased from 0.5 (5#) to 1.2 (7#). In contrast, the reduction in area and elongation slightly increased from 24.23% to 27.32% and from 9.36% to 9.96%, respectively. When comparing the microstructures of the four steel samples' fractures, it was found that they all contained three kinds of microstructures, namely, secondary microcracks, tear dimples and fine equiaxed dimples. With the increase in alkalinity, the microstructure at the fracture surface of the samples changed greatly: the number and size of secondary microcracks gradually increased, there were high-density large and deep holes in the fracture of the 6# sample (these holes were likely caused by large hard inclusions), and there were not only large and deep holes but also many cleavage planes at the fracture of sample 7# .

The fracture morphologies of samples 5#

Moreover, the fracturing of the 2

fiber area at the fracture of the 6

addition, the area of the shear lip was large.

The 5

, 2#
