Search Results (1,704)

Microbial priming is an emerging strategy in sustainable agriculture that involves the use of beneficial microorganisms to enhance agricultural productivity and sustainability. This innovative approach leverages the natural interactions between plants and microorganisms to promote plant growth and improve soil health. This study explores the application of microbial priming on almond seeds, focusing on the biostimulant effect of soil-based microbial extracts from a mediterranean shrub Pistacia lentiscus L. as an ecological strategy to improve the germination and seedling of almond (Prunus dulcis (Mill.)). The extraction process of soil differentiates three extracts: the first separates AMF spores (Myco) from all other bacterial and fungal consortia (MW), and the third combines the two previous extracts (MW + Myco). The experiment evaluated germination rates, seedling growth parameters, and conducted physico-chemical soil analyses. Arbuscular Mycorrhizal Fungi (AMF) colonization was also measured. Microbial priming significantly improved germination rates and enhanced seedling growth compared to untreated controls. The three microbial extracts showed significant effects on germination rate after 20 days, exceeding 90%. After 27 days, all treatments reach their maximum (100%). Seedling indicators allow MW + Myco extract to be considered as the most powerful extract on almond seedling growth. The combination of microbial and endomycorrhizal fungal extracts could be considered as a facilitator of seedling growth of almond. The AMF colonization was notably higher in treated plants. Overall, microbial priming effectively enhances almond seed germination and seedling growth, demonstrating its potential as a sustainable biostimulation strategy in agriculture. This practice boosts crop productivity and promotes soil health by enriching microbial communities and improving nutrient cycling. These results open up perspectives towards a natural-based strategy able to facilitate the germination and early seedling of almonds in both nurseries and in the field—and to enhance the productivity and health of almond cultivation in special Mediterranean area. Full article

Biogas from palm oil mill effluent (POME) is a promising fuel that has many advantages as an alternative fuel. The methane content in biogas derived from POME is up to 75% and can be used as an alternative fuel in an internal combustion engine. One of the technologies for utilizing biogas in compression ignition engines is the Diesel Dual-Fuel (DDF) technique due to the different characteristics of fuel and the impact on the environment due to significantly reducing emissions. This study aims to find the effect of biogas POME composition and energy ratio on the DDF engine’s performance and emissions. The simulations using AVL BOOST software were confirmed by experimental engine parameters. The modeling was conducted on the biogas energy ratio (20%, 40%, 60%, and 75% POME) and biogas POME composition (55% and 75% methane). The results showed that the fuel consumption of diesel fuel was reduced by up to 69%, and NO_x and soot emissions were reduced by up to 92% and 80%, respectively, with dual-fuel mode operation. Meanwhile, the value of brake mean effective pressure (BMEP) and efficiency was reduced by up to 18%, volumetric efficiency decreased by up to 4%, the increase in brake specific energy consumption (BSEC) was up to 23%, and brake specific fuel consumption (BSFC) was up to 155%. The optimum of the engine’s performance and emission was 40% biogas ratio with 75% methane content. Full article

Introducing fast, reliable, and low-input technologies that utilize wholemeal wheat is essential for efficiently screening gluten quality in wheat breeding lines. Although the GlutoPeak Tester (GPT) has been widely studied for gluten assessment, its application in breeding programs remains underexplored. This study presents a comprehensive approach to optimizing a GPT protocol using a diverse set of genotypes collected over seven harvest years and multiple environments. To improve screening capabilities, a quick and simple protein fractionation (PF) technique was integrated into the workflow. Key GPT parameters—such as peak maximum time, maximum torque, and aggregation energy—along with the newly proposed PM-AM parameter, showed strong correlations with established quality traits. PF data, especially insoluble glutenin percentage and the ratio of insoluble to soluble glutenin, provided additional insights into gluten composition. This extensive dataset supports the use of GPT and PF as a dual, high-throughput screening tool. When applied within specific wheat classes and benchmarked against established checks, this method offers a robust strategy for ranking breeding lines based on gluten performance. The use of wholemeal samples further streamlines the process by eliminating the need for milling, making this protocol particularly suitable for early-stage selection in wheat breeding programs. Full article

In this research, micro-milling of Ti-6Al-4V has been carried out in the conventional machining range. The influence of key machining parameters, including feed rate, cutting speed, depth of cut, and cooling conditions, was statistically analyzed in relation to burr width and height on both the up-milling and down-milling sides. The feed rate, followed by cutting speed were found to be the most influencing factors affecting burr width with collective contribution of 89.06% in up-milling and 92.67% in down-milling. The depth of cut and cooling condition had negligible impact on burr width. Burr height was mostly affected by depth of cut and feed rate, whereas cutting speed and cooling condition had no impact on burr height. The combined contribution of depth of cut and feed rate to burr height was 77.36% in up-milling and 73.95% in down-milling. Full article

Using traditional methods to fabricate geometrically complicated items was challenging, but Additive Manufacturing (AM) has made it possible. Although AM (3D printing) was first developed to produce prototypes, in recent years it has also been utilized for the fabrication of end-use products. As a result, the mechanical strength of AMed parts has gained considerable significance. Three-dimensional printing has proved its capabilities in the fabrication of customizable parts with complex geometries. In the current study, the effects of manufacturing parameters on the mechanical strength and the fracture behavior of 3D-printed components have been investigated. To this aim, we fabricated specimens using Polyethylene Terephthalate Glycol (PETG) and the Fused Deposition Modeling (FDM) process. Particularly, the dumbbell-shaped and Single Edge Notched Bend (SENB) specimens were fabricated and examined to determine their tensile and fracture behaviors. Particularly, the notches in SENB specimens were introduced by two different techniques to investigate the influence of the manufacturing process on the mechanical performance of 3D-printed PETG parts. Moreover, finite element simulations were conducted to investigate the fracture behavior of the parts. The results indicate that the fracture loads of 3D-printed and milled parts are 599.1 N and 417.2 N, respectively. In addition, experiments confirm brittle fracture with no plastic deformation in all specimens with 3D-printed and milled notches. The outcomes of this study can be used for the future designs of FDM 3D-printed parts with a better structural performance. Full article

This study evaluated the effect of acidic environment and tooth brushing on the color stability and translucency of stained 3D-printed ceramic-reinforced composite (CRC) resins for indirect restorations and hybrid prostheses. Twelve specimens were prepared from each 3D-printing resin material: Ceramic Crown (CC), OnX (ONX), and Tough 2 (T2), and one CAD/CAM milling resin, Lava Ultimate (LU). After preparation, all specimens were stained, then immersed in either water or citric acid. Subsequently, the specimens underwent simulated tooth brushing for 3650 cycles. Color stability (ΔE) and translucency parameter (TP) were measured using a spectrophotometer. Data were analyzed using ANOVA, post hoc Tukey tests, and independent Student t-tests (α = 0.05). Material type, immersion medium, and their interaction did not significantly influence the mean ΔE (p > 0.05). The lowest ΔE value was for LU in acid (ΔE = 1.11 ± 0.39), and the highest for T2 in water (ΔE = 2.09 ± 1.47). Except for ONX and LU in acid, all materials had ΔE values above the perceptibility threshold (ΔE = 1.2). The mean TP was significantly affected by material type, immersion medium, and their interaction (p < 0.05). The lowest TP value was for group CC in acid (0.91 ± 0.26); the highest was for group LU in acid (6.24 ± 0.56). After immersion and subsequent tooth brushing, TP values decreased for all materials. Exposure to an acidic environment and tooth brushing did not affect color stability but significantly reduced translucency. Both the 3D-printed CRCs and milled resin material displayed comparable color stability below clinically acceptable thresholds, though the translucency of 3D-printed materials remained lower compared to milled material. Full article

Wood–plastic composite (WPC) is being increasingly adopted in construction and furniture applications due to its durability and recyclability. This study investigates face-milling responses—resultant cutting force and cutting temperature—under systematically varied cutting parameters, and develops a radial basis function neural network for predictive modeling. Experiments were conducted on a computer numerical control machining center using a polycrystalline diamond end-milling cutter for face milling with fixed axial depth of cut. Feed speed, radial depth of cut, and spindle speed were selected as input factors. The results indicate that feed speed and radial depth of cut generally increase all force components, whereas higher spindle speed tends to reduce force magnitudes while elevating temperature. The radial basis function neural network yields acceptable accuracy for resultant cutting force (coefficient of determination R² ≈ 0.91) and acceptable accuracy for cutting temperature (R² ≈ 0.81). These findings demonstrate the feasibility of radial basis function neural network based prediction for WPC face milling and provide guidance for parameter selection. Full article

The growing demand for automated production systems is driving continuous innovation in smart and data-driven manufacturing technologies. In the field of production metrology, the trend is shifting from using measurement laboratories to integrating measurement systems directly into production processes. This has led the Institute of Manufacturing Technology at TU Vienna together with its partners to develop a roughness measurement device that can be directly integrated into machine tools. Building on this foundation, this study tries to find applications beyond mere surface roughness assessment and demonstrates how the device could be applied in broader contexts of manufacturing process monitoring. By linking surface measurements with tool wear monitoring, the study establishes a correlation between surface roughness and wear progression of indexable inserts in milling. It demonstrates how in situ data can support predictive maintenance and the real-time adjustment of cutting parameters. This represents a first step toward integrating in situ metrology into closed-loop control in machining. The experimental setup followed ISO 8688-1 guidelines for tool life testing. Indexable inserts were operated throughout their entire service life while surface roughness was continuously recorded. In parallel, cutting edge conditions were documented at defined intervals using focus variation microscopy. The results show a consistent three-phase pattern: initially stable roughness, followed by a steady increase due to flank wear, and an abrupt decrease in roughness linked to edge chipping. These findings confirm the potential of integrated roughness measurement for condition-based monitoring and the development of adaptive machining strategies. Full article

Research into technological processes, such as welding, provides the basis for optimising the strength and quality of PVC joints, which are becoming increasingly important in the context of sustainable construction. The study analysed the influence of welding parameters on the quality and strength of the welds of PVC window profiles reinforced with glass fibre composite. The variable parameters were welding time (21–25 s) and composite milling depth (up to 1 mm). The constant parameters were a welding temperature of 264 °C and a head feed rate of 0.25 mm/s. The results showed that the most favourable results were achieved with a composite milling depth of 1 mm and a melting time of 22 s, which provided the highest average failure load values and met the strength requirements. Additionally, the white welds confirmed that the welding process had been carried out correctly, with no depolymerisation or material degradation occurring. In contrast, milling depths of less than 1 mm or no milling depth at all resulted in problems with dimensional tolerance. In addition, overloading of the welding machine during the welding process was observed for composite milling depths of less than 1 mm and a melting time of 22 s. The results of the study highlight the need for further analysis of the influence of other process parameters, including welding temperature. Full article

The aim of this study is to investigate the impact of machining parameters on the deflection of a cutting tool (i.e., end mill) in the milling of a surface with a curvilinear profile. Test samples were made of aluminium alloy EN AW-7075 T651. Experiments were conducted using the Gocator 2530 laser line profile sensor for real-time measurement of dynamic tool displacement with an inspection speed up to 10 kHz at resolution ranging from 0.028 to 0.054 mm. Response surface methodology was used. Five main technological factors were analysed: cutting speed, feed per tooth (cutting parameters), amplitude, term (curvilinear profile parameters), and the number of flutes (end mill parameter). Obtained data were filtered and visualised as 3D plots. The results showed that cutting speed and amplitude had the greatest impact on tool deflection, while feed per tooth also played a significant role in process stability. In particular, the use of tools with a higher number of flutes led to a considerable reduction in tool deflection, confirming their positive effect on the stability of the machining process. These findings may serve as a basis for the optimisation of machining parameters by taking into account the dynamic deformation of cutting tools. Full article

Glass fiber-reinforced polymer (GFRP) composites are highly susceptible to thermal damage during machining, which can compromise their structural integrity and final quality. This study examines the efficacy of graphene and wax additives in reducing drilling temperatures in GFRP composites. Nine unique samples were manufactured with varying weight percentages of wax (0%, 1%, 2%) and graphene (0%, 0.25%, 2%). Drilling experiments were performed on a CNC milling center under a range of cutting parameters, with temperature monitoring carried out using an infrared thermal camera. A hierarchical cubic response surface model was employed to analyze thermal behavior. The results indicate that cutting speed is the dominant factor, accounting for 67.28% of temperature generation. The formulation containing 2% wax and 0% graphene achieved the lowest average drilling temperature (64.64 °C), underscoring wax’s superior performance as both a lubricant and heat sink. Although graphene alone slightly elevated median temperatures, it substantially reduced thermal variability. The optimal condition for minimizing thermal damage was identified as 2% wax combined with a high cutting speed (200 mm/min), providing actionable insights for industrial process optimization. Full article

Plastic gears are used in a variety of industrial fields and are primarily produced by injection molding with a gear cavity. At present, EDM is usually used for machining gear cavities with metal materials, and the tool electrode used in the process is usually machined through a milling process. For helical gear cavities and helical bevel gear cavities, certain problems are encountered when the tool electrodes of EDM are obtained from milling procedures, including waste of raw materials and the complex technical process. Focusing on the above problems, this paper used copper powder to fabricate gear electrodes through a selective laser sintering process. The obtained gear electrodes underwent heat treatment and the effects of the main process parameters on the electrical conductance of tool electrodes were analyzed in this study. Finally, the heat-treated gear electrodes were applied to EDM to fabricate a helical gear cavity and a helical bevel gear cavity. During EDM, the TWR and MRR of the gear electrodes were 0.0029 mm³/min and 0.3872 mm³/min, respectively. Compared with that of gear electrodes made by the milling process, the MRR of the gear electrodes fabricated by SLS improved by 31.53%. Full article

This study examines the effects of the extreme drought and heatwaves that occurred in Romania during the summer of 2024 on the microbiological and mycotoxicological quality of wheat (Triticum aestivum) stored until April 2025, as well as on the quality of wholemeal flour and bread derived from it. Comparative analyses were conducted against the contamination in wheat harvested in 2024. The hot and dry conditions significantly influenced the microbial and mycotoxicological contamination of both freshly harvested and stored wheat, as well as the derived flour and bread, due to their notably reduced moisture content and water activity. Although levels of total fungi, Fusarium-damaged kernels, and mycotoxins deoxynivalenol, aflatoxin B1, and ochratoxin A remained well below regulatory thresholds, higher contamination was observed in Transylvania and Moldavia—particularly in the Curvature Carpathians, likely due to their cooler and wetter microclimates. The observed quality changes were strongly associated with alterations in physico-chemical, rheological, and colorimetric parameters, posing potential economic challenges for the milling and baking industries. The study recommends implementing integrated regional strategies to enhance wheat resilience, optimize production systems, and improve contamination control in response to increasing climate stress across Southeastern Europe. Full article

Turn-milling is a relatively new process which combines turning and milling operations, offering a number of advantages such as chip breaking and interrupted cutting, which improves tool life. In addition to providing the capability of producing eccentric forms or shapes, it increases productivity for difficult-to-machine material at lower cost. This study investigates the influence of cutting speed and feed on surface roughness and tool wear in conventional turning and turn-milling of H13 tool steel. The tests were conducted for longitudinal and face machining strategies. It was found that the range of surface roughness in turning is lower than in turn-milling. In longitudinal turning, face-turning, and face turn-milling operations, surface roughness is elevated in the higher feeds. However, the surface roughness in longitudinal turn-milling operations can be reduced by increasing the feed. Although the simultaneous rotation of the tool and workpiece in turn-milling could negatively affect the surface quality, this operation provides the advantage of an interrupted cutting mechanism that produces discontinuous chips. Also, the wear of the endmill in longitudinal and face turn-milling operations is lower than the wear of the inserts used in conventional longitudinal and face turning. Using Response Surface Methodology (RSM), mathematical models were developed for surface roughness and tool wear in each operation. The RSM models developed in this study achieved coefficients of determination (R²) above 90%, with prediction errors below 7% for surface roughness and below 3% for tool wear. The analysis of variance (ANOVA) revealed that the feed and cutting speed are the most influential parameters on the surface roughness and tool wear, respectively, with p-value < 0.05. The experimental results demonstrated that tool wear in turn-milling was reduced by up to 50% compared to conventional turning. Full article

This study aimed to evaluate the impact of different adhesive solutions on the surface roughness and hardness of denture base materials. Twenty specimens (20 × 20 × 5 mm) were produced for each material group: heat-cured ProBase Hot^®, 3D-printed NextDent Denture 3D+^®, and PMMA-milled Exaktus^®. They were then divided into five solution subgroups (n = 4): control (T0), distilled water, Corega PowerMax^®, Elgydium Fix^®, and Kukident Pro Ultimate^®. Specimens were immersed in the solution at 37 °C daily for 28 days, simulating continuous use. Profilometry and Shore D hardness tests were performed at baseline and after 28 days of the immersion protocol. Data analysis was done using IBM SPSS Statistics 30.0, considering a confidence level of 0.05. At baseline, the materials differed in surface roughness and Shore D hardness, with the 3D-printed group showing the highest median values for the Rz parameter (p = 0.023) and the lowest for hardness (p = 0.023). Elgydium Fix had a significant effect on the heat-cured resin, with increased Rz and decreased hardness. Kukident caused higher roughness and lower hardness in the 3D-printed and milled resins (not significant). Corega showed minor effects in all tested materials. In conclusion, the denture base material and the adhesive formulation influence the physical and mechanical properties of denture base resins. Full article