Search Results (1,906)

The polymer industry gained increasing importance due to the ability of polymers to replace traditional materials such as wood, glass, and metals in various applications, offering advantages such as high strength-to-weight ratio, corrosion resistance, and ease of fabrication. Among key performance indicators, melt flow rate (MFR) plays a crucial role in determining polymer quality and processability. However, conventional offline laboratory methods for measuring MFR are time-consuming and unsuitable for real-time quality control in industrial settings. To address this challenge, the study proposes a leveraging artificial intelligence with machine learning-based melt flow rate prediction for polymer properties analysis (LAIML-MFRPPPA) model. A dataset of 1044 polymer samples was used, incorporating six input features such as reactor temperature, pressure, hydrogen-to-propylene ratio, and catalyst feed rate, with MFR as the target variable. The input features were normalized using min–max scaling. Two ensemble models—kernel extreme learning machine (KELM) and random vector functional link (RVFL)—were developed and optimized using the pelican optimization algorithm (POA) for improved predictive accuracy. The proposed method outperformed traditional and deep learning models, achieving an R² of 0.965, MAE of 0.09, RMSE of 0.12, and MAPE of 3.4%. A SHAP-based sensitivity analysis was conducted to interpret the influence of input features, confirming the dominance of melt temperature and molecular weight. Overall, the LAIML-MFRPPPA model offers a robust, accurate, and deployable solution for real-time polymer quality monitoring in manufacturing environments. Full article

Automated optical inspection (AOI) of wood surfaces is critical for ensuring product quality in the furniture and manufacturing industries; however, existing defect detection systems often struggle to generalize across complex grain patterns and diverse defect types. This study proposes a wood defect recognition model employing a Gabor Convolutional Network (GCN) that integrates convolutional neural networks (CNNs) with Gabor filters. To systematically optimize the network’s architecture and improve both detection accuracy and computational efficiency, the Taguchi method is employed to tune key hyperparameters, including convolutional kernel size, filter number, and Gabor parameters (frequency, orientation, and phase offset). Additionally, image tiling and augmentation techniques are employed to effectively increase the training dataset, thereby enhancing the model’s stability and accuracy. Experiments conducted on the MVTec Anomaly Detection dataset (wood category) demonstrate that the Taguchi-optimized GCN achieves an accuracy of 98.92%, outperforming a baseline Taguchi-optimized CNN by 2.73%. Results confirm that Taguchi-optimized GCNs enhance defect detection performance and computational efficiency, making them valuable for smart manufacturing. Full article

This paper reviews various emerging alternative SCMs derived from minerals and biomass sources, industrial byproducts, and underutilized waste streams. The paper compiles and evaluates physicochemical properties, reaction mechanisms in cementitious systems, resource availability, supply chain dynamics, technology readiness, the impact on concrete performance, and environmental and cost factors for each candidate SCM. Specifically, the review examines wood ash from bioenergy plants, volcanic and sedimentary natural pozzolans, and construction and demolition waste. This includes recycled concrete fines, asphalt plants’ rock dust (baghouse fines), aggregate production fines, and post-consumer waste, particularly municipal solid waste incinerator ash and wastewater sludge ash. Additionally, the paper explores innovative additives such as cellulose and chitin nanomaterials and calcium–silicate–hydrate nanoseeds to address challenges of slower strength development and rheological changes. The key contribution of this review is a multifactor framework for assessing alternative SCMs, emphasizing availability, supply chain, market readiness, and environmental performance, combined with an engineering performance review. Full article

Measuring the bioeconomy enables policymakers to monitor advancements in sustainable development goals, identify growth opportunities, comprehend the economic implications of bio-based products, assess environmental impacts, and shape policies that foster a sustainable economy reliant on renewable biological resources. For this purpose, this study measures the value of the bioeconomy in New Zealand using the latest published input–output table for the year 2020. This study estimates the size and economic significance of New Zealand’s bioeconomy by applying two complementary methodologies. Results indicate that, in 2020, the total value added by the bioeconomy ranged from NZD 48.8 billion to NZD 50.8 billion, representing 16.5% to 17.1% of the nation’s total value added. Agriculture emerged as the dominant contributor, accounting for approximately 89% of the sector’s total value added, followed by forestry and logging at around 11%. To identify potential growth areas, the analysis further disaggregated bioeconomy value added by economic subsectors. Among bio-based industries, food manufacturing was the largest contributor, generating 43.1% (NZD 21 billion) of total bioeconomy value added, followed by bio-based services at 12.9% (NZD 6.3 billion). The biotechnology sector contributed NZD 0.34 billion, equivalent to 0.7% of the total bioeconomy. Additional significant contributors included wood processing and manufacturing (3.3%; NZD 1.6 billion), construction (0.71%; NZD 0.35 billion), and textiles and clothing (0.58%; NZD 0.29 billion). These findings underscore the pivotal role of food manufacturing, services, wood processing, textiles and clothing, and construction in shaping the bioeconomy. They further highlight the importance of assessing the economic and environmental impacts of bio-based industries and formulating policy frameworks that support a sustainable, renewable resource-based economy. Full article

Buildings represent approximately 40% of the total energy consumption. Net-zero energy buildings (NZEBs) have lower energy demands than conventional buildings due to improved thermal insulation combined with other passive design strategies. Thermal mortars, used in insulating plasters, help improve buildings’ energy efficiency in a cost-effective manner, with minimal added thickness, even on irregular surfaces. Brewer’s spent grain (BSG) accounts for 85% of the total by-products of the brewing industry. It is a cellulosic wood material, with a composition rich in protein (20%) and fiber (70%). Considering these properties, it has potential for use as a natural aggregate in mortars and as a sustainable material for buildings aligned with circular economy principles. This work aims to characterize BSG as a natural by-product for use in thermal mortars and identify different incorporation percentages. First, BSG was characterized in terms of its water content, particle size and volume mass. Then, mortars with BSG and fine sand, with different water contents, were produced and compared to a reference mortar and two commercially available thermal mortars. The performance of the mixtures was evaluated in terms of water absorption, mechanical behavior (namely, compressive and flexural strength) and thermal behavior. BSG mortars with a 0.25 w/c ratio presented a water absorption coefficient similar to that of the reference mortar. Overall, BSG mortars presented a mechanical strength profile similar to that of conventional thermal mortars. In the thermal test, the best BSG mortar (BSG75-w/c-0.25) achieved a stationary temperature difference between surfaces that was 8% lower than that of a commercial thermal mortar and 110% higher than that of the reference mortar. In sum, the best BSG mortars had a lower w/c ratio. Full article

This study presents the Wood Protection Sustainability Index (WPSI), a novel decision-support tool aimed at evaluating wood preservatives utilized in Chile and facilitating a shift toward more sustainable wood protection practices. WPSI encompasses four essential attributes: protection treatment, wood durability, in-service risk, and sustainability. These are assessed under two distinct scenarios. Scenario 1 represents current market practices, where chromated copper arsenate (CCA) remains prevalent due to its accessibility and affordable cost. In contrast, Scenario 2 prioritizes sustainability, demonstrating that copper azole (CA) and alkaline copper quaternary (ACQ) surpass CCA in performance, with CCA ranking lowest due to its environmental implications. Furthermore, a SWOT analysis accompanies the index, identifying key challenges and opportunities within Chile’s wood preservation industry. The findings highlight the importance of aligning national strategies with Environmental, Social, and Governance (ESG) frameworks, as well as the Sustainable Development Goals (SDGs), through performance-based regulations and safer alternatives. The WPSI can be integrated with local standards, regional risk classifications, and national preservative approval systems, allowing for meaningful comparison across diverse global contexts. This approach promotes more sustainable construction practices while ensuring both technical and economic viability. Full article

The objective of this study was to analyze price variability and the factors influencing the formation of monthly prices of by-products of the wood industry in Poland between October 2017 and January 2025. The analysis considered the impact of economic variables, including energy commodity prices (natural gas and coal) and industrial wood prices, on the pricing of wood industry by-products. The adopted approach enabled the identification of key determinants shaping the prices of these by-products. The effectiveness of two tree-based regression models—Random Forest (RF) and CatBoost (CB)—was compared in the analysis. Although RF offers greater interpretability and lower computational requirements, CB proved more effective in modeling dynamic, time-dependent phenomena. The results indicate that industrial wood prices exerted a weaker influence on by-product prices than natural gas prices, suggesting that the energy sector plays a leading role in shaping biomass prices. Coal prices had only a marginal impact on the biomass market, implying that changes in coal availability and pricing did not directly translate into changes in the prices of wood industry by-products. The growing role of renewable energy sources derived from natural gas and wood biomass is contributing to the emergence of a distinct market, increasingly independent of the traditional coal market. In Poland, due to limited access to alternative energy sources, biomass plays a critical role in the decarbonization of the energy sector. Full article

Wastewater containing synthetic dyes harmful to aquatic environments supposes significant challenges for treatment. This study focuses on how structural characteristics of three N-containing carbons synthesized at high temperatures from polyacrylonitrile (PAN) as a precursor, i.e., an N-doped (PAN-C), an activated carbon (PAN-C-Act), and a carbon also incorporating sulfur (PAN-S-C), influence adsorption of a common dye employed for wood veneers (Red GRA 200%). The impact of pH (1.9–2.3, 6.0–6.8, and 11.8–12.6), adsorbent dosage (S/L, 0.43–0.53 and 1.73–1.91 g L⁻¹), and amount of dye (24–28 mg L⁻¹ and 231–285 mg L⁻¹) on dye removal from aqueous solutions were investigated. In general, the results obtained in the present work indicate that the presence of larger pores in the materials plays an important role in dye adsorption by preventing size exclusion of the dye molecules. The activated carbon (PAN-C-Act) demonstrated the greatest adsorption performance, with an adsorption yield close to 100% achieved at a carbon dose of 0.47 g L⁻¹ and acidic pH for the highest dye concentration and longest experiment time. The pseudo-second-order model best described the kinetics, and both external mass transfer and intra-particle diffusion were confirmed. Full article

A wide range of microorganisms, including endophytes, frequently interact with forest trees. The role of endophytes in industrial conifers has not been fully investigated. The Yezo spruce Picea jezoensis is widely used for logging in Russia and Japan. In this work, the endophytic communities of bacteria and fungi in healthy needles, branches, and fresh wood of P. jezoensis from Primorsky Territory were analyzed using metagenomic analysis. The results indicate that the diversity of endophytic communities in P. jezoensis is predominantly influenced by the specific tree parts (for both bacteria and fungi) and by different tree specimens (for fungi). The most abundant bacterial classes were Alphaproteobacteria, Gammaproteobacteria and Actinobacteria. Functional analysis of KEGG orthologs (KOs) in endophytic bacterial community using PICRUSt2 and the PLaBAse PGPT ontology revealed that 59.5% of the 8653 KOs were associated with plant growth-promoting traits (PGPTs), mainly, colonization, stress protection, bio-fertilization, bio-remediation, vitamin production, and competition. Metagenomic analysis identified a high abundance of the genera Pseudomonas and Methylobacterium-Methylorubrum in P. jezoensis, which are known for their potential growth-promoting activity in other coniferous species. The dominant fungal classes in P. jezoensis were Dothideomycetes, Sordariomycetes, and Eurotiomycetes. Notably, the genus Penicillium showed a pronounced increase in relative abundance within the fresh wood and needles of Yezo spruce, while Aspergillus displayed elevated abundance specifically in the fresh wood. It is known that some of these fungi exhibit antagonistic activity against phytopathogenic fungi. Thus, our study describes endophytic communities of the Yezo spruce and provides a basis for the production of biologicals with potential applications in forestry and agriculture. Full article

This study investigated the potential of hazelnut wood (Corylus avellana L.) as an alternative raw material in the production of single-layer structural particleboards. Boards with a target density of 700 kg m⁻³ and thickness of 13 mm were manufactured using varying substitution levels (5%, 10%, 25%, 50% and 100%) of hazel wood particles relative to industrial pine (Pinus sylvestris L.) particles. Phenol-formaldehyde (PF) resin was used as the adhesive at a 15% resination rate. Mechanical and physical properties, including modulus of rupture (MOR), modulus of elasticity (MOE), internal bond (IB), screw withdrawal resistance (SWR), water absorption (WA), and thickness swelling (TS), were evaluated according to relevant European standards. Density profiles (DP) were also assessed. The results showed that while higher hazel content reduced bending strength (from 23.3 N mm⁻² for reference to 18.7 N mm⁻² for 100% hazel wood board) and stiffness (from 3515 N mm⁻² for reference to 2520 N mm⁻² for 100% hazel wood board), most boards met standard mechanical requirements of EN 312 for P3 and P5 boards. Notably, IB strength improved significantly at higher hazel content, with the 100% variant (2.07 N mm⁻²) exceeding the reference board (1.57 N mm⁻²). Screw withdrawal resistance also increased with hazel wood addition (from 235 N mm⁻¹ for reference to 262 N mm⁻¹ for 100% hazel wood board), linked to its higher density. However, water resistance and dimensional stability worsened with increasing hazel content, particularly in bark-containing particles, leading to excessive thickness swelling after prolonged water exposure. Thickness swelling after 24 h of soaking rose from 16.36% for the reference board to 20.13% for the 100% hazel wood board. Density profiles revealed a more uniform internal structure in boards with higher hazel content. Overall, hazelnut wood shows promise as a partial substitute for pine in particleboard production, especially at moderate substitution levels, though limitations in moisture resistance must be addressed for broader industrial application. Full article

Pine wood has a natural, rustic, and environmentally friendly style and is used in a large number of applications in the furniture industry. However, its soft and porous texture makes it susceptible to bacteria, mould, and other micro-organisms. Pine wood was selected as the test substrate, and tea tree essential oil@chitosan (TTO@CS) microcapsules with emulsifier concentrations of 4%, 5%, and 6% were added to the waterborne topcoat at a content of 1%–9% (in 2% intervals) to investigate their effect on the surface coating properties of pine wood. With the increase in microcapsule content, there was an overall increase in colour difference and light loss rate of pine wood surface coating, and the reflectance showed an increase and then decrease. The overall performance of the pine wood surface coatings containing 7% of 13# microcapsules was found to be excellent: the antimicrobial activity of the coatings was 62.58% for Escherichia coli and 61.29% for Staphylococcus aureus after 48 h, and the antimicrobial activity of the coatings was 40.14% for Escherichia coli and 38.89% for Staphylococcus aureus after 4 months. The colour difference in the coating was 2.37, and the light loss was 63.71%. The reflectance value was found to be 0.6860, while the hardness was determined to be 2H and the adhesion class was categorised as one. The impact resistance class was determined to be three, while the roughness was measured at 1.320 μm. The waterborne coating on the surface of pine wood was modified by microencapsulation technology with the objective of enhancing the antimicrobial properties of pine wood and expanding its scope of application. Full article

Traditionally, mechanical bending tests are used to measure the stiffness of lumber, which is generally represented by the static modulus of elasticity (MoE). However, it is desirable to measure the stiffness of wood before it is processed into lumber. Acoustic nondestructive testing techniques are therefore the main techniques used by the wood industry to estimate the dynamic MoE of wood. The acoustic resonance technique is employed for measuring the MoE in felled logs and lumber. In contrast, the acoustic time-of-flight (ToF) technique is traditionally used for MoE measurements on standing trees and seedlings. However, the ToF technique overestimates stiffness compared to both resonance and static bending tests (considered the gold standard). In this work, a guided wave technique is used to measure the stiffness of wooden rods. This work is the first to compare the MoE values obtained using static bending tests (gold standard) with those obtained using acoustic resonance, ToF, and guided wave methods. Measurements were performed on 16 mm diameter radiata pine wooden rods. For comparison, measurements were also performed on acetal, aluminium, and steel rods of similar dimensions. The findings show that stiffness measurements obtained using the proposed guided wave method are more accurate than those obtained using the traditional ToF method and closely match those of the resonance method across all materials. The measurements from the ToF method were overestimated compared to resonance, guided wave, and static bending methods. The findings show the potential for the guided wave method to be used as an alternative method to provide more accurate stiffness measurements in juvenile trees/seedlings compared with the traditional ToF technique. Full article

Pyrolysis of oily sludge (OS) faces two significant challenges, dehydration in emulsion and coke formation, which cause extra energy consumption. Targeting energy saving, this paper first reported on solar photothermal dehydration and confined catalytic pyrolysis of OS using a single material. A wood sponge loaded with carbon dots (CM-CDs) can generate heat by absorbing solar energy and promote rapid phase separation and water transport via capillary action of oil–water emulsion in OS under sunlight. Almost all free water in OS with varied content can be removed after 3 h. Hydrocarbons entered the internal space of CM-CDs instead of contacting with soil minerals, contributed to the subsequent confined catalytic pyrolysis, led to a reduction in Ea (35.61 kJ/mol), inhibited coking and caking, and yielded higher oil recovery efficiency. In addition, CDs can form hotspots to enhance pyrolytic behaviors in local regions. When the ratio of OS to CM-CDs reached 10:0.6, the recovery rate of the oil fraction through combined pyrolysis was as high as 89%, which was 17% higher than that of OS pyrolysis alone. This discovery provides a new way to solve the bottleneck problems of OS pyrolysis in the industry. Full article

Industrial tree plantations (ITPs) are increasingly recognized as a sustainable response to deforestation and the decline in native wood resources in the Philippines. This study presents LUNTIAN (Labor, UNiversity, Timber Investment, and Agent-based Nexus), an agent-based model that simulates an experimental ITP operation within a mountain forest managed by University of the Philippines Los Baños. The model integrates biophysical processes—such as tree growth, hydrology, and stand dynamics—with socio-economic components such as investment decision making based on risk preferences, employment allocation influenced by local labor availability, and informal harvesting behavior driven by job scarcity. These are complemented by institutional enforcement mechanisms such as forest patrolling, reflecting the complex interplay between financial incentives and rule compliance. To assess the model’s validity, its outputs were compared to those of the 3PG forest growth model, with results demonstrating alignment in growth trends and spatial distributions, thereby supporting LUNTIAN’s potential to represent key ecological dynamics. Sensitivity analysis identified investor earnings share and community member count as significant factors influencing net earnings and management costs. Parameter calibration using the Non-dominated Sorting Genetic Algorithm yielded an optimal configuration that ensured profitability for resource managers, investors, and community-hired laborers while minimizing unauthorized independent harvesting. Notably, even with continuous harvesting during a 17-year rotation, the final tree population increased by 55%. These findings illustrate the potential of LUNTIAN to support the exploration of sustainable ITP management strategies in the Philippines by offering a robust framework for analyzing complex social–ecological interactions. Full article