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Greening the Bond: A Narrative and Systematic Literature Review on Advancing Sustainable and Non-Toxic Adhesives for the Fiberboard Industry
Prosper Mensah
,Rafael Rodolfo Melo
,Alexandre SantosPimenta Pimenta
,James Amponsah
,Gladys Tuo
,Fernando Rusch
,Edgley Alves de Oliveira Paula
,Humphrey Danso
,Juliana de Moura
,Márcia Ellen Chagas dos Santos Couto
+2 authors
Posted: 14 October 2025
Optimized De-Chlorination Strategy of ASR-Based Solid Recovered Fuel (SRF) via Inorganic Additive and Bamboo Blending
Chen-Hui Chen
,Way Long
,Tung-Lin Wu
,Jeng-Wei Tsai
,Yan-Jia Liou
,Chun-Shen Cheng
,Shu-Hsien Tsai
,Rung-Jiun Gau
,Li-Chi Su
,Chuan-Chi Chien
The objective of this study was to investigate the chlorine-related challenges in Automotive Shredder Residue (ASR) by developing a de-chlorination strategy and formulating Solid Recovered Fuel (SRF) pellets with improved environmental and fuel quality. A ternary blending approach was employed using Fe–Ca-based inorganic dechlorinating agents and thorny bamboo biomass as co-materials with ASR. The de-chlorination efficiency, calorific value, and ash content of the resulting SRF were evaluated. Results indicated that the optimal dechlorinating formulation reduced the chlorine content of PVC from 43.26 wt% to 0.59 wt%, achieving a de-chlorination efficiency of 97.23%. A second-order polynomial regression model(η_DeCl = –1.5277x² + 2.5519x – 0.0225,R² = 0.9347)was developed to predict the de-chlorination performance based on the blending ratio of dechlorinating agent to ASR, demonstrating behavior consistent with first-order reaction kinetics observed in pyrolytic de-chlorination. The final ternary formulation—comprising 55% thorny bamboo, 37.5% ASR, and 7.5% dechlorinating agent—produced SRF pellets with improved overall quality, demonstrating effective chlorine control, reasonable ash content, and enhanced thermal properties suitable for regulatory compliance and practical application. Such findings meet the criteria set by EN ISO 21640:2021 (Class 2), JIS Z7311 (Grade A), and forthcoming Taiwanese SRF regulations. Based on the findings in this work it can be stated that the high de-chlorination potential of Fe–Ca-based additives for chlorine-rich waste and introduces a predictive formulation model that supports both resource circularity and clean fuel production.
The objective of this study was to investigate the chlorine-related challenges in Automotive Shredder Residue (ASR) by developing a de-chlorination strategy and formulating Solid Recovered Fuel (SRF) pellets with improved environmental and fuel quality. A ternary blending approach was employed using Fe–Ca-based inorganic dechlorinating agents and thorny bamboo biomass as co-materials with ASR. The de-chlorination efficiency, calorific value, and ash content of the resulting SRF were evaluated. Results indicated that the optimal dechlorinating formulation reduced the chlorine content of PVC from 43.26 wt% to 0.59 wt%, achieving a de-chlorination efficiency of 97.23%. A second-order polynomial regression model(η_DeCl = –1.5277x² + 2.5519x – 0.0225,R² = 0.9347)was developed to predict the de-chlorination performance based on the blending ratio of dechlorinating agent to ASR, demonstrating behavior consistent with first-order reaction kinetics observed in pyrolytic de-chlorination. The final ternary formulation—comprising 55% thorny bamboo, 37.5% ASR, and 7.5% dechlorinating agent—produced SRF pellets with improved overall quality, demonstrating effective chlorine control, reasonable ash content, and enhanced thermal properties suitable for regulatory compliance and practical application. Such findings meet the criteria set by EN ISO 21640:2021 (Class 2), JIS Z7311 (Grade A), and forthcoming Taiwanese SRF regulations. Based on the findings in this work it can be stated that the high de-chlorination potential of Fe–Ca-based additives for chlorine-rich waste and introduces a predictive formulation model that supports both resource circularity and clean fuel production.
Posted: 18 September 2025
Turning Waste into Treasure: Preparation of Gypsum Fibers from Flotation Phosphorus Tailings and Their Use as Paper Fillers
Zhengguo Xue
,Yongju Luo
,Long Liu
,Zhixuan Tu
,Hong Cao
,Jun Xue
Posted: 15 September 2025
Sandblasting Wood as a Technique of Simulated Weathering
Marko Petrič
,Luka Albreht
,Eli Keržič
,Jaka Levanič
,Matjaž Pavlič
,Jernej Skerbiš
Posted: 05 August 2025
Effect of Steam Explosion (SE) Pretreatment on the Contamination of Woody Biomass with Metallic Inhibitors
Jan Szadkowski
,Anna Gałązka
,Witold Jan Wardal
Posted: 24 July 2025
Anatomical Barriers to Impregnation in Hybrid Poplar: A Comparative Study of Pit Characteristics in Normal and Tension Wood
Andreas Buschalsky
,Holger Militz
,Tim Koddenberg
Posted: 09 July 2025
A Wavelength‐Rule for the Analysis of Clusteroluminescence
Frank B. Peters
,Andreas O. Rapp
Posted: 24 June 2025
Experimental Study of the Vapor Retarder’s Impact on Moisture Content in a Multi-Layer Log Wall
Róbert Uhrín
,Stanislav Jochim
,Vlastimil Borůvka
,Miloš Pavelek
,Pavol Sedlák
,Dominika Búryová
,Katarína Střelcová
Posted: 13 June 2025
Multilayer Barrier Coatings with Starch/Bentonite for Paperboards—The Effects of the Number of Layers and the Drying Strategy on the Barrier Properties
Lars Järnström
,Hanna Christophliemk
,Erik Bohlin
,Johan Larsson
,Per Emilsson
Posted: 22 May 2025
Recycling Particleboard by Acid Hydrolysis: Effects on the Physical, Thermal, and Chemical Characteristics of Recycled Wood Particles
Gustavo E. Rodríguez
,Rosilei Garcia
,Alain Cloutier
Posted: 18 April 2025
Modelling and Analysis of the Cooling Process in Post-Hot Flat-Pressed Wood-Plastic Composites
Pavlo Lyutyy
,Pavlo Bekhta
,Ján Sedliačik
Posted: 17 April 2025
Valorisation of Forest Waste into Natural Textile Dyes – Case Study of Pine Cones
Anna Barreto
,Jorge M Martins
,Nuno Ferreira
,Isabel Brás
,Luisa M. H. Carvalho
Posted: 03 April 2025
The Creation and Testing of a New Biodegradable Diapermade of Kapok Fiber and Bamboo Cloth
Jose Jessie Manaloto Maravilla
,Miguel Antonio Alvarez Aganon
,Apollo T Duque
,Michael Julian I De Los Reyes
,Jinhyung Park
Posted: 28 March 2025
Veneer Composites for Structural Applications – Mechanical Parameters as Basis for Design
Robert Krüger
,Beate Buchelt
,Mario Zauer
,André Wagenführ
Posted: 03 March 2025
Research on the Preparation of Supercapacitor Separators with High Wettability and Excellent Temperature Adaptability through In Situ Deposition of Nano-Barium Sulfate on Regenerated Cellulose
Hui Li
,Jiehua Li
,Chuanshan Zhao
,Fenfen Zhao
With portable electronics and new-energy vehicles booming, the demand for high-performance energy storage devices has skyrocketed. Supercapacitor separators are thus vital. Traditional ones such as polyolefins and non-woven fabrics have limitations, while cellulose and its derivatives, with low cost, good hydrophilicity, and strong chemical stability, are potential alternatives. This study used regenerated cellulose Lyocell fibers. Through fiber treatment, refining, and in situ deposition, a composite regenerated cellulose separator (NFRC-Ba) with nano-barium sulfate was made. Its physical, ionic, and charge–discharge properties were tested. The results show that NFRC-Ba excels in terms of mechanical strength, porosity, hydrophilicity, and thermal stability. Compared with the commercial NKK30AC-100 separator, it has better ionic conductivity, better ion-transport ability, a higher specific capacitance, better capacitance retention, and good cycle durability. It also performs stably from -40°C to 100°C. With a simple and low-cost preparation process, NFRC-Ba could be a commercial separator for advanced supercapacitors.
With portable electronics and new-energy vehicles booming, the demand for high-performance energy storage devices has skyrocketed. Supercapacitor separators are thus vital. Traditional ones such as polyolefins and non-woven fabrics have limitations, while cellulose and its derivatives, with low cost, good hydrophilicity, and strong chemical stability, are potential alternatives. This study used regenerated cellulose Lyocell fibers. Through fiber treatment, refining, and in situ deposition, a composite regenerated cellulose separator (NFRC-Ba) with nano-barium sulfate was made. Its physical, ionic, and charge–discharge properties were tested. The results show that NFRC-Ba excels in terms of mechanical strength, porosity, hydrophilicity, and thermal stability. Compared with the commercial NKK30AC-100 separator, it has better ionic conductivity, better ion-transport ability, a higher specific capacitance, better capacitance retention, and good cycle durability. It also performs stably from -40°C to 100°C. With a simple and low-cost preparation process, NFRC-Ba could be a commercial separator for advanced supercapacitors.
Posted: 21 February 2025
Machine Learning Algorithms and Nondestructive Methods for Estimating Wood Density in Planted Forest Trees
Rafael Gustavo Mansini Lorensani
,Raquel Gonçalves
Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees, aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, Extreme Gradient Boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R²) of 89% and a root mean square error (RMSE) of 10.6 kg·m⁻³. In contrast, the conventional statistical model, using the same parameters, yielded an R² of 33% and an RMSE of 26.4 kg·m⁻³. These findings highlight the superior performance of machine learning in nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry.
Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees, aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, Extreme Gradient Boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R²) of 89% and a root mean square error (RMSE) of 10.6 kg·m⁻³. In contrast, the conventional statistical model, using the same parameters, yielded an R² of 33% and an RMSE of 26.4 kg·m⁻³. These findings highlight the superior performance of machine learning in nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry.
Posted: 22 January 2025
A Comparative Study and Thermophysical Characterization of Wool Fiber from Different Regions of Morocco
Nabil Aazou
,Faical Zaim
,Said Gmouh
Wool fibers have long been used in home textiles and clothing, but their future looks even more promising with the growing consumer demand for natural, renewable, and sustainable materials. Beyond traditional clothing, wool is gaining increasing attention in the field of technical textiles due to its unique properties that make it suitable for a wide range of applications. As a natural and renewable fiber, wool offers benefits including tremendous moisture absorption, temperature law, and flame resistance, which make it a perfect material for technical textiles. In this study, two styles of Moroccan wool (Sardi and Timahdite), sourced from one-of-a-kind areas become accrued to explore their bodily and chemical homes and to investigate their capacity use within the manufacturing of nonwoven textiles for technical applications. Various analyses were carried out, inclusive of Fourier-remodel infrared spectroscopy and the Optical Fiber Diameter Analyzer, together with numerous check techniques based totally on global standards. These tests evaluated parameters which include grease content material, alkali content, acid content, solubility in alkali, and tensile strength. The results showed that Timahdite wool is the most suitable for nonwovens, way to its fineness and excessive absorbency compared with the Sardi wool.
Wool fibers have long been used in home textiles and clothing, but their future looks even more promising with the growing consumer demand for natural, renewable, and sustainable materials. Beyond traditional clothing, wool is gaining increasing attention in the field of technical textiles due to its unique properties that make it suitable for a wide range of applications. As a natural and renewable fiber, wool offers benefits including tremendous moisture absorption, temperature law, and flame resistance, which make it a perfect material for technical textiles. In this study, two styles of Moroccan wool (Sardi and Timahdite), sourced from one-of-a-kind areas become accrued to explore their bodily and chemical homes and to investigate their capacity use within the manufacturing of nonwoven textiles for technical applications. Various analyses were carried out, inclusive of Fourier-remodel infrared spectroscopy and the Optical Fiber Diameter Analyzer, together with numerous check techniques based totally on global standards. These tests evaluated parameters which include grease content material, alkali content, acid content, solubility in alkali, and tensile strength. The results showed that Timahdite wool is the most suitable for nonwovens, way to its fineness and excessive absorbency compared with the Sardi wool.
Posted: 08 January 2025
Advanced Phosphorus-Protein Hybrid Coatings for Fire Safety of Cotton Fabrics, Developed Through the Layer-by-Layer As-sembly Technique
Xuqi Yang
,Xiaolu Li
,Wenwen Guo
,Abbas Mohammadi
,Marjan Entezar Shabestari
,Ehsan Naderi Kalali
,Rui Li
,Shuyi Zhang
Posted: 06 January 2025
Enhanced Properties of Cryptomeria japonica from the Azores Through Heat-Treatment
Bruno Esteves
,Lina Nunes
,Rogério Lopes
,Luísa Cruz-Lopes
Posted: 20 December 2024
Exploring the Molecular Structure and Treatment Dynamics of Cellulose Fibres with Photoacoustic and Reversed Double-Beam Spectroscopy
Levente Csóka
,Worakan Csoka
,Ella Tirronen
,Ekaterina Nikolskaya
,Yrjö Hiltunen
,Bunsho Ohtani
Posted: 25 October 2024
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