Demand For Materials Research Articles

Progress in galactomannan-based materials for biomedical application.

Progress in galactomannan-based materials for biomedical application.

Fully-biodegradable and self-powered intelligent filter assembled by fibrous cellulose and MOF-functionalized poly(lactic acid) core-shell nanofibers for active PM capturing and passive respiratory sensing.

Fully-biodegradable and self-powered intelligent filter assembled by fibrous cellulose and MOF-functionalized poly(lactic acid) core-shell nanofibers for active PM capturing and passive respiratory sensing.

Tamarind (Tamarindus indica L.) Seed Polysaccharide: A promising biopolymer for drug delivery, wound healing, tissue engineering and beyond.

Tamarind (Tamarindus indica L.) Seed Polysaccharide: A promising biopolymer for drug delivery, wound healing, tissue engineering and beyond.

Sustainability effects of material demand by next-generation lithium-ion battery technologies: A global value chain perspective

Sustainability effects of material demand by next-generation lithium-ion battery technologies: A global value chain perspective

Waste and Recycled Material in Concrete Technology

The increasing demand for sustainable and eco-friendly construction materials has led to the exploration of alternative materials in concrete production. This research investigates the performance of M50 grade concrete using industrial and agricultural waste materials—Fly Ash, Rice Husk Ash (RHA), and Coconut Shells (CS)—as partial replacements for cement and coarse aggregates. The increasing emphasis on sustainable construction has prompted researchers to explore the incorporation of industrial and agricultural waste materials into concrete. This study investigates the potential of using Fly Ash, Rice Husk Ash (RHA), and Coconut Shells (CS) as partial replacements in high-strength M50 grade concrete. The aim is to evaluate their influence on workability, strength, durability, and density, while reducing dependency on conventional materials. The project involves developing a standard M50 concrete mix and then partially replacing cement with Fly Ash and RHA, and coarse aggregates with Coconut Shells. Each mix was tested for fresh and hardened properties over different curing periods. The experimental work follows IS codes and standard testing protocols to ensure accuracy and consistency. The results indicate that these waste materials can effectively be used in concrete without compromising essential performance characteristics. Depending on the type and percentage of replacement, they also contribute to reduced material cost, improved environmental sustainability, and lower dead load in structural elements. The study underscores the feasibility of using waste-based concrete in both structural and non-structural applications.

Innovative Use of Paddy Straw Ash in Concrete: Boosting Strength and Sustainability

The increasing demand for sustainable building materials has prompted the use of agricultural waste products in concrete production. This paper explores the potential of using paddy straw ash (PSA), a by-product of rice farming, as a partial replacement for cement in concrete. The effects of various replacement levels of PSA on the compressive strength, durability and workability of concrete are evaluated. Compressive strength tests on mortar samples with varying PSA replacement levels (0–25%) revealed that optimal strength was achieved with 5–10% PSA substitution. The study demonstrates that PSA can improve the sustainability of concrete by enhancing its strength and reducing its environmental impact, while also making use of agricultural waste.

Comparison between Normal Concrete and Ultra High Performance Concrete

Over the last twenty years, remarkable advances have taken place in the research and application of ultra-high performance concrete (UHPC), which exhibits excellent rheological behaviour’s that include workability, self-placing and selfdensifying properties, improved in mechanical and durability performance with very high compressive strength, and nonbrittleness behaviour. It is the ‘future’ material with the potential to be a viable solution for improving the sustainability of buildings and other infrastructure components. This paper will give an overview of UHPC focusing on its fundamental introduction, design, applications and challenges. After several decades of development, a wide range of commercial UHPC formulations have been developed worldwide to cover an increasing number of applications and the rising demand of quality construction materials. UHPC has several advantages over conventional concrete but the use of it is limited due to the high cost and limited design codes. This paper also aims to help designers, engineers, architects, and infrastructure owners to expand the awareness of UHPC for better acceptance.

Antagonistic Effect Between Deformation and Magnetism in Liquid Metal Coils Smart Architecture for Multi‐Mode Sensing

AbstractAddressing the growing demand for advanced smart materials in complex operational environments, the Antagonistic Liquid Metal Architecture (ALMA), a novel system exhibiting sophisticated multi‐responsivity and robustness is introduced. ALMA uniquely integrates temperature‐induced deformation and magnetically modulated liquid metal coils within a PDMS@Fe matrix to achieve tunable inductance. By varying the Fe‐to‐PDMS weight ratio (WR), the temperature coefficient of inductance is precisely controlled from positive (0.032%/K) to negative (−0.052%/K), demonstrating exceptional linearity (R2 ≈ 0.999). Notably, at WR = 1.4, ALMA enables temperature‐insensitive pressure sensing, minimizing temperature‐induced inductance error to <0.01875%/K. This, combined with intrinsic resistance changes, facilitates decoupled pressure and temperature multimodal sensing. Furthermore, a biomimetic superhydrophobic surface (>150° contact angle) imparts remarkable environmental robustness, ensuring visible protection against acid‐induced corrosion. Long‐term monitoring confirms ALMA's reliability and sensitivity to subtle temperature variations. ALMA presents a versatile and robust smart material platform, promising significant advancements in flexible sensors for diverse applications including industrial monitoring, advanced robotics, and extreme environment exploration.

Machine learning-enabled optoelectronic material discovery: a comprehensive review

The development of advanced optoelectronic materials constitutes a pivotal frontier in modern energy and communication technologies, facilitating critical energy-photon-electron interconversion processes that underpin sustainable energy infrastructures and high-performance electronic devices. However, the discovery and optimization of novel optoelectronic materials face substantial hurdles arising from complicated structure-property interdependencies, prohibitive development costs, and protracted innovation cycles. Conventional empirical approaches and computational simulations usually exhibit limited efficacy in addressing the escalating demands for materials with superior stability, economic viability, and customizable electronic properties. The integration of machine learning (ML) with high-throughput screening has emerged as a transformative strategy to address these challenges. By rapidly processing large multidimensional datasets and predicting critical material properties such as electronic structure, thermodynamic stability, and charge transport behaviors, ML offers unprecedented capabilities in the efficient and rational design of high-performance optoelectronic materials. This review provides a comprehensive overview of cutting-edge ML-driven methodologies in efficient optoelectronic materials discovery with emphasis on critical workflows, data integration strategies, and model frameworks. We also discuss the challenges and prospects for ML applications, particularly in data standardization, model interpretability and closed-loop experimental validation. We further propose the potential of artificial intelligence and autonomous laboratories to build a powerful discovery pipeline to advance the development of high-performance optoelectronic materials.

Advancing Circular Economy Through Optimized Construction and Demolition Waste Management Under Life Cycle Approach

The construction industry significantly impacts the environment, consuming 50% of natural resources and generating 20% of global greenhouse gas (GHG) emissions. In developing countries, managing construction and demolition (C&D) waste is a growing challenge due to rapid urbanization and inadequate waste management practices. This study employs life cycle assessment and life cycle costing to compare landfill and recycling scenarios for C&D waste using ISO 14040 (Environmental Management—Life Cycle Assessment—Principles and Framework) and ISO 14044 (Environmental Management—Life Cycle Assessment—Requirements and Guidelines). The study’s system boundary encompasses the entire life cycle of C&D waste management, with one ton of C&D waste as the functional unit. The results demonstrated that landfilling C&D waste is harmful due to negative impacts from transportation and landfill emissions. Recycling shows promising potential by significantly reducing environmental impacts and lowering the demand for new raw materials. The recycling scenario substantially decreased GHG emissions, saving 37 kg of CO2 equivalents per ton of waste. Economically, recycling C&D waste proved more viable, with favorable indicators. Implementing a recycling plant in Lahore could save USD 2.53 per ton in resource costs and mitigate significant environmental impacts. This study recommends that policymakers in developing countries prioritize C&D waste recycling to enhance sustainability and support the transition to a circular economy. The findings provide valuable insights for developing effective waste management strategies, contributing to environmental conservation and economic efficiency. These recommendations guide future initiatives for sustainable C&D waste management, promoting a greener and more resilient urban environment. Furthermore, this study underlines the potential of C&D waste recycling to contribute significantly to achieving Sustainable Development Goals (SDGs), particularly sustainable cities (SDG 11), responsible consumption and production (SDG 12), and climate action (SDG 13).

Hyperspectral Investigation of an Abandoned Waste Mining Site: The Case of Sidi Bou Azzouz (Morocco)

The increasing demand for critical raw materials (CRMs), driven by global energy transition, underscores the need for innovative approaches to identify secondary resources, such as mining residues. Mining residues, often overlooked during initial mining activities, now represent valuable sources of raw materials thanks to technological advancements, including hyperspectral remote sensing. This study investigates the potential of hyperspectral satellite imagery to detect and map CRMs in mining residues of the abandoned Sidi Bou Azzouz mine in Morocco. The proposed approach is based on the integration between satellite data, field spectroscopy, chemical, and mineralogical analyses in a strong multi-scale and interdisciplinary framework. The integration between advanced laboratory techniques, including LIBS, XRF, XRPD, and SEM-EDS, was employed to enhance hyperspectral data interpretation. The integration of remote sensing and laboratory results provided a comprehensive understanding of mineral composition, confirming the effectiveness of hyperspectral methods for characterizing heterogeneous surface deposits. This research demonstrates the potential of hyperspectral observations to identify valuable raw materials and to map them using PRISMA imagery in abandoned mining residues, offering a tool useful for planning cost-effective and sustainable solutions aimed at answering the growing demand for CRMs crucial to industrial competitiveness and sustainable growth.

Cationic Carbon Dot Reinforced Highly Tensile, Tough, Dehydration Resistant Polyelectrolyte Hydrogels with Fluorescence for Flexible Sensing and Information Anti-Counterfeiting.

With the rapid development of wearable devices, there is an increasing demand for multifunctional conductive soft materials. Nanocomposite hydrogels containing carbon nanofillers such as carbon dots (CDs) composite gels emerge as promising candidates. However, traditional CDs nanocomposite hydrogels face limitations in terms of mechanical strength, stability and elasticity. To overcome these critical challenges, in this work, a cationic carbon dots (CCDs)-reinforced polyelectrolyte hydrogel engineered through synergistic electrostatic assembly and salting-out strategies is developed. The polyacrylic acid/sodium hyaluronate/cationic carbon point glycerol-water binary solvent fluorescent organohydrogel (PAH-CG) is fabricated. The resulting organohydrogel PAH-CG successfully overcame the plasticizing effect of glycerol, resulting in a significant enhancement of mechanical properties, with a 149-fold increase in Young's modulus compared to the control hydrogel. Specifically, the PAH-CG hydrogel exhibited high tensile strain (1200%-2734%), tensile strength (234kPa), and modulus (275kPa), alongside excellent elasticity, fluorescence, and dehydration resistance. The improvement in mechanical properties leads to excellent performance in flexible sensor applications. Concurrently, glycerol incorporation not only amplifies fluorescence intensity but also improves dehydration resistance and moisture absorption. Applications for encrypted transmission of information and anti-counterfeiting have been developed based on these properties, making PAH-CG hydrogels a promising platform for advanced smart devices.

Mechanical Insights through Finite Element Analysis: Flax Woven Fabric Reinforced Epoxy via Vacuum Infusion

The growing demand for sustainable materials has driven interest in natural fiber-reinforced composites (NFRCs), with flax fibers emerging as a promising candidate due to their high specific strength, low density, and biodegradability. However, the widespread adoption of flax-based composites is hindered by challenges in manufacturing processes and the need for accurate predictive models to assess their mechanical performance. This study investigates the tensile properties of flax woven fabric reinforced epoxy composites fabricated using the vacuum infusion process (VIP) and evaluates their performance through both Finite Element Analysis (FEA) and experimental testing. The primary objective is to compare FEA predictions with experimental results, identify discrepancies, and propose improvements for predictive modeling. FEA predicted tensile strengths ranging from 216.31 MPa for 2 plies to 65.31 MPa for 8 plies, while experimental results showed lower values, ranging from 75.60 ± 5.37 MPa for 2 plies to 143.95 ± 13.76 MPa for 6 plies. Similarly, FEA overestimated tensile moduli, with values ranging from 4.33 GPa to 6.53 GPa, compared to experimental values of 2.83 ± 0.20 GPa to 3.41 ± 0.31 GPa. The largest discrepancies were observed for 2 plies and 8 plies, highlighting limitations in FEA models due to assumptions of ideal conditions, such as perfect fiber alignment and uniform resin distribution. These findings underscore the importance of considering real-world manufacturing variables, such as fiber misalignment, resin variability, and interfacial defects, which are often overlooked in FEA models. In conclusion, while FEA provides valuable theoretical insights, experimental results emphasize the need for refined modeling approaches that account for material imperfections and fabrication processes. Future work should focus on enhancing FEA models to improve the accuracy of predictions for flax-based composites, supporting their broader adoption in sustainable engineering applications.

A Review of Industrial By-Product Utilization and Future Pathways of Circular Economy: Geopolymers as Modern Materials for Sustainable Building

In the era of increasing climatic requirements and changing approaches towards circular economy (CE), the demand for materials designed with care for the environment is growing. This idea is especially important in the construction industry, where ordinary Portland cement (OPC) production emits a large number of greenhouse gases. The main aim of this article is to demonstrate the possibility of using industrial waste for geopolymer production according to CE goals, including closing material loops. This work is based on a critical analysis of the literature and selected case studies. The most important findings of this article allow us to confirm that the role of industrial waste in the construction industry is growing and that industrial by-products are valuable sources for geopolymer production. The development of sustainable materials allows the introduction of closed loops into production processes by making it possible to reuse materials after the end of use, which is an important issue in the context of introducing CE into practice, especially in existing systems.

Strategic Significance and Sustainable Development Prospects of Offshore Sea Sand Resources in Guangdong Province

Against the backdrop of Guangdong Province's rapid economic development, the demand for construction materials continues to rise. Offshore sea sand resources, with advantages such as abundant reserves, concentrated distribution, and relatively convenient extraction, have become an essential material foundation for supporting regional engineering projects. In-depth research on the genetic mechanism and sustainable development pathways of offshore sea sand in Guangdong holds significant practical value. This paper systematically analyzes the strategic value of offshore sea sand resources in Guangdong's regional economic construction, elaborates on its genesis from the perspectives of geological processes, marine dynamics, and sedimentary environments, and identifies problems encountered in current development practices. Based on this, it proposes sustainable development pathways aimed at providing theoretical references and practical guidance for the scientific development and rational use of Guangdong's offshore sea sand resources.

ANFIS modelling of the strength properties of natural rubber latex modified concrete

The increasing demand for sustainable construction materials has driven research into innovative modifications to enhance concrete performance while reducing environmental impact. This study investigates the optimization of Natural Rubber Latex Modified Concrete (NRLMC) using an Adaptive Neuro-Fuzzy Inference System (ANFIS), a hybrid AI model that integrates fuzzy logic and neural networks for precise property prediction. The justification for this study stems from the need for an eco-friendly, high-performance alternative to conventional concrete, leveraging renewable natural rubber latex (NRL) to improve mechanical properties and durability. Laboratory experiments were conducted to evaluate the effects of varying NRL and calcium sulfate (CaSO4) contents on compressive, flexural, and splitting tensile strength. Results showed that an optimal mix of 10% NRL and 2% CaSO4 achieved a compressive strength of 44.27 MPa, while 9% NRL and 1.8% CaSO4 yielded peak flexural and splitting tensile strengths of 12.33 MPa and 5.1 MPa, respectively. Beyond these thresholds, mechanical properties declined due to matrix destabilization. Microstructural analysis using Scanning Electron Microscopy and Energy Dispersive X-ray Spectroscopy confirmed NRL’s role in reducing porosity and enhancing matrix uniformity. The ANFIS model demonstrated exceptional accuracy, with low RMSE and MAPE values and a strong R2 correlation, offering a superior predictive framework compared to traditional modeling techniques. Furthermore, SHAP analysis reveals that OPC (%) and NRL (%) are the primary contributors to compressive and tensile strength, while CaSO4 (%) has a moderate impact, particularly on flexural and tensile properties, providing valuable insights for optimizing material composition in construction applications. This research holds significant implications for sustainable infrastructure development, promoting renewable resource utilization while enhancing the durability and resilience of concrete structures. Future studies should explore hybrid AI models, long-term field performance, and additional material combinations to further optimize NRLMC’s applicability in various structural environments.

Material and energy use in Norway's residential building archetypes

AbstractBuildings require substantial amounts of resources, as both construction materials and operational energy. In Norway, as buildings become more energy efficient due to advancements in construction, technology, and stricter regulations, the relative impact of construction and maintenance materials rises. However, there is a lack of comprehensive data on construction and material use, and consequently, their embodied emissions. While some studies explored the environmental impacts of Norwegian buildings, they often either focus on case‐study buildings or only the operational emissions, due to limited data on embodied emissions; others rely on inconsistent statistical correlations between energy use and material composition. Bottom‐up physics‐based building archetypes offer a solution to fill this gap by providing structured data on energy use and material composition. This paper, therefore, introduces 21 archetypes of Norwegian residential buildings, categorized into three typologies and seven construction cohorts. Dynamic energy simulations were conducted, using DesignBuilder, for estimating space heating consumption, combined with the BuildME Python package for material estimation and aggregation. We found that load‐bearing components drive building's material intensity, especially in wooden buildings with basements. Post‐1991 multi‐family houses (MFHs) have lower material intensity than single‐family houses (SFHs) and apartment blocks (ABs), though ABs outperform them by lower space heating demand. Substitution of concrete slabs by wood and increasing occupancy to MFH's level can reduce the material intensity of ABs and SFHs, respectively. By establishing integrated energy and material demand models, archetypes provide a representative and scalable basis for further assessment of building stock's resource use, renovation impacts, and environmental studies.

A New Methodology to Fabricate Polymer–Metal Parts Through Hybrid Fused Filament Fabrication

This paper introduces a new methodology that enables the production of polymer–metal parts through hybrid additive manufacturing. The approach combines fused filament fabrication (FFF) of polymers with adhesive bonding of metal inserts, applied during layer-by-layer construction. The work is based on unit cells designed and fabricated using eco-friendly materials—polylactic acid (PLA) and aluminum—which were subsequently analyzed for build quality and for mechanical performance under tensile lap-shear and three-point bending tests. The acquired knowledge in terms of optimal processing parameters for attaining strong polymer–metal bonds was then applied for the fabrication and testing of prototypes representing modular corner connectors for framing applications. Results on build quality demonstrate that issues, such as lumps and warping, can be solved by finetuning the 3D printing stages of the proposed methodology. In terms of destructive testing, significant improvements in the mechanical performance of PLA can be achieved, demonstrating the feasibility of the proposed methodology in integrating the lightweight properties of polymers with the stiffness of metals. This enables the development of innovative, sustainable and eco-friendly solutions that align with the growing demand for eco-friendly materials and processes in manufacturing.

Light extraction film for organic light-emitting diodes based on an eco-friendly template comprising cellulose and polyphenon 60

The demand for eco-friendly, alternative materials and processes is increasing across various industries to substitute petroleum-based materials, which have negative environmental impacts. Therefore, this study developed an environmentally sustainable template using polyphenon 60 (P60) extracted from green tea and hydroxyethyl cellulose (HEC) via a solvent-free process employing only deionized water. The template surface exhibited randomly distributed microscale aggregates owing to the chemical interactions between HEC and P60, with their morphology varying as a function of the P60 concentration. The quantitative analysis utilizing fill factor calculations demonstrated that increased P60 concentration led to a higher aggregate density and larger structure sizes as the fill factor values increased from 21% at 1.5 wt% to 45% at 2.0 wt% and 86% at 2.5 wt%. This precise modulation of the P60 concentration enabled systematic control over the aggregate size and density, offering a significant advantage in optimizing the structural properties of the enhanced optical performance template. The light extraction film showed enhanced efficiency of up to 29.5% in all directions when integrated into an organic light-emitting diode (OLED), validating the effectiveness of the proposed method in improving device performance. These findings highlight a scalable and sustainable approach for advancing OLED display and lighting technologies.

High-Strength Conductive Hydrogel Fiber Prepared Via Microfluidic Technology for Functionalized Strain Sensing.

The rapid advancement of wearable flexible electronics has heightened the demand for hydrogel materials that combine mechanical robustness with electrical conductivity. Herein, the TEMPO-oxidized cellulose nanofibers-Graphene nanosheets/poly(vinyl alcohol)-sodium alginate-tannic acid (TOCN-GN/PVA-SA-TA, TGG) composite hydrogel fibers are prepared by microfluidic spinning technology to solve the bottleneck problems of poor dispersion of GN and imbalance of mechanical-conductive properties of traditional hydrogels. TOCN, acting as a biotemplate, effectively inhibits GN agglomeration via hydrogen bonding and mechanical interlocking, thereby enhancing GN dispersion and facilitating the formation of 3D conductive networks within hydrogel fibers. The optimized TGG fibers achieved a tensile strength of 0.96MPa, 150% elongation at break, and electrical conductivity of 2.66 S m-1, while exhibiting enhanced energy dissipation and fatigue resistance. As strain sensors, TGG fibers demonstrated high sensitivity (gauge factor is 1.81 at 40-100% strain) and rapid response (≈0.3 s), enabling precise monitoring of joint movements, facial micro-expressions, and swallowing actions. Furthermore, PDMS-encapsulated textile sensors enabled encrypted Morse code transmission, demonstrating innovative potential for next-generation flexible electronics in health monitoring and human-machine interfaces.