Materials Science Research Articles

Optimizing agricultural downstream supply chain: addressing information asymmetry and losses

PurposeThis study aims to understand the significant issues in the downstream supply chain of agricultural commodities and find out the improved strategy.Design/methodology/approachA value chain analysis on a downstream supply chain is performed to understand all ground-level issues related to information asymmetry and material losses. The study maps processes, actors, activities, product flow, information flow, material volume flow, technology adoption and value share. The study is performed by doing a qualitative survey using a semi-structured questionnaire and face-to-face interviews with 120 farmers, six aggregators, six traders in APMC mandis, six processors, six distributors and six retailers. A case study is performed on the mustard supply chain in Rajasthan to relate the results more comprehensively. After identifying the prominent issues, a cause-and-effect analysis is done to generate suggestions for improvement in the paper.FindingsThe study reveals that the downstream supply chain has 8–12% losses of agricultural produce, and 5–7% of that is at the farmer’s end as post-harvesting losses. Farmers cannot access all available options for marketing their produce because of poor information exchange and poor reach. It suggests farmer empowerment for the optimum benefit of the entire supply chain.Research limitations/implicationsThis is an exploratory study conducted by field visits and lacks statistical evidence for some findings. The dataset can be more extensive, diversified, and analyzed for various commodities.Practical implicationsThe study’s outcome will guide the stakeholders in finding more optimum options in the downstream agriculture supply chain. Research methodology can be used as a template for studying the supply chain of any agricultural commodity in different countries.Originality/valueThe study reveals the prominent issues, causes, effects and solutions throughout the agriculture downstream supply chain. The study is a bundle of foremost observations altogether. The study has been conducted in-depth in the field with actual scenarios that unlayered the hidden issues at the root. This study addresses a relatively underexplored area and provides actionable recommendations, which significantly contribute to the existing literature on the agriculture supply chain.

Transition of Perovskite Solar Technologies to Being Flexible

AbstractPerovskite technologies has taken giant steps on its advances in only a decade time, from fundamental science to device engineering. The possibility to exploit this technology on a thin flexible substrate gives an unbeatable power to weight ratio compares to similar photovoltaic systems, opening new possibilities and new integration concepts, going from building integrated and applied photovoltaics (BIPV, BAPV) to internet of things (IoT). In this perspective, the recent progress of perovskite solar technologies on flexible substrates are summarized, focusing on the challenges that researchers face upon using flexible substrates. A dig into material science is necessary to understand what kind of mechanisms are limiting its efficiency compare to rigid substrates, and which physical mechanism limits the upscaling on flexible substrate. Furthermore, an overview of stability test on flexible modules will be described, suggesting common standard procedure and guidelines to follow, showing additional issues that flexible modules face upon bending, and how to prevent device degradation providing an ad‐hoc encapsulation. Finally, the recent advances of flexible devices in the perovskite market will be shown, giving an outline of how this technology is exploited on flexible substrates, and what are still missing that need stakeholders’ attention.

Prof. George Whitesides’ Contributions to Self-Assembled Monolayers (SAMs): Advancing Biointerface Science and Beyond

Prof. George Whitesides’ pioneering contributions to the field of self-assembled monolayers (SAMs) have profoundly influenced biointerface science and beyond. This review explores the development of SAMs as highly organized molecular structures, focusing on their role in advancing surface science, biointerface research, and biomedical applications. Prof. Whitesides’ systematic investigations into the effects of SAMs’ terminal group chemistries on protein adsorption and cell behavior culminated in formulating “Whitesides’ Rules”, which provide essential guidelines for designing bioinert surfaces. These principles have driven innovations in anti-fouling coatings for medical devices, diagnostics, and other biotechnological applications. We also discuss the critical role of interfacial water in SAM bioinertness, with studies demonstrating its function as a physical barrier preventing protein and cell adhesion. Furthermore, this review highlights how data science and machine learning have expanded the scope of SAM research, enabling predictive models for bioinert surface design. Remarkably, Whitesides’ Rules have proven applicable not only to SAMs but also to polymer-brush films, illustrating their broad relevance. Prof. Whitesides’ work provides a framework for interdisciplinary advancements in material science, bioengineering, and beyond. The enduring legacy of his contributions continues to inspire innovative approaches to addressing challenges in biomedicine and biotechnology.

Applications of Nanomaterial Coatings in Solid-Phase Microextraction (SPME)

This review explores the advances in developing adsorbent materials for solid-phase microextraction (SPME), focusing on nanoparticles, nanocomposites, and nanoporous structures. Nanoparticles, including those of metals (e.g., gold, silver), metal oxides (e.g., TiO2, ZnO), and carbon-based materials (e.g., carbon nanotubes, graphene), offer enhanced surface area, improved extraction efficiency, and increased selectivity compared to traditional coatings. Nanocomposites, such as those combining metal oxides with polymers or carbon-based materials, exhibit synergistic properties, further improving extraction performance. Nanoporous materials, including metal–organic frameworks (MOFs) and ordered mesoporous carbons, provide high surface area and tunable pore structures, enabling selective adsorption of analytes. These advanced materials have been successfully applied to various analytes, including volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), pesticides, and heavy metals, demonstrating improved sensitivity, selectivity, and reproducibility compared to conventional SPME fibers. The incorporation of nanomaterials has significantly expanded the scope and applicability of SPME, enabling the analysis of trace-level analytes in complex matrices. This review highlights the significant potential of nanomaterials in revolutionizing SPME technology, offering new possibilities for sensitive and selective analysis in environmental monitoring, food safety, and other critical applications.

Elemental Germanium Activation and Catalysis Enabled by Mechanical Force

In the realm of materials science and chemical industry, germanium emerges as a strategic resource with distinctive properties that extend its applicability beyond traditional electronics and optics into the promising field of chemical catalysis. Despite its significant role in advanced technological applications, the potential of elemental germanium as a catalyst remains unexplored. Leveraging recent developments in mechanochemistry, this study introduces a groundbreaking approach to activate elemental germanium via mechanical force, facilitating the Reformatsky reaction without the reliance on external reducing agents. Meanwhile, we have also demonstrated, for the first time, the catalytic activity of elemental germanium, successfully achieving this through the bromoalkylation of alkenes. These achievements mark a significant advancement in the field of catalysis and open up a new promising avenue for both academic research and industrial applications.

Elemental Germanium Activation and Catalysis Enabled by Mechanical Force

In the realm of materials science and chemical industry, germanium emerges as a strategic resource with distinctive properties that extend its applicability beyond traditional electronics and optics into the promising field of chemical catalysis. Despite its significant role in advanced technological applications, the potential of elemental germanium as a catalyst remains unexplored. Leveraging recent developments in mechanochemistry, this study introduces a groundbreaking approach to activate elemental germanium via mechanical force, facilitating the Reformatsky reaction without the reliance on external reducing agents. Meanwhile, we have also demonstrated, for the first time, the catalytic activity of elemental germanium, successfully achieving this through the bromoalkylation of alkenes. These achievements mark a significant advancement in the field of catalysis and open up a new promising avenue for both academic research and industrial applications.

Development of Thermoplastic Bi-Component Electrodes for Triboelectric Impact Detection in Smart Textile Applications

Smart textiles provide a significant technological advancement, but their development must balance traditional textile properties with electronic features. To address this challenge, this study introduces a flexible, electrically conductive composite material that can be fabricated using a continuous bi-component extrusion process, making it ideal for sensor electrodes. The primary aim was to create a composite for the filament’s core, combining multi-walled carbon nanotubes (MWCNTs), polypropylene (PP), and thermoplastic elastomer (TPE), optimised for conductivity and flexibility. This blend, suitable for bi-component extrusion processes, exemplifies the role of advanced materials in combining electrical conductivity, mechanical flexibility, and processability, which are essential for wearable technology. The composite optimisation balanced MWCNT (2.5, 5, 7.5, and 10 wt.%) and TPE (0, 25, and 50 wt.%) in a PP matrix. There was a significant decrease in electrical resistivity between 2.5 and 5 wt.% MWCNT, with electrical resistivity ranging from (7.64 ± 4.03)104 to (1.15 ± 0.10)10−1 Ω·m. Combining the composite with 25 wt.% TPE improved the flexibility, while with 50 wt.% TPE decreased tensile strength and hindered the masterbatch pelletising process. The final stage involved laminating the composite filament electrodes, with a 5 wt.% MWCNT/PP/(25 wt.% TPE) core and a TPE sheath, into a textile triboelectric impact detection sensor. This sensor, responding to contact and separation, produced an output voltage of approximately 5 V peak-to-peak per filament and 15 V peak-to-peak with five filaments under a 100 N force over 78.54 cm2. This preliminary study demonstrates an innovative approach to enhance the flexibility of conductive materials for smart textile applications, enabling the development of triboelectric sensor electrodes with potential applications in impact detection, fall monitoring, and motion tracking.

Multi-Type Ship Target Detection in Complex Marine Background Based on YOLOv11

Realizing accurate control of ship target information in complex marine environments is of great significance for maintaining marine environment security and safeguarding maritime sovereignty. With the rapid development of material technology and manufacturing industry, the types and styles of ships are increasing, and the distribution of multi-type ships on the sea is widespread. How to realize the accurate detection and identification of dynamic multi-type ship targets in the complex marine environment is an important and difficult problem that needs to be solved urgently in current marine environment detection. In this paper, an improved YOLOv11 ship target detection algorithm is proposed, which firstly utilizes the improved EfficientNetv2 network to replace the original backbone network of YOLOv11 to improve the learning ability of ship features under complex sea conditions; in order to solve the problem of interference by moving objects at sea when detecting dense ship targets and reduce the problems of missing detection and false alarms, the algorithm borrows from ConvNext block idea in the process of a neck feature pyramid network fusion; the algorithm introduces the WIoU loss function, which compensates for the effect of the small number of pixels of the small target in the process of regression loss computation, so as to improve the network’s performance in detecting small targets. In order to test the network performance in actual application scenarios, the article builds a visible ship target dataset, including complex background, occlusion and overlap, small targets, and other factors. Through experimental verification, the detection accuracy of the improved algorithm is improved by 5.6% compared with the original algorithm, and compared with typical algorithms in terms of detection accuracy, speed, and number of parameters, ablation experiments are designed to comprehensively validate and analyze the algorithm’s performance.

Numerical Simulation of the Influence Mechanism of Melt Rate Variation on the Macrosegregation of 8Cr4Mo4V-Bearing Steel During Vacuum Arc Remelting

In this study, 8Cr4Mo4V steel was selected as the research material to develop a numerical model of the macrosegregation phenomenon during vacuum arc remelting (VAR). The accuracy of the model was validated by comparing it with the literature and experimental results. According to the simulation results, molten steel flows down along the solidification front, resulting in positive segregation at the center and negative segregation close to the edge of the ingot. Solute enrichment reduces the undercooling of the alloy system, which in turn decreases the local solidification rate and causes a slight increase in steady-state molten pool depth. Notably, as the molten pool depth increases, the temperature gradient decreases, while the local cooling rate remains nearly constant, which leads to an increase in the local solidification rate again. Consequently, the positive segregation degree at the ingot’s center is gradually alleviated, and the depth of the molten pool gradually decreases. Furthermore, macrosegregation in VAR ingots becomes pronounced with an increase in melt rate. The main reason for this is due to the increased molten pool depth when the melt rate is increasing, which strengthens fluid flow and accelerates the migration of solute elements to the center. Additionally, due to the increase in the extent of solute enrichment when the melt rate is increasing, the degree of fluctuation in both the steady-state molten pool depth and positive segregation increases.

Safety Assessment of Graphene-Based Materials.

Graphene is the first 2D atomic crystal, and its isolation heralded a new era in materials science with the emergence of several other atomically thin materials displaying multifunctional properties. The safety assessment of new materials is often something of an afterthought, but in the case of graphene, the initial isolation and characterization of the material was soon followed by the assessment of its potential impact on living systems. The Graphene Flagship project addressed the health and environmental aspects of graphene and other 2D materials, providing an instructive lesson in interdisciplinarity - from materials science to biology. Here, the outcomes of the toxicological and ecotoxicological studies performed on graphene and its derivatives, and the key lessons learned from this decade-long journey, are highlighted.

Dissecting the Molecular Structure of the Air/Ice Interface from Quantum Simulations of the Sum-Frequency Generation Spectrum.

Ice interfaces are pivotal in mediating key chemical and physical processes such as heterogeneous chemical reactions in the environment, ice nucleation, and cloud microphysics. At the ice surface, water molecules form a quasi-liquid layer (QLL) with properties distinct from those of the bulk. Despite numerous experimental and theoretical studies, a molecular-level understanding of the QLL has remained elusive. In this work, we use state-of-the-art quantum dynamics simulations with a realistic data-driven many-body potential to dissect the vibrational sum-frequency generation (vSFG) spectrum of the air/ice interface in terms of contributions arising from individual molecular layers, orientations, and hydrogen-bonding topologies that determine the QLL properties. The agreement between experimental and simulated spectra provides a realistic molecular picture of the evolution of the QLL as a function of the temperature without the need for empirical adjustments. The emergence of specific features in the experimental vSFG spectrum suggests that surface restructuring may occur at lower temperatures. This work not only underscores the critical role of many-body interactions and nuclear quantum effects in understanding ice surfaces but also provides a definitive molecular-level picture of the QLL, which plays a central role in multiphase and heterogeneous processes of relevance to a range of fields, including atmospheric chemistry, cryopreservation, and materials science.

Introduction of 2D materials heterostructures' properties

Since the successful fabrication and characterization of graphene, it has demonstrated many unprecedented exceptional properties, garnering extensive attention and research interest. Simultaneously, studies on graphene have propelled the development of research into other two-dimensional (2D) materials. Research in this field has achieved significant breakthroughs and rapid progress, establishing itself as a prominent focus in condensed matter physics and materials science. Initially, studies on 2D materials primarily concentrated on single-layer 2D materials. Later, researchers discovered that stacking two or more different 2D materials could also result in the formation of novel 2D materials, collectively referred to as 2D material heterostructures. 2D material heterostructures have attracted substantial interest in condensed matter physics and materials science due to their unique nanoscale properties. These heterostructures demonstrate remarkable optical and electronic characteristics, making them ideal candidates for the development of atomically thin devices. This review summarizes recent advancements in 2D material heterostructure research and explores potential future directions and developments in this rapidly evolving field

Dynamically reconfigurable acoustofluidic metasurface for subwavelength particle manipulation and assembly

Particle manipulation plays a pivotal role in scientific and technological domains such as materials science, physics, and the life sciences. Here, we present a dynamically reconfigurable acoustofluidic metasurface that enables precise trapping and positioning of microscale particles in fluidic environments. By harnessing acoustic-structure interaction in a passive membrane resonator array, we generate localized standing acoustic waves that can be reconfigured in real-time. The resulting radiation force allows for subwavelength manipulation and patterning of particles on the metasurface at individual and collective scales, with actuation frequencies below 2 MHz. We further demonstrate the capabilities of the reconfigurable metasurface in trapping and enriching beads and biological cells flowing in microfluidic channels, showcasing its potential in high-throughput bioanalytical applications. Our versatile and biocompatible particle manipulation platform is suitable for applications ranging from the assembly of colloidal particles to enrichment of rare cells.

Research and application of bionic robotic arms

The research on bionic robotic arms originates from the aspiration to imitate and replicate the structure and functions of the human arm. With advancements in technology, particularly in the rapid development of robotics, sensor technology, and materials science, robust technical support has been provided for the study of bionic robotic arms. Additionally, as people's demands for a higher quality of life increase, so does the need for mechanical devices that can undertake arduous, hazardous, or high-precision tasks in place of humans. Especially in fields such as industrial production, healthcare, and military security, the research and application of bionic robotic arms have become a focal point in today's technological landscape. This article presents a comprehensive overview of the research background, development trajectory, and future prospects of three specific areas: flexible robotic arms for confined space operations, bionic robotic arms for rotorcraft, and bionic jellyfish robotic arms. The aim is to provide theoretical support and technical references for research and engineering applications in related fields

Performance Assessment and Failure Mechanisms of Roller Bearings Using Dual Material Comparison

This study presented the performance and failure mechanisms of roller bearings for structural steel and AISI 52100 alloy steel under various operating conditions. It emphasizes how material properties affect stress, deformation, and thermal performance according to simulations carried out in ANSYS Workbench. Results clearly present that AISI 52100 alloy steel exhibits better strength against stress, dimensional stability, and thermal efficiency compared with structural steel. Key factors contributing to the bearing's failure included high tightening axial force, vibration, and temperature, with spalling and wear as the dominant modes of failure. The improvement in performance further came through dimensional changes reducing stress and deformation. The whole research highlights the need for attention to material selection and axial force control while designing roller bearings to be reliable and efficient. Findings of the present study may thus advocate for the use of AISI 52100 alloy steel in applications requiring high performance and durability. Future studies might look at advanced materials and optimized designs to further advance bearing reliability under demanding conditions.

Practical Value of Intensive Learning, use and Development of Communicative Skills for Students of Mathematics Based on Professional English Language

Research relevance: the article deals with the special application of methods and techniques that have shown their effectiveness in world practice for the successful implementation of professional communication of mathematicians-students in English. Research purpose: clarification in a practical context of the objective aspects need for methods to achieve the expected results in teaching English in the system of higher mathematical professional education in Kyrgyzstan. Research materials and methods: analysis of their influence on the development of the professional speech of mathematicians-students through the views of students who studied this question, and also the ways of verifying these methods in practice are proposed. The content of these methods is revealed in the article, taking into account public and social conditions. This is related to the task of preparing mathematicians-students for international competition by forming professional English language at the required level, and also demonstrates the content of methods used in practice with examples. Research results: on the basis of the proposed points, a number of problems in teaching English in the field of professional education and mathematics are highlighted. Conclusions: a comprehensive approach is required to improve the teaching of English in mathematics.

Research Related to Turbofan Engines

The development of aerospace technology has become a topic of daily concern and discussion for the benefit of all mankind. As the global temperature rises, the living environment of human beings is threatened, and scientists have decided to work on the development of aerospace technology in order to solve this problem and meet people's needs. Looking at the aviation industry, which is currently accessible to most people, aviation scientists are focusing on aircraft engines. There are different types of engines such as turbojet engines, turbofan engines, paddle fan engines and so on, but the type of engine that meets the needs of most people today is the turbofan engine. This paper introduced the basic information of turbofan engine in the context of literature, for example, the characteristics of turbofan engine such as high efficiency, high thrust, low noise, high reliability, and the problem of durability of high-temperature components that it faces, which can be improved from the research and development of advanced materials and innovative cooling technology

The design space of E(3)-equivariant atom-centred interatomic potentials

Abstract Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time. Here we construct a mathematical framework that unifies these models: atomic cluster expansion is extended and recast as one layer of a multi-layer architecture, while the linearized version of NequIP is understood as a particular sparsification of a much larger polynomial model. Our framework also provides a practical tool for systematically probing different choices in this unified design space. An ablation study of NequIP, via a set of experiments looking at in- and out-of-domain accuracy and smooth extrapolation very far from the training data, sheds some light on which design choices are critical to achieving high accuracy. A much-simplified version of NequIP, which we call BOTnet (for body-ordered tensor network), has an interpretable architecture and maintains its accuracy on benchmark datasets.

Recent advances on support materials for enhanced Pt-based catalysts: applications in oxygen reduction reactions for electrochemical energy storage

Abstract As the demand for sustainable energy solutions grows, developing efficient energy conversion and storage technologies, such as fuel cells and metal-air batteries, is vital. Oxygen Reduction Reaction (ORR) is a significant limitation in electrochemical systems due to its slower kinetics. Although Pt-based catalysts are commonly used to address this challenge, their high cost and suboptimal performance remain significant obstacles to further development. This review offers a comprehensive overview of advanced support materials aimed at improving the efficiency, durability, and cost-effectiveness of Pt-based catalysts. By examining a range of materials, including mesoporous carbon, graphene, carbon nanotubes, and metal oxides, the review clarifies the relationship between the structural properties of these supports and their influence on ORR performance. Additionally, it discusses the fundamental characteristics of these materials, their practical applications in fuel cells, and explores potential solutions and future directions for optimizing Pt-based catalysts to advance sustainable energy conversion technologies. Future research could focus on nano-engineering and composite material development to unlock the full potential of Pt-based catalysts, significantly enhancing their economic viability and performance in energy applications.

Design and Energy Absorption Study of an Asymmetric Windmill‐Style Negative Poisson's Ratio Honeycomb Structures

The negative Poisson's ratio (NPR) structure, as one of the representatives of advanced lightweight honeycomb materials, has good application prospects in aerospace, vehicles, biomedical, and other fields due to its unique deformation mechanism and huge energy absorption potential. In this article, a 2D asymmetric windmill‐style composite honeycomb (AWH) with NPR effects is presented and its compression properties are systematically assessed using both axial compression experiments and simulations. Through the experimental results, the accuracy and applicability of the finite‐element model are verified, indicating that the shape of the rotating arrangement and the stable internal design of the triangle make it have significantly higher energy absorption capacity than traditional symmetric reentrant honeycomb structures. In addition, the influence of the height, width, and cell spacing of asymmetric unit cell indentation points on the compression characteristics of AWH under axial quasi‐static compression conditions is further analyzed through orthogonal simulation experiments. In this study, a certain theoretical basis for the design and energy absorption application of NPR materials is provided, indicating that AWH has excellent mechanical properties and broad application prospects.