Optimal Material Design Research Articles

Synthesis of the Solar Selective Material CuFeMnO4 by Solid Phase and Co-Precipitation

This study meticulously explores two distinct synthesis methods, the solid-state reaction method and the co-precipitation method, for fabricating the spinel-structured solar selective material CuFeMnO4. By comparing the materials synthesized through these two methods in terms of crystal structure, micro-morphology, particle size distribution, and optical properties, the influence of different preparation methods on the final material performance is revealed. The primary characterization through X-ray diffraction (XRD), scanning electron microscopy (SEM), and UV-Vis spectroscopy revealed the material’s structural and optical properties, allowing evaluation of the modified synthetic approach’s effectiveness in material design optimization. The results indicate that CuFeMnO4 prepared by the solid-state method exhibits high crystallinity and good thermal stability under high-temperature conditions. The XRD patterns show that the spinel phase is more prominent and fewer impurities are observed in samples synthesized by the solid-state method. In contrast, the co-precipitation method demonstrates a significant advantage in controlling particle size, with particles of 1–3 μm obtained via the solid-state method and particles of 400–1000 nm synthesized via the co-precipitation method. This study further discusses optimization strategies for both methods, providing theoretical support and a practical basis for the future design and fabrication of efficient solar selective materials.

Progress in Plastic Work–Heat Conversion of Metallic Crystals

The Taylor–Quinney coefficient (TQC) is a critical parameter quantifying the thermal conversion of plastic work during deformation in metallic crystals. This review provides a comprehensive summary of recent advances in TQC research, spanning experimental, theoretical, and computational perspectives. The fundamental principles of the TQC are introduced, emphasizing its thermodynamic background and dependence on microstructural features. Experimental studies demonstrate how the strain rate, temperature, and microstructure influence the TQC, with advanced techniques such as infrared thermography and high-speed imaging enabling precise measurements under dynamic conditions. Theoretical models, including internal variable frameworks and nonequilibrium thermodynamics, offer insights into the energy distribution mechanisms and provide predictive capabilities across diverse loading scenarios. Computational simulations, using methods like finite element analysis and molecular dynamics, reveal multiscale thermal conversion mechanisms and the role of dislocation motion and localized heat accumulation in governing TQC values. Challenges and opportunities for TQC research are highlighted, including the need for multiscale modeling, the exploration of complex stress states, and applications under extreme environments. Future directions should focus on integrating advanced experimental techniques and computational models to optimize material design and performance. This review aims to deepen the understanding of the TQC and its implications for energy dissipation and material reliability in high-performance applications.

Advances in the application and research of biomaterials in promoting bone repair and regeneration through immune modulation.

Advances in the application and research of biomaterials in promoting bone repair and regeneration through immune modulation.

Review—Recent Progress in Materials Development for Electrochemical Gas Sensors

Abstract Gas sensors are critical in detecting various gases across industrial, environmental, and healthcare applications. Among them, electrochemical gas sensors stand out due to their high sensitivity, selectivity, and portability. However, traditional electrochemical gas sensors have faced limitations regarding long-term stability and the ability to detect gases at low concentrations. This review paper explores the emerging materials and innovative approaches that promise to address these challenges and enhance sensor performance. The unique properties of novel materials, including metal and metal oxides, carbon materials, conducting polymers, their composites, and others, are discussed in detail. These materials exhibit vital features such as high surface area, enhanced conductivity, and improved gas adsorption capabilities, which are crucial for developing advanced electrochemical gas sensors. Our review emphasizes the critical relationship between material properties and sensing mechanisms, offering insights into optimal material selection and design strategies. In addition to the materials aspect, we also cover many advanced electrochemical techniques, including electrode design enhancements, surface functionalization strategies, and innovative electrolytes like ionic liquids and polymer electrolytes. Overall, this comprehensive overview of state-of-the-art developments in electrochemical gas sensing highlights the potential for transformative applications across diverse fields and emphasizes the importance of interdisciplinary collaboration to drive future innovations.

Highly Elastic Spongelike Hydrogels for Impedance-Based Multimodal Sensing.

Hydrogel-based sensors have been widely studied for perceiving the environment. However, the simplest type of resistive sensors still lacks sensitivity to localized strain and other extractable data. Enhancing their sensitivity and expanding their functionality to perceive multiple stimuli simultaneously are highly beneficial yet require optimal material design and proper testing methods. Herein, we report a highly elastic, sponge-like hydrogel and its derived multimodal iontronic sensor. By unidirectional freeze casting of poly(vinyl alcohol) (PVA) with electrospun cellulose nanofibers (CNF), a hierarchical structure with aligned PVA channels supported by interlaced CNF tangles is created. The structure ensures both efficient mass transport and good elasticity, enhancing reversible compressibility and ionic conductivity. Combining this sponge hydrogel with impedance-based measurement methods allows the development of multimodal sensors capable of detecting local strain, position, and material type of object-in-contact. Integrating these sensing capabilities, a two-dimensional small motion monitor, a 3D input interface, and a material identification gripper are demonstrated. This study provides a simple approach to versatile multimodal sensors.

Optimal Design and Simulation Analysis of Phase Change Material Composite Self-Insulating Block in a Typical Cold Region City of China in Summer

Background:: Incorporating PCMs (Phase Change Materials) into the building envelope can achieve the purpose of regulating heat transfer and enhancing indoor comfort. In recent years, lots of patents for new phase change concretes have been proposed and applied to the envelope. Objective:: This study aimed to explore the optimum phase change temperature and installation position of PCM by optimizing different concrete blocks to improve the thermal behavior of concrete compound self-insulating blocks. Methods:: Firstly, based on the existing patents, five new types of phase change self-insulating blocks were proposed. The thermal insulation performance of different blocks was tested using ANSYS simulation. Then, the feasibility of using EnergyPlus to simulate the thermal environment of the room was verified by taking a summer south-facing room in Hohhot City as a research object. Finally, 13 phase-change block types containing 4 phase-change temperatures and 3 PCM installation locations were designed for further testing. Results:: A three-row staggered perforated block was selected, and the heat transmission coefficient of the masonry wall was 0.437 W/(m2·K). The optimal phase change temperatures of outdoor, medium- temperature, high-temperature, and low-temperature periods in summer, were 24.0oC, 30.0oC, and 28.0oC, respectively. The optimal phase change temperature in the whole summer was 26.0~ 28.0oC, and the best phase transition layer location was the inner hole of the block. Conclusion:: The PCM mounting position has a greater effect on room temperature than the PCM phase change temperature. The study results are of great significance for stabilizing room temperature and building energy conservation.

Modulating Mn-doped NiO nanoparticles: structural, optical, and electrical property tailoring for enhanced hole transport layers.

Mn-doped NiO nanoparticles (NPs), denoted as Ni1-x Mn x O with x values of 0.00, 0.02, 0.04, 0.06, and 0.08, were synthesized using a chemical precipitation process. These NPs were comprehensively analyzed for their structural, optical, and electrical properties, along with their surface morphology and elemental composition. X-ray Diffraction (XRD) confirmed the single-phase cubic crystal structure and revealed a reduction in crystallite size from 15.26 nm to 10.38 nm as Mn doping increased. Field Emission Scanning Electron microscopy (FE-SEM) determined the average particle sizes ranging from 26.03 nm to 23.30 nm. The optical properties, assessed by UV-visible spectroscopy (UV-vis), revealed a widening of the bandgap from 3.49 eV to 4.10 eV with increasing Mn doping, suggesting tunable optical characteristics. X-ray Photoelectron Spectroscopy (XPS) confirmed the presence of nickel (Ni), oxygen (O), and manganese (Mn) within the NPs. The highest mobility, 1.31 ± 0.03 × 103 cm2 V-1 s-1, was observed in the 6 wt% Mn-doped NiO NPs thin film, as determined by Hall measurements. To assess their practical utility, SCAPS-1D simulation was employed, demonstrating the potential of Mn-doped NiO NPs as a hole transport layer (HTL) in perovskite solar cells (PSCs). The enhanced electrical and optical properties, combined with structural tunability, highlight Mn-doped NiO as a promising material for advanced optoelectronic applications. This study provides valuable insights into the development of efficient and stable solar cells, offering a pathway to optimize material design for improved performance in photovoltaic applications.

A Numerical Approach to Predict the Flexural Response of Simply Supported Nonhomogeneous and Non-Slender Graded Beams

In recent years, one promising avenue to optimize material design is the development of functionally graded materials (FGMs), which represent a new generation of composites with tailored mechanical properties. These properties vary continuously according to a function-law, allowing FGMs to mitigate issues like interfacial debonding and stress concentration. Accordingly, this study focuses on simulating the mechanical behavior of simply supported FGM non-slender beams under bending using finite element modeling (FEM). The numerical procedure and the loading setup as well as the implementation the power-law function which governs the stiffness distribution of the used metal and ceramic materials are explicitly presented. In addition, an optimal mesh size is determined for the modeled FGM beams. The numerical results show the effect of material exponent index and beam span ration on displacements and stresses distributions. The validated FEM-tool developed in this work provides a reliable means for estimating the elastic flexural response of non-slender graded beams under bending.

OBTAINING AND TESTING OF MG-CA-SR BIODEGRADABLE MATERIALS USED IN MEDICINE

Biodegradable magnesium (Mg), calcium (Ca), and strontium (Sr) alloys have garnered significant interest in regenerative medicine due to their unique mechanical properties, biocompatibility, and controlled degradation combination. These materials are particularly promising for temporary implants, such as orthopedic screws, plates, and cardiovascular stents, as they eliminate the need for secondary surgical removal and provide osteogenic benefits through the release of bioactive ions. Despite their potential, the clinical implementation of Mg-Ca-Sr alloys faces several challenges, including precise control of degradation rates to match tissue healing, optimization of biocompatibility to prevent inflammatory responses, and addressing the complexities of industrial production for consistent quality and performance. Future research directions focus on employing advanced technologies like nano-engineering and 3D printing to tailor the properties of these alloys for specific applications. Long-term in vivo studies are critical for understanding their behavior in biological environments while combining these alloys with ceramics or polymers could create hybrid materials with enhanced mechanical strength and degradation control. Additionally, artificial intelligence offers opportunities to optimize material design and predict clinical outcomes. Mg-Ca-Sr alloys are promising to transform the landscape of biodegradable implants, address current limitations, and improve patient outcomes through innovative materials and fabrication techniques.

Optimal design and experimentation of full tailings and cementitious materials: a case study of a lead-zinc mine in China

As mineral resources become increasingly scarce and environmental awareness grows, mining companies urgently need cost-effective and environmentally friendly filling methods for mines. The use of ultrafine tailings combined with various binders at different ratios plays a key role in determining the rheological properties and mechanical strength of cemented paste backfill. This paper provides parameter basis for the design of a mine filling system, firstly, different filling materials and proportions were selected, and basic physicochemical property tests, along with cementitious material analysis, were conducted to determine the key physical and chemical properties and mineral composition of the materials. Next, the rheological properties, transport performance, and bleeding characteristics of the filling slurry were tested to assess the feasibility and process requirements for self-flow transport through pipelines. The results indicated that the transportation performance of the slurry was better when gelling powder was used as the binder. Finally, the compressive, shear, and tensile strengths of the filling blocks were tested under varying slurry mass concentrations and cement-tailings ratios at different curing times. This helped identify the optimal filling concentration and proportions needed to meet the strength requirements of the filling structure. The final study found that the sample with a cement-tailings ratio of 1:6, a mass concentration of 68%, and a gelling powder as the binder reached the strength requirements for mine filling after 28 days. This research offers valuable insights for other mining companies seeking to implement similar environmentally sustainable and cost-effective filling technologies, promoting wider adoption and advancements in the field.

Thermal expansion of boron nitride nanotubes and additively manufactured ceramic nanocomposites

Controlling the thermal expansion of ceramic materials is important for many of their applications that involve high-temperature processing and/or working conditions. In this study, we investigate the thermal expansion properties of additively manufactured alumina that is reinforced with boron nitride nanotubes (BNNTs) over a broad temperature range, from room temperature to 900 °C. The coefficient of thermal expansion (CTE) of the BNNT-alumina nanocomposite increases with temperature but decreases with an increase in BNNT loading. The introduction of 0.6% BNNTs results in an approximate 16% reduction in the CTE of alumina. The observed significant CTE reduction of ceramics is attributed to the BNNT's low CTE and ultrahigh Young's modulus, and effective interfacial load transfer at the BNNT-ceramic interface. Micromechanical analysis, based onin situRaman measurements, reveals the transition of thermal-expansion-induced interface straining of nanotubes, which shifts from compression to tension inside the ceramic matrix under thermal loadings. This study provides valuable insights into the thermomechanical behavior of BNNT-reinforced ceramic nanocomposites and contributes to the optimal design of ceramic materials with tunable and zero CTE.

Comparative analysis of direct search methods for material design optimization

This paper contributes to the field of optimization for periodic composite material design by systematically evaluating the performance of four direct search algorithms: greedy, simulated annealing (SA), genetic algorithms (GA), and particle swarm optimization (PSO). The central goal is to determine the optimal arrangement of two material domains inside a representative volume element (RVE) while respecting the constraint that half volume of the domains is composed of a specific material, with the effective shear modulus as the objective function. The main contribution of this work is the detailed comparison of these algorithms in terms of success rates and computational efficiency, providing critical insights into their suitability for different problem scales. For a small-scale problem (16 cells), PSO achieves a 100% success rate, while SA demonstrates over 90% success but at a higher computational cost. The greedy algorithm, despite its simplicity, achieves a 72% success rate with the lowest computational effort, requiring an average of 256 objective function evaluations. GA, however, exhibits the lowest success rate at 52% and requires the highest average number of evaluations (5003.2). Furthermore, the paper extends the analysis to a more complex problem (36 cells), where the adaptability and efficiency of the algorithms are tested. This investigation highlights the trade-offs between algorithmic complexity, success rate, and computational cost, offering practical guidelines for selecting suitable optimization methods based on problem size and characteristics.

Paradigm on Levenberg–Marquardt neural algorithm analysis of heat conduction optimization for ternary hybrid nanofluid with entropy generation

AbstractThe significance of the present article is to enhance the thermal management and energy efficiency of complex engineering infrastructures such as energy storage systems, modern electric vehicles, thermal insulations, heavy‐duty machinery, and production units. This research aims to understand the intricate relationship between the thermal conductivity performance of ternary () hybrid nanomaterial and entropy generation to optimize material design and efficacy. A synergetic combination of three distinct nanomaterials silicon dioxide, ferric oxide, and titanium oxide with ethylene glycol and water in the ratio 3:2 as a base solvent is comprised of contributing unique thermophysical properties. To elucidate the impact of this hybrid composition on thermal conductivity, various factors are analyzed. The advanced computational technique of Artificial intelligent feed‐forward neural network (AIFFNN) is utilized. The problem governed the system of PDEs, which is transformed into ODEs by dimensionless similarity. Adams method provided the dataset which is filtered and embedded into Marquardt–Levenberg Algorithm (LMA). The study examines the role of nanomaterial constituents, morphology, and boundary conditions on thermal performance and entropy generation. Graphical analysis of velocity, temperature, and entropy is provided with respect to varying parameters, including surface absorption (λ), magnetic strength (Tesla M), radiation parameter (Rd), Brownian motion (Br), and Eckert number (Ec). The findings have practical significance for optimizing material design in engineering and industrial applications.

Designing Contact Independent High-Performance Low-Cost Flexible Electronics.

Organic semiconductors enable low-cost solution processing of optoelectronic devices on flexible substrates. Their use in contemporary applications, however, is sparse due to persistent challenges in achieving the requisite performance levels in a reliable and reproducible manner. A critical bottleneck is the inefficiency associated with charge injection. Here, large-scale simulations are employed to identify operational windows where key device parameters that are difficult to control experimentally, such as the contact resistance, become less consequential to overall device functionality. This design methodology overcomes injection barrier limitations in organic field-effect transistors (OFETs), leading to high charge carrier mobility and significantly expanding the range of suitable electrode materials. Leveraging this new understanding, all-organic, solution-deposited OFETs are successfully fabricated on flexible substrates. These devices incorporate printed contacts and showcase mobilities exceeding 5cm2Vs-1. These results provide a route for accessing the fundamental limits of material properties even in the absence of ideal contacts - a critical step in establishing reliable structure/property relationships and optimal material design paradigms. While reducing the injection barrier and contact resistance remains critical for achieving high OFET performance, this work demonstrates a path toward consistently achieving high charge carrier mobility through device geometry design, ultimately reducing processing complexity and cost.

A multi-scale modeling method for tensile properties of strain-hardening cementitious composites

A multi-scale modeling method for tensile properties of strain-hardening cementitious composites

Thermophysical Investigation of Multiform NiO Nanowalls@carbon Foam/1-Octadecanol Composite Phase Change Materials for Thermal Management.

Multiform NiO nanowalls with a high specific surface area were constructed in situ on carbon foam (CF) to construct NiO@CF/OD composite phase change materials (CPCMs). The synthesis mechanism, microstructures, thermal management capability, and photothermal conversion of NiO@CF/OD CPCMs were systematically studied. Additionally, the collaborative enhancement effects of CF and multiform NiO nanowalls on the thermal properties of OD PCMs were also investigated. NiO@CF not only maintains the porous 3D network structure of CF, but also effectively prevents the aggregation of NiO nanosheets. The chemical structures of NiO@CF/OD CPCMs were analyzed using XRD and FTIR spectroscopy. When combined with CF and NiO nanosheets, OD has high compatibility with NiO@CF. The thermal conductivity of NiO@CF/OD-L CPCMs was 1.12 W/m·K, which is 366.7% higher than that of OD. The improvement in thermal conductivity of CPCMs was theoretically analyzed according to the Debye model. NiO@CF/OD-L CPCMs have a photothermal conversion efficiency up to 77.6%. This article provided a theoretical basis for the optimal design and performance prediction of thermal storage materials and systems.

Structural properties and mechanical responses of geopolymer pore models under chloride exposure: Molecular dynamics simulation

Structural properties and mechanical responses of geopolymer pore models under chloride exposure: Molecular dynamics simulation

A recycled crushed rock sand mortar based on Talbot grading theory: Correlation of pore structure and mechanical properties

A recycled crushed rock sand mortar based on Talbot grading theory: Correlation of pore structure and mechanical properties

Hierarchically porous carbon foams coated with carbon nitride: Insights into adsorbents for pre-combustion and post-combustion CO2 separation

Hierarchically porous carbon foams coated with carbon nitride: Insights into adsorbents for pre-combustion and post-combustion CO2 separation

Optimal design and thermal performance evaluation of phase change material filling position for solar air collectors

Optimal design and thermal performance evaluation of phase change material filling position for solar air collectors