Hasil untuk "Materials of engineering and construction. Mechanics of materials"

Bin Liu, Yafan Hu, Kai Xu et al.

Anoj Aryal, Weiyi Gong, Huta Banjade et al.

Machine learning models for functional materials design require precise and informative representations of material systems. Common representations encode atomic composition and bonding but often do not include local coordination environments across chemically diverse crystals. Recurring structural motifs provide a motif level description of crystalline solids and can serve as interpretable descriptors for structure property learning. To analyze the motif connectivity in materials, we construct a bipartite material motif network from 131,548 Materials Project entries, with materials and motifs as the two node sets. Edges connect materials to their constituent motifs and are weighted by motif distortion, which quantifies the strength of each material motif association. Network connectivity is analyzed to identify motif-defined material clusters that capture recurring local geometries relevant to structure property trends. Most shared motifs act as hubs that connect otherwise disconnected regions of the network, enabling motif guided screening by expanding from known motifs to nearby materials in the same neighborhoods. A network embedding step converts this weighted connectivity into vector representations of materials. Using these motif informed embeddings, property prediction yields a formation energy mean absolute error (MAE) of 0.157 eV per atom and a bandgap MAE of 0.601 eV. These results indicate that motif connectivity provides a compact, interpretable representation that complements existing descriptors for scalable screening and structure property modeling.

Yixue Zhang, Yiannis Pontikes, Jo Van Caneghem et al.

Juliane Fjelrad Christfort, Matteo Tollemeto, Yudong Li et al.

Oral drug delivery remains the most preferred administration route, and new oral delivery concepts continuously arise to enable oral delivery of new therapeutics. This study investigates how colloidal structures in five simulated intestinal fluids (SIFs) with varying bile salt and phospholipid compositions influence drug solubility, nanoparticle aggregation and cytotoxicity, and mucoadhesion of nanoparticles and polymers. For the poorly water‐soluble drugs indomethacin and felodipine, colloidal structure size in SIFs varies with solubility, and felodipine's solubility is influenced by the lipid composition. Nanoparticles, including polymersomes and mesoporous silica nanoparticles with different surface charges, are characterized in each medium. Dynamic light scattering reveals three interaction modalities: interaction, aggregation, and combination, depending on nanoparticle type and fluid composition. Additionally, interaction patterns correlate with Caco‐2 cell cytotoxicity. Quartz crystal microbalance with dissipation analysis reveals that both particle and polymer interactions with mucin are significantly altered in SIFs. For nanoparticles, mucin interactions differ depending on the type of nanoparticle. For the polymers, polyethylene oxide completely loses mucin interaction in SIFs, while chitosan retains partial mucoadhesion. These findings emphasize the importance of not only studying drug properties, but also cell compatibility and mucoadhesion of polymers and nanoparticles, in physiologically relevant conditions.

Skye Supakul, Ishtiaque Robin, Eda Aydogan et al.

Recently, compositionally complex alloys (CCAs) have been proposed as material candidates for extreme environments, such as for fission or fusion. To explore low activation designed W-Ti-based CCA systems, two new nanocrystalline CCA thin films were synthesized. Single-phase BCC ternary W–Ti–V and quaternary W–Ti–Cr–V CCAs were subjected to in-situ heating and dual-beam ion irradiation investigations at 900 °C. After exposure to 900 °C with and without ion irradiation both systems exhibited negligible grain growth. Small (≤ 1 nm) cavities distributed throughout the film were observed with no radiation induced loop formation post dual-beam ion irradiation up to ∼ 13 dpa. These responses are in excellent agreement with atomistic modeling. Compared to other candidate material systems, these systems possess impressive thermal stabilities and irradiation resistances, while serving as low activation alternatives to W–Ta–based compositionally complex alloys for extreme environments.

S. -Y. Zhang, J. Tian, S. -L. Liu et al.

Designing high-performance amorphous alloys is demanding for various applications. But this process intensively relies on empirical laws and unlimited attempts. The high-cost and low-efficiency nature of the traditional strategies prevents effective sampling in the enormous material space. Here, we propose material networks to accelerate the discovery of binary and ternary amorphous alloys. The network topologies reveal hidden material candidates that were obscured by traditional tabular data representations. By scrutinizing the amorphous alloys synthesized in different years, we construct dynamical material networks to track the history of the alloy discovery. We find that some innovative materials designed in the past were encoded in the networks, demonstrating their predictive power in guiding new alloy design. These material networks show physical similarities with several real-world networks in our daily lives. Our findings pave a new way for intelligent materials design, especially for complex alloys.

Yong YANG, Jiajia CHEN, Songyan LIU et al.

Objectives: With the development of modern processing technology, heat accumulation has become an urgent processing problem that needs to be solved. A heat pipe is a heat exchange element that efficiently transfers heat through the gas-liquid phase change of the working fluid inside the pipe. Gravity heat pipe have advantages such as simple structure, stable operation, and low cost, and are widely used in various heat exchange scenarios in industrial production. They have played a significant role in energy conservation, the development and utilization of new energy, and in strengthening heat exchange during processing. This article prensents experimental research on diamond nanofluids, exploring the influence of different parameters on the heat transfer performance of diamond nanofluid gravity heat pipes, laying a foundation for the research and application of heat pipe technology in heat dissipation during machining processes such as drilling, milling, and grinding. Methods: The evaporation section is heated using a DC power supply and thermal resistance wire. K-type thermocouples and temperature acquisition cards are used to record the temperature of the evaporation and condensation sections of the gravity heat pipe. The influence of heating power, filling rate, nanofluid concentration, and nanoparticle size on the heat transfer performance of the gravity heat pipe is analyzed using thermal resistance R as an indicator. Results: The heat transfer performance of gravity heat pipes is investigated under a power range of 3-18 W, while maintaining a filling rate of 20% and a nanoparticle concentration of 1%. The results show that as the heating power increases, the temperatures of the evaporation and the condensation sections gradually increase, while the rise time gradually shortenes. The temperature difference between the evaporation and condensation sections shows a decreasing trend. When the heating power increases for the same concentration and filling rate of nanoparticles, the total thermal resistance shows a decreasing trend, but the magnitude of the decrease continues to decrease. Keeping the concentration of nanoparticles at 2% and the heating power at 6 W, the heat transfer performance of gravity heat pipes is investigated under conditions of filling rates of 8%, 14%, 20%, and 26%. The results show that the overall temperature of the 20 nm diamond nanofluid is higher than those of other filling rates at a 20% filling rate, while the overall temperature at a 26% filling rate is lower than at other filling rates. The overall temperature at a 26% filling rate is higher than at other filling rates. With the same mass fraction and heating power, as the filling rate increases, the total thermal resistance shows a trend of first decreasing and then increasing, with the minimum value of the total thermal resistance appearing at a filling rate of 14%. By maintaining a filling rate of 26% and a heating power of 12 W, the heat transfer performance of gravity heat pipes under 0.5%, 1.0%, 1.5%, and 2.0% mass fraction conditions is investigated. The results show that the overall temperature of 20 nm diamond nanofluid heat pipes is the highest at a 1% mass fraction, while the overall temperature is lower at a 2.0% mass fraction. The hot-end temperature of 50 nm diamond nanofluid heat pipes is the highest at a 1.5% mass fraction, and the cold-end temperature is the lowest. At a mass fraction of 2.0%, there is a situation where the hot-end temperature is lower and the cold-end temperature is higher. With the same filling rate and heating power, as the mass fraction increases, the total thermal resistance first increases and then decreases. At a mass fraction of 2.0%, the minimum total thermal resistance will appears. In addition, for diamond nanofluids with different particle sizes, there is a trend of heat transfer capacity decreasing first and then improving with increasing mass fraction. Maintaining a filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with particle sizes of 20 nm and 50 nm was investigated. The total thermal resistance of 50 nm diamond nanofluid gravity heat pipes was always lower than that of 20 nm diamond nanofluid gravity heat pipes. However, as the heating power increases, the advantage of 50 nm diamond nanofluid gravity heat pipes tends to weaken. Maintaining a liquid filling rate of 14% and a mass fraction of 2.0%, the heat transfer performance of gravity heat pipes with and without a liquid absorbing core was investigated. The total thermal resistance of gravity heat pipes with suction cores is lower than that of heat pipes without suction cores, but as the heating power increases, the advantage tends to weaken. Conclusions: When the mass fraction is 2.0%, gravity heat pipes have the best heat transfer performance, with a total thermal resistance increase of approximately 28.4%-64.7% compared to the maximum value. When the filling rate is 14%, the heat transfer performance is the best, and the total thermal resistance decreases by about 6.1%-8.5% compared to the maximum value. When using diamond nanofluids with a particle size of 50 nm, the overall heat transfer performance of gravity heat pipes is better than that of 20 nm. When the heating power of the power supply increases, the heat exchange performance also improves. When using a gravity heat pipe with a liquid absorbing core, its overall heat transfer performance is better than that of a gravity heat pipe without a liquid absorbing core.

Tianyuan Zhu, Liyang Ma, Shiqing Deng et al.

Abstract Since the first report of ferroelectricity in nanoscale HfO2-based thin films in 2011, this silicon-compatible binary oxide has quickly garnered intense interest in academia and industry, and continues to do so. Despite its deceivingly simple chemical composition, the ferroelectric physics supported by HfO2 is remarkably complex, arguably rivaling that of perovskite ferroelectrics. Computational investigations, especially those utilizing first-principles density functional theory (DFT), have significantly advanced our understanding of the nature of ferroelectricity in these thin films. In this review, we provide an in-depth discussion of the computational efforts to understand ferroelectric hafnia, comparing various metastable polar phases and examining the critical factors necessary for their stabilization. The intricate nature of HfO2 is intimately related to the complex interplay among diverse structural polymorphs, dopants and their charge-compensating oxygen vacancies, and unconventional switching mechanisms of domains and domain walls, which can sometimes yield conflicting theoretical predictions and theoretical-experimental discrepancies. We also discuss opportunities enabled by machine-learning-assisted molecular dynamics and phase-field simulations to go beyond DFT modeling, probing the dynamical properties of ferroelectric HfO2 and tackling pressing issues such as high coercive fields.

Shuhua Xiong, Shungen Zhao, Dikuan Wang et al.

High Modulus Asphalt Mixtures (HMAM) have gained widespread utilization in asphalt pavement construction. It is great critical to study the fatigue characteristics of HMAM. At present, various fatigue test methods are employed in indoor testing to assess HMAM under different mechanical states. Therefore, there is a critical problem that the value of fatigue parameters is not unique in the structural design of HMAM. In this study, three fatigue testing methods were initially used to address the above issues: direct tensile testing, indirect tensile testing, and uniaxial compression testing. These tests help to determine the strength yield surface states at different loading rates. And to reveal the effect of loading rate on the mechanical behavior of HMAM. The results show a power function fit and a good correlation between strength and loading rate. The relationship models of strength with speed for indirect tensile, direct tensile and uniaxial compression tests are SI=3.22(v)0.14, SD=3.22(v)0.15 and SU=3.22(v)0.12, respectively.The higher the loading rate for the three fatigue test results, the greater the expansion of the strength yield surface.The fatigue life (Nf) of HMAM underwent testing, yielding its fatigue effective stress ratio. The relationship between the two was and then established. It is found that the point (1, 1) appears on the backextension line, thus effectively complementing the conventional S-N equation. In addition, the fatigue equations for various fatigue test methods were unified based on effective stress strength ratio and the fatigue life. This paper introduces a novel method for the antifatigue design of HMAM.

Aswathi K. Sivan, Begoña Abad, Tommaso Albrigi et al.

The possibility to tune the functional properties of nanomaterials is key to their technological applications. Superlattices, i.e., periodic repetitions of two or more materials in different dimensions are being explored for their potential as materials with tailor-made properties. Meanwhile, nanowires offer a myriad of possibilities to engineer systems at the nanoscale, as well as to combine materials which cannot be put together in conventional heterostructures due to the lattice mismatch. In this work, we investigate GaAs/GaP superlattices embedded in GaP nanowires and demonstrate the tunability of their phononic and optoelectronic properties by inelastic light scattering experiments corroborated by ab initio calculations. We observe clear modifications in the dispersion relation for both acoustic and optical phonons in the superlattices nanowires. We find that by controlling the superlattice periodicity we can achieve tunability of the phonon frequencies. We also performed wavelength-dependent Raman microscopy on GaAs/GaP superlattice nanowires and our results indicate a reduction in the electronic bandgap in the superlattice compared to the bulk counterpart. All our experimental results are rationalized with the help of ab initio density functional perturbation theory (DFPT) calculations. This work sheds fresh insights into how material engineering at the nanoscale can tailor phonon dispersion and open pathways for thermal engineering.

Ahmad Wadee, Pete Walker, Nick McCullen et al.

Victor Igwemezie, Muhammad Shamir, Ali Mehmanparast et al.

A great deal of effort goes into production of modern steel for structural applications. The structural integrity of the steel becomes compromised when it is welded to form engineering components. The structural capacity of the steel joints is further reduced if the joint is to serve in a fluctuating stress environment. This is because, the fatigue strength (FS) of the steel structure is now shifted to the welded joints. One of the major factors that deteriorate the FS of welded joints is tensile residual stress (TRS). There have been efforts in the last two decades to develop welding alloys capable of mitigating TRS in welded joints based on the phase-transformation of austenite (γ) to martensite (ά). This paper reviews the design, application and results of these alloys often referred to as Low Transformation Temperature (LTT) welding alloys. It also presented the factors affecting them and areas where performance data are lacking.

Hao Guo, Haitao Duan, Xingxing Wang et al.

Reducing wear and clarifying relation mechanism are essential to improve the life of engine bearings, so we investigate the influence of ambient temperature on the friction characteristics of M50 steel self-matching pairs under dry friction conditions. As the ambient temperature increases from 30 °C to 500 °C, friction coefficient decreases sharply from 0.78 and tends to be stable around 0.4, while wear rate firstly decreases and then increases. High temperature (More than 300 °C) induces the serious oxidation and softening on the wear surface, causing the main wear mode from abrasive wear to adhesive wear. The oxides include mainly of Fe _2 O _3 and Fe _3 O _4 , and minor MoO _3 and Cr _2 O _3 , which are benefit for forming a continuous tribolayer on the wear surface, thereby improving the friction performance.

Sijie Wan, Jingsan Xu, Shaowen Cao et al.

Abstract To satisfy the requirements of substantial green development, it is urgent to explore an innovative eco‐friendly semiconductor photocatalyst to efficiently achieve visible‐light‐driven photocatalytic H2 evolution (PHE). The strategy of promoting the spatial separation efficiency of photoinduced carriers can essentially enhance the PHE performance of a photocatalyst. Herein, a graphitic carbon nitride (g‐C3N4)‐based donor–acceptor (D‐A) copolymer (CNDMx) is constructed by simple one‐pot thermal polycondensation, using urea and 5,8‐DibroMoquinoxaline (as an electron donor) as precursors. The electron D‐A modulation consequently creates an internal electric field to facilitate the intramolecular charge transfer within the copolymer. A series of experimental characterizations and density functional theory calculations are applied to elucidate the variation and correlation of the structure and PHE performance of the as‐prepared catalysts. It is found that the best average PHE rate of 3012.5 μmol g−1 h−1 can be achieved over the optimal D‐A copolymer under visible‐light (400 < λ < 800 nm) irradiation, which is ~3.3 times that of pure urea‐derived g‐C3N4. The corresponding apparent quantum efficiency is 1.3% at 420 nm. This study provides a protocol for designing effective visible‐light photocatalysts via D‐A modulation of polymeric semiconductors.

Yamid E. Nuñez de la Rosa, Oriana Palma Calabokis, Gloria M. Pena Uris et al.

Abstract This study investigated the pitting and crevice corrosion behavior of the gas tungsten arc welding (GTAW) process in the UNS S32205 according to industrial parameters. Results revealed that the welding process presented a weld metal chemical composition similar to the base metal and an adequate balance of the austenite and ferrite phases. No relevant variation in the hardness was observed and XRD spectra did not identify the presence of deleterious phases in the weld bead. Cyclic polarization tests revealed similarities between welded and base metal samples (20±2°C, NaCl 3.5% wt.). When comparing the behavior obtained in the crevice, and pitting tests, a decrease in the corrosion resistance was observed in the presence of a crevice former. The SEM-EDS proved that the attack occurred mainly in secondary austenites. Profilometry measurements revealed that the crevice corrosion in the weld region was deeper than in the base metal. However, considering the welded samples as a unit, making no difference between regions: weld metal, HAZ, and base metal, the average crevice corrosion depth was comparable to that of the base metal samples. Finally, it was concluded that the welding process used for the UNS S32205 steel did not harm its corrosion resistance.

Bing Zhang, Hele Guo, Longsheng Zhang et al.

Abstract The exploration of a noble-metal-free and nitrogen-doped carbon (M–N/C) composite electrocatalyst for the oxygen reduction reaction (ORR) remains a great challenge. The activities of the M–N/C composite electrocatalysts are mainly affected by the metal active sites, pyridinic nitrogen, and graphitic nitrogen. In the present work, the iron-coordinated self-assembly is proposed for the preparation of iron-chelating pyridine nitrogen-rich coordinated nanosheet (IPNCN) composites as electrocatalysts. Due to the highly conjugated structure of the IPNCN precursor, the pyridine nitrogen elements at both ends of the tetrapyrido [3,2-a:2',3'-c:3'',2''-h:2''',3'''-j] phenazine (TP) provide the multiple ligands, and the coordination interactions between the irons and the pyridine nitrogen further improve the thermodynamic stability, where the metal active sites and nitrogen elements are uniformly distributed in the whole structure. The resultant IPNCN composites exhibit excellent ORR performance with an onset potential of 0.93 V and a half potential of 0.84 V. Furthermore, the IPNCN composite electrocatalysts show the higher methanol resistance and electrochemical durability than the commercial Pt/C catalysts. It could be convinced that the as-designed IPNCN composite catalysts would be a promising alternative to the noble metal Pt-based catalysts in the practical applications.

Jack Y. Araz, Juan Carlos Criado, Michael Spannowsky

Chiral magnets have attracted a large amount of research interest in recent years because they support a variety of topological defects, such as skyrmions and bimerons, and allow for their observation and manipulation through several techniques. They also have a wide range of applications in the field of spintronics, particularly in developing new technologies for memory storage devices. However, the vast amount of data generated in these experimental and theoretical studies requires adequate tools, among which machine learning is crucial. We use a Convolutional Neural Network (CNN) to identify the relevant features in the thermodynamical phases of chiral magnets, including (anti-)skyrmions, bimerons, and helical and ferromagnetic states. We use a flexible multi-label classification framework that can correctly classify states in which different features and phases are mixed. We then train the CNN to predict the features of the final state from snapshots of intermediate states of a lattice Monte Carlo simulation. The trained model allows identifying the different phases reliably and early in the formation process. Thus, the CNN can significantly speed up the large-scale simulations for 3D materials that have been the bottleneck for quantitative studies so far. Moreover, this approach can be applied to the identification of mixed states and emerging features in real-world images of chiral magnets.

Bo Xu, Zhanpeng Gong, Jingran Liu et al.

Polar topological structures in ferroelectric thin films have recently drawn significant interest due to their fascinating physical behaviors and promising applications in high-density nonvolatile memories. However, most polar topological patterns are only observed in the perovskites superlattices. Here, we report the discovery of the tunable ferroelectric polar topological defective structures designed and achieved by strain engineering in two-dimensional PbX (X=S, Se, and Te) materials using multiscale computational simulations. First, the first-principles calculations demonstrate the strain-induced recoverable ferroelectric phase transition in such 2D materials. The unique polar topological vortex pattern is then induced by applied mechanical indentation, evidenced by molecular dynamics simulations based on a developed deep-learning potential. According to the strain phase diagram and applied complex strain loadings, the diverse polar topological structures, including antivortex structure and flux-closure structure, are predicted to be emergent through the finite-element simulations. We conclude that strain engineering is promising to tailor various designed reversible polar topologies in ultra-flexible 2D materials, which provide excellent opportunities for next-generation nanoelectronics and sensor devices.

Dong–Cho Kim, Tomo Ogura, Ryosuke Hamada et al.

Duplex stainless steel (DSS) is vulnerable to changes in the α/γ phase fraction due to the dissolution and precipitation of various compounds during multi–pass welding. Thus, prediction of this dissolution and precipitation behavior is key for the development of effective manufacturing strategies. In this study, the kinetics of the dissolution and precipitation phenomena of the γ phase in Fe-Cr-Ni alloy were investigated using the kinetic constants derived by the phase–field method, and the α/γ phase fraction of the multi-pass welds was theoretically investigated. The kinetics of the dissolution and precipitation phenomena were evaluated theoretically and experimentally through optical and scanning electron microscopy. DSSs with different compositions were evaluated to achieve satisfactory correlation. The temperature dependences of the experimental and calculated values were found to be in good agreement, indicating that it is possible to theoretically predict the dissolution and precipitation phenomenon of the γ phase by using the phase-field method presented herein. With regard to the α/γ phase fraction, there was a remarkably high correlation between the results predicted using the kinetic constant of the experimental value and those predicted using the kinetic constant derived from the phase–field method. Therefore, the kinetics-based theoretical results of this study could serve as a resource for predicting the γ phase amount of multi–pass welds in DSSs.