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

Junaid Khan, Júlia Marí-Guaita, Joshua D. Forero et al.

Abstract Metal-halide perovskites are promising materials for optoelectronic applications due to their strong light absorption, tunable bandgaps, and solution-processability. However, their use in photodetectors is often limited by low carrier mobility and degradation over time as compared to advanced 2D nano-materials. Here, we report ultrasensitive photodetectors based on inkjet-printed nanocrystalline films of mixed-phase raisin bread CsPbBr3/Cs4PbBr6 perovskite integrated on graphene platforms. The combination of a photoconductive mixed-phase perovskite and a high-mobility 2D graphene channel enables efficient photogating and broadband charge transport. This device architecture achieves exceptional performance with responsivities surpassing 5.7 × 104 A W-1 and detectivities exceeding 1016 Jones at 312 nm. The enhanced performance arises from the synergistic interplay between charge confinement in the perovskite domains and ultrafast carrier extraction by graphene. Moreover, the fabricated photodetectors exhibit remarkable operational stability, a longevity primarily attributed to the unique composite raisin-bread architecture of the inkjet-printed perovskite films. This work offers a scalable and sustainable strategy for high-performance broadband photodetection.

Yuqi An, Zhenbin Wang

Universal machine-learning interatomic potentials (uMLIPs) have become powerful tools for accelerating computational materials discovery by replacing expensive first-principles calculations in crystal structure prediction (CSP). However, their effectiveness in identifying new, complex materials remains uncertain. Here, we systematically assess the capability of a uMLIP (i.e.,M3GNet) to accelerate CSP in quaternary oxides. Through extensive exploration of the Sr-Li-Al-O and Ba-Y-Al-O systems, we show that uMLIP can rediscover experimentally known materials absent from its training set and identify seven new thermodynamically and dynamically stable compounds. These include a new polymorph of Sr2LiAlO4 (P3221) and a new disordered phase, Sr2Li4Al2O7 (P1_bar). Furthermore, our results show stability predictions based on the semilocal PBE functional require cross-validation with higher-level methods, such as SCAN and RPA, to ensure reliability. While uMLIPs substantially reduce the computational cost of CSP, the primary bottleneck has shifted to the efficiency of search algorithms in navigating complex structural spaces. This work highlights both the promise and current limitations of uMLIP-driven CSP in the discovery of new materials.

Chaiti Saha, Shova Pandit, Md Motaher Hossain et al.

Rice blast caused by Pyricularia oryzae (syn. Magnaporthe oryzae ) is one of the most devastating diseases in rice, resulting in substantial yield loss. Currently, the control of rice blast relies significantly on chemical fungicides, which raise numerous environmental concerns. However, silver nanoparticles (AgNPs) are emerging as innovative, non-resistant substitutes for conventional fungicides. This study aimed to synthesize AgNPs from banana flowers via a green approach and assess their antifungal activity against Pyricularia oryzae strain SP2 in vitro . The pathogen Pyricularia oryzae strain SP2 was identified by morphological features and study of the internal transcribed spacer (ITS) sequence. The AgNPs were characterized via UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), transmission electron microscopy (TEM) and energy-dispersive x-ray analysis (EDX). The optimal reaction conditions for the green synthesis of the AgNPs resulted in a rapid color change from light yellow to dark brown when the floral extract (15 ml) was added. A surface plasmon resonance peak was observed in the UV-visible spectrum at approximately 433 cm ^−1 , which was correlated with the synthesis of the AgNPs. The biogenic AgNPs had a spherical form with an average particle size of 47.63 nm, according to TEM and SEM examination. The greatest mycelial growth inhibition of P. oryzae (87.25%) was observed when it was exposed to biofabricated AgNPs at 40 μg ml ^−1 . The AgNPs successfully suppressed spore germination and germ tube development of P. oryzae , with increased doses demonstrating enhanced antifungal efficacy. Additionally, the appressorium formation rates decreased from 78.34% in the control to 41.67%, 16.45%, and 4% at increasing concentrations (20, 30, 40 μg ml ^−1 ). Overall, this study demonstrated that bioinspired AgNPs have antifungal activity against the rice blast pathogen P. oryzae and can be used to control blast diseases in rice.

Suman Lata Yadav

The concept of life skills is related to the way of life that emphasises the mutual exchange of knowledge, attitudes, and interpersonal skills in education. Its objective is to develop diverse skills among students and prepare them to face life’s challenges with determination. The World Health Organization has defined life skills as “the positive behaviours and tendencies that enable a person to adapt in day-to-day life.” Life skills are the abilities that enable a person to adapt and exhibit positive behaviour, allowing them to deal effectively with the problems and challenges of daily life. Life is a unique gift. Therefore, by equipping life with various skills, happiness, peace, and prosperity are created. In this research, with the objectives of the study in mind, an analytical examination of life skills among secondary-level students has been conducted. This research study examines the effects of living conditions, gender, and social class on students’ life skills and presents the findings. Future researchers can build upon this, and other factors affecting the research can also be explored.

Xiaoxiao Zhou, Yuxin Xu, Xiaoqi Gao et al.

BiFeO3BaTiO3 (BF–BT) ceramics exhibit higher piezoelectric coefficients (d33), Curie temperatures (TC), and temperature stability than other high-temperature lead-free piezoelectric materials. However, despite their crucial role in piezoelectric devices, the mechanical properties of BF–BT ceramics have been underexplored. A thorough evaluation of the mechanical properties of BF–BT is crucial for developing cost-effective and durable lead-free piezoelectric ceramics. Moreover, the specific causes of the high piezoelectric response and excellent temperature stability of BF–BT ceramics remain unclear owing to the instrumental detection threshold, which limits experimental studies to temperatures above 140 °C and below the degradation temperature of d33. To investigate the intrinsic origins of the high piezoelectricity and temperature stability of BF–xBT ceramics and to enhance their mechanical properties, a two-step sintering process is used to fabricate these ceramics (0.25 ≤ x ≤ 0.40). Owing to improvements in grain refinement and reduced Bi3+ volatilization, the BF–0.33 BT ceramic exhibits enhanced overall performance, with a modified small punch strength of 155 MPa, Vickers hardness of 5.2 GPa, a d33 of 220 pC/N at room temperature, TC of 466 °C, and d33 values exceeding 400 pC/N at 260 °C. Phase-field simulations, which address the limitations of device detection thresholds, reveal that with increasing temperature, the domain structure relaxes, and polarization intensity decreases. This indicates that changes in the high-temperature piezoelectric properties can be attributed to domain structure relaxation and the increase in dielectric constant. Overall, BF–BT ceramics exhibit superior piezoelectric performance, mechanical properties, and temperature stability, making them highly suitable for use in high-temperature and demanding environments.

Olajumoke Oluwatobiloba Emmanuel, Shuvankar Gupta, Xianglin Ke

The Nernst effect, the generation of a transverse electric voltage in the presence of longitudinal thermal gradient, has garnered significant attention in the realm of magnetic topological materials due to its superior potential for thermoelectric applications. In this work, we investigate electronic and thermoelectric transport properties of a Kagome magnet ErMn$_6$Sn$_6$, a compound showing an incommensurate antiferromagnetic phase followed by a ferrimagnetic phase transition upon cooling. We show that in the antiferromagnetic phase ErMn$_6$Sn$_6$ exhibits both topological Nernst effect and anomalous Nernst effect, analogous to the electric Hall effects, with the Nernst coefficient reaching 1.71 uV/K at 300 K and 3 T. This value surpasses that of most of previously reported state-of-the-art canted antiferromagnetic materials and is comparable to recently reported other members of RMn$_6$Sn$_6$ (R = rare-earth, Y, Lu, Sc) compounds, which makes ErMn$_6$Sn$_6$ a promising candidate for advancing the development of Nernst effect-based thermoelectric devices.

Navindra D. Singh, James Leung, Ji Feng et al.

Most solar desalination efforts are photothermal: they evaporate water with ``black'' materials that absorb as much sunlight as possible. Such ``brine-boiling'' methods are limited by the high thermal mass of water, i.e., its capacity to store and release heat. Here, we study the light-enhanced evaporation by a hard, white, aluminum nitride wick, and propose a route to selectively target salt-water bonds instead of bulk heating via deep-UV interactions. Through experiments and analyses that isolate the effects of light absorption and heating in aluminum nitride, we provide experimental evidence of a light-driven, spectrum-selective path to non-photothermal saltwater evaporation. Leverage of these light-matter interactions in white ceramic wicks may achieve low-cost, low-energy desalination, reduce the heat island effects of traditional solar technologies, and contribute to future cooling technologies where drought is also a concern.

Eleni C. Mazarakioti, Carla Boix-Constant, Iván Gómez-Muñoz et al.

Van der Waals (vdW) materials provide a platform to study and control the physical properties of low-dimensional materials. While strategies developed for two-dimensional (2D) crystals are not directly transferable to one-dimensional (1D) systems, we can benefit from them by creating layers formed by interconnected chains. Here, we develop a molecular strategy to illustrate this concept consisting of assembling 1D materials in 2D metal-organic frameworks (MOFs). Crystals of [FeX(pzX)(bpy)] (X = Cl, F; pz = pyrazole; bpy = bipyridine) consist of iron chains along the b-axis, crosslinked via bpy ligands along the a-axis to form 2D layers, stacked along the c-axis via vdW forces. This structural anisotropy manifests itself in highly-anisotropic optical properties, as demonstrated by optical measurements in the visible and terahertz ranges, results which are supported by DFT calculations. Chemical substitution enables the tuning of the optical properties, as exemplified by the photoluminescence of the Cl-derivative, which is quenched for the F-derivative. Thin-layers are obtained by mechanical exfoliation, and their optical properties are further tuned through the fabrication of orthogonally-twisted vdW heterostructures, enabling to effectively switch-off the optical anisotropy. Our work highlights the chemical flexibility of vdW layered MOFs as a platform for designing and manipulating 1D architectures.

Wenfeng Zhang, Ran Li, Jianfeng Wang et al.

Superior soft-magnetic materials are necessary for the development of modern magnetic devices with energy-saving and high-power density requirements. However, improving the magnetism by nanocrystallization always brings about the sacrifice of resistivity, presenting a common trade-off in Fe-based amorphous-nanocrystalline alloys. Here, the comprehensive merits of both superior soft-magnetic properties (high saturation magnetization of 1.81 T and low coercivity of 3.8 A/m) and high resistivity of 117.2 μΩ·cm were obtained by precisely tailoring amorphous-nanocrystalline microstructure close to electrical percolation threshold for a Fe82.5B12P2C1Cu0.5Co2 amorphous alloy. The soft-magnetic properties are attributed to the low magnetic anisotropy stemming from high nuclei number density and ultrafine nanocrystalline grains of 9.2 nm. The high resistivity is associated with the electrical percolation behavior with a nanocrystalline volume threshold of 14.8 % in the composite alloy. The results provide an effective strategy to overcome the trade-off in traditional amorphous-nanocrystalline alloys, significant for applications in high-frequency, high-power, and energy-saving devices.

Pavel Khazov, Vladimir Erofeev, Olga Vediaikina et al.

В последние десятилетия наблюдается повышенный интерес к изучению напряженно-деформированного состояния трубобетонных конструкций – композитных элементов, состоящих из стальной трубы-оболочки и бетонного сердечника, находящегося в состоянии трехосного сжатия. В таком сочетании сталь и бетон позволяют достичь лучших прочностных и деформативных характеристик, чем при их раздельной работе, что позволяет проектировать безопасные и экономичные конструкции. В настоящей статье приводятся результаты экспериментального исследования процесса деформирования изгибаемых трубобетонных элементов малогабаритных круглых сечений. Показано, что при трехточечном поперечном изгибе трубобетонной балки помимо прогиба за счет искривления оси стержня, существенное влияние на вертикальные перемещению оказывают деформации локального смятия в местах приложения сосредоточенных нагрузок. Проводится оценка возможности применения классической теории изгиба полой стальной балки по модели Бернулли. Сопоставляются результаты испытаний и диаграммы деформирования полых стальных труб (аналитические и экспериментальные данные) и сталежелезобетонных балок труб, заполненных бетоном. Произведена качественная и количественная оценка вклада наличия бетонного сердечника на несущую способность и деформативность (в т.ч. местное смятие) элемента. Наличие бетонного сердечника в композитном стержне дает существенное утяжеление конструкции, однако в случае внецентренного сжатия несущих вертикальных элементов многоэтажных зданий эффективность применения трубобетонных элементов весьма эффективно.

Damien Pinto, Michael Greenwood, Nikolas Provatas

The development of novel materials in recent years has been accelerated greatly by the use of computational modelling techniques aimed at elucidating the complex physics controlling microstructure formation in materials, the properties of which control material function. One such technique is the phase field method, a field theoretic approach that couples various thermophysical fields to microscopic order parameter fields that track the phases of microstructure. Phase field models are framed as multiple, non-linear, partial differential equations, which are extremely challenging to compute efficiently. Recent years have seen an explosion of computational algorithms aimed at enhancing the efficiency of phase field simulations. One such technique, adaptive mesh refinement (AMR), dynamically adapts numerical meshes to be highly refined around steep spatial gradients of the PDE fields and coarser where the fields are smooth. This reduces the number of computations per time step significantly, thus reducing the total time of computation. What AMR doesn't do is allow for adaptive time stepping. This work combines AMR with a neural network algorithm that uses a U-Net with a Convolutional Long-Short Term Memory (CLSTM) base to accelerate phase field simulations. Our neural network algorithm is described in detail and tested in on simulations of directional solidification of a dilute binary alloy, a paradigm that is highly practical for its relevance to the solidification of alloys.

X. Feng, Y. Jiang, H. Hu et al.

Kagome materials manifest rich physical properties due to the emergence of abundant electronic phases. Here, we carry out a high-throughput first-principles study of the kagome 1:6:6 family MT$_6$Z$_6$ materials in space group 191, focusing on their phonon instability and electronic flat bands. Different MT$_6$Z$_6$ kagome candidates reveal a remarkable variety of kagome flat bands ranging from unfilled, partially filled, to fully filled. Notably, the Mn/Fe-166 compounds exhibit partially filled flat bands with a pronounced sharp peak in the density of states near the Fermi level, leading to magnetic orders that polarize the bands and stabilize the otherwise unstable phonon. When the flat bands are located away from the Fermi level, we find a large number of phonon instabilities, which can be classified into three types, based on the phonon dispersion and vibrational modes. Type-I instabilities involve the in-plane distortion of kagome nets, while type-II and type-III present out-of-plane distortion of trigonal M and Z atoms. We take MgNi$_6$Ge$_6$ and HfNi$_6$In$_6$ as examples to illustrate the possible CDW structures derived from the emergent type-I and type-II instabilities. The type-I instability in MgNi$_6$Ge$_6$ suggests a nematic phase transition, governed by the local twisting of kagome nets. The type-II instability in HfNi$_6$In$_6$ may result in a hexagonal-to-orthorhombic transition, offering insight into the formation of MT$_6$Z$_6$ in other space groups. Additionally, the predicted ScNb$_6$Sn$_6$ is analyzed as an example of the type-III instability. Our predictions suggest a vast kagome family with rich properties induced by the flat bands, possible CDW transitions, and their interplay with magnetism.

Azad A. Mohammed, Muhammad A. Muhammad, Bilal K. Mohammed

This paper aims to experimentally investigate the flexural behavior of concrete beams reinforced with glass fiber reinforced polymer (GFRP) bars made of concrete with and without polyethylene terephthalate (PET) waste fiber addition. The test variable covers the structural application of different PET fiber lengths (20 mm and 40 mm). Firstly, several tests were done on ten concrete mixes containing 1–2% PET waste fiber with a 0.25% increment by volume. The mixture's concrete properties, including stress-strain curves, were studied to obtain the optimum percentage of PET fiber. Furthermore, four GFRP reinforced concrete (RC) beams were cast from concrete containing 0% PET fiber (the control beam), 1% PET fiber volumes of 20 mm and 40 mm, and an equal mixture of both lengths. The beams were designed using ACI 440.1R to fail in GFRP rupture. The results showed that compressive strength increased by 8% and 6% using 1% fiber volume of 20 and 40 mm PET fiber, respectively. It was found that PET fiber addition had a negligible effect on changing the ductility, cracking pattern, or failure mode of under reinforced GFRP RC beams. The cracking and ultimate loads are slightly reduced, however, and the corresponding deflections are well reduced, especially when using 40 mm PET fiber. With the use of PET waste fiber, serviceability increased by up to 12% based on deflection limit control (L/240). The addition of 40 mm of PET fiber was found to enhance the beam stiffness by 25%. An analysis method has been proposed to predict the flexural strength of GFRP RC beams made with PET fiber. Moreover, it is recommended to treat the PET fiber surface to improve the fiber-concrete bond when used in non-ductile RC beams.

Sanhita Das, Yuri Lubomirsky, Eran Bouchbinder

Crack front waves (FWs) are dynamic objects that propagate along moving crack fronts in 3D materials. We study FW dynamics in the framework of a 3D phase-field framework that features a rate-dependent fracture energy $Γ(v)$ ($v$ is the crack propagation velocity) and intrinsic lengthscales, and quantitatively reproduces the high-speed oscillatory instability in the quasi-2D limit. We show that in-plane FWs feature a rather weak time dependence, with decay rate that increases with $dΓ(v)/dv\!>\!0$, and largely retain their properties upon FW-FW interactions, similarly to a related experimentally-observed solitonic behavior. Driving in-plane FWs into the nonlinear regime, we find that they propagate slower than predicted by a linear perturbation theory. Finally, by introducing small out-of-plane symmetry-breaking perturbations, coupled in- and out-of-plane FWs are excited, but the out-of-plane component decays under pure tensile loading. Yet, including a small anti-plane loading component gives rise to persistent coupled in- and out-of-plane FWs.

Bailing An, Yan Xin, Rongmei Niu et al.

To study discontinuous precipitation, which is an important method for strengthening materials, we observed the nucleation and growth of discontinuous precipitates in Cu–Ag alloys using electron backscatter diffraction and scanning transmission electron microscopy. We found that discontinuous precipitation always started with Ag precipitates, which nucleated on Cu grain boundaries. These precipitates then each took the shape of a large, abutted cone that shared a semi-coherent interface with one of the Cu grains, topped by a small spherical cap that shared an incoherent interface with the Cu grain on the opposite side of the boundary. This formation created a difference between the levels of interface energy on each side of boundary. We assume that this difference and boundary curvature together generates the driving force necessary to push grain boundary migration, thus triggering discontinuous precipitation. Because of grain boundary migration, Ag solute was consumed at one side of the grain, which causes a solute difference. The difference produces mainly driving force, pushing the boundaries to migrate forward.

Axel Hoffmann, Shriram Ramanathan, Julie Grollier et al.

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new energy-efficient device concepts that implement neuromorphic ideas at the hardware level. In particular, strong correlations give rise to highly non-linear responses, such as conductive phase transitions that can be harnessed for short and long-term plasticity. Similarly, magnetization dynamics are strongly non-linear and can be utilized for data classification. This paper discusses select examples of these approaches, and provides a perspective for the current opportunities and challenges for assembling quantum-material-based devices for neuromorphic functionalities into larger emergent complex network systems.

Hui Wang, Sihang Xiao, Jianshan Wang

Previous discussions about perforated auxetic metamaterials primarily focused on the ordered systems with high degree of geometric symmetry. However, it is difficult to manufacture or retain the perfect auxetic systems in practical applications. In this paper, three types of disordered perforated auxetic systems including orientated disordered system, dimensional disordered system and complete-disordered system are explored thoroughly. The perforations of interest are oval holes which are advantageous in ensuring auxeticity, reducing stress level and improving material distribution. The designed disordered systems are fabricated by 3D printing technology and then are tested by the uniaxial tension to reveal their mechanical properties and verify the related finite element models. Thereafter, the evolution of mechanical properties of these disordered systems is investigated numerically for the varied perturbed geometric parameters such as the orientation and dimension of oval hole. The results reveal that the disordered systems still show great robustness in auxetic behavior, although the disorder in orientation and dimension exists. A high degree of symmetry in microstructure is not necessary for designing perforated auxetic systems. This provides a great convenience for the flexible and practicable design and application of perforated auxetic metamaterials.

Ruirui Fang, Nana Deng, Hongbin Zhang et al.

In this paper, selective laser melting (SLM) was used to manufacture corrax stainless steel samples under different parameters. It was found that the SLMed samples were mainly composed by lots of fine martensite (including cellular structure, cellular dendritic grains and blocky grains), and trace austenite. During SLM forming process, a large number of low-angle grain boundaries (LAGBs) and high-density dislocations were formed in the matrix. Meanwhile, the samples showed weak texture and no obvious preference orientation. Moreover, the relative density of all SLMed samples reached above 90%, and the relative density was above 97% when the laser energy density was 54.13–78.19 J·mm−3. Under the optimal process parameters of P = 190 W, V = 1.1 m·s−1, the relative density of sample reached above 99.52 ± 0.09%, while the sample exhibited the best mechanical properties, including the highest microhardness (374.2 ± 6.5HV), yield strength (YS = 946 ± 7.3 MPa), ultimate tensile strength (UTS = 1084 ± 3 MPa) and elongation (EL = 17.64 ± 0.18%). Moreover, the strengthening mechanisms of SLMed samples mainly included grain boundary strengthening, dislocation strengthening and precipitation strengthening, while dislocation strengthening played a dominant role. Besides that, the fracture mechanisms of SLMed samples belonged to ductile fracture, except for the samples prepared with laser energy density below 54.13 J·mm−3.

Sebastian Ament, Maximilian Amsler, Duncan R. Sutherland et al.

Autonomous experimentation enabled by artificial intelligence (AI) offers a new paradigm for accelerating scientific discovery. Non-equilibrium materials synthesis is emblematic of complex, resource-intensive experimentation whose acceleration would be a watershed for materials discovery and development. The mapping of non-equilibrium synthesis phase diagrams has recently been accelerated via high throughput experimentation but still limits materials research because the parameter space is too vast to be exhaustively explored. We demonstrate accelerated synthesis and exploration of metastable materials through hierarchical autonomous experimentation governed by the Scientific Autonomous Reasoning Agent (SARA). SARA integrates robotic materials synthesis and characterization along with a hierarchy of AI methods that efficiently reveal the structure of processing phase diagrams. SARA designs lateral gradient laser spike annealing (lg-LSA) experiments for parallel materials synthesis and employs optical spectroscopy to rapidly identify phase transitions. Efficient exploration of the multi-dimensional parameter space is achieved with nested active learning (AL) cycles built upon advanced machine learning models that incorporate the underlying physics of the experiments as well as end-to-end uncertainty quantification. With this, and the coordination of AL at multiple scales, SARA embodies AI harnessing of complex scientific tasks. We demonstrate its performance by autonomously mapping synthesis phase boundaries for the Bi$_2$O$_3$ system, leading to orders-of-magnitude acceleration in establishment of a synthesis phase diagram that includes conditions for kinetically stabilizing $δ$-Bi$_2$O$_3$ at room temperature, a critical development for electrochemical technologies such as solid oxide fuel cells.

Suvo Banik, Troy D Loeffler, Rohit Batra et al.

Defect dynamics in materials are of central importance to a broad range of technologies from catalysis to energy storage systems to microelectronics. Material functionality depends strongly on the nature and organization of defects, their arrangements often involve intermediate or transient states that present a high barrier for transformation. The lack of knowledge of these intermediate states and the presence of this energy barrier presents a serious challenge for inverse defect design, especially for gradient-based approaches. Here, we present a reinforcement learning (Monte Carlo Tree Search) based on delayed rewards that allow for efficient search of the defect configurational space and allows us to identify optimal defect arrangements in low dimensional materials. Using a representative case of 2D MoS2, we demonstrate that the use of delayed rewards allows us to efficiently sample the defect configurational space and overcome the energy barrier for a wide range of defect concentrations (from 1.5% to 8% S vacancies), the system evolves from an initial randomly distributed S vacancies to one with extended S line defects consistent with previous experimental studies. Detailed analysis in the feature space allows us to identify the optimal pathways for this defect transformation and arrangement. Comparison with other global optimization schemes like genetic algorithms suggests that the MCTS with delayed rewards takes fewer evaluations and arrives at a better quality of the solution. The implications of the various sampled defect configurations on the 2H to 1T phase transitions in MoS2 are discussed. Overall, we introduce a Reinforcement Learning (RL) strategy employing delayed rewards that can accelerate the inverse design of defects in materials for achieving targeted functionality.