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

Changhua Bao, Vincent Eggers, Manuel Meierhofer et al.

Abstract Dispersionless electronic bands lead to an extremely high density of states and suppressed kinetic energy, thereby increasing electronic correlations and instabilities that can shape emergent ordered states, such as excitonic, ferromagnetic, and superconducting phases. A flat band that extends over the entire momentum space and is well isolated from other dispersive bands is, therefore, particularly interesting. Here, the band structure of the van der Waals crystal NbOCl2 is revealed by utilizing photoelectron momentum microscopy. We directly map out an electronic band that is flat throughout the entire Brillouin zone and features a width of only  ~ 100 meV. This band is well isolated from both the conduction and remote valence bands. Moreover, the quasiparticle band gap shows a high tunability upon the deposition of cesium atoms on the surface. By combining the single-particle band structure with the optical transmission spectrum, the optical gap is identified. The fully isolated flat band in a van der Waals crystal provides a qualitatively new testbed for exploring flat-band physics.

Brandon Schoener, Yuting Hu, Pasit Wanlapha et al.

Incorporating Machine Learning (ML) into material property prediction has become a crucial step in accelerating materials discovery. A key challenge is the severe lack of training data, as many properties are too complicated to calculate with high-throughput first principles techniques. To address this, recent research has created experimental databases from information extracted from scientific literature. However, most existing experimental databases do not provide full atomic coordinate information, which prevents them from supporting advanced ML architectures such as Graph Neural Networks (GNNs). In this work, we propose to bridge this gap through an alignment process between experimental databases and Crystallographic Information Files (CIF) from the Inorganic Crystal Structure Database (ICSD). Our approach enables the creation of a database that can fully leverage state-of-the-art model architectures for material property prediction. It also opens the door to utilizing transfer learning to improve prediction accuracy. To validate our approach, we align NEMAD with the ICSD and compare models trained on the resulting database to those trained on NEMAD originally. We demonstrate significant improvements in both Mean Absolute Error (MAE) and Correct Classification Rate (CCR) in predicting the ordering temperatures and magnetic ground states of magnetic materials, respectively.

Mohammed Saleh Alshaikh

The performance of Organic Solar Cells (OSCs) is intrinsically linked to the molecular, electronic, and structural properties of donor and acceptor materials. This study employs various machine learning techniques, namely the Generalized Regression Neural Network (GRNN), Support Vector Machine (SVM), and Tree Boost, to predict key performance metrics of OSCs, including power conversion efficiency (PCE), short-circuit current density (JSC), open-circuit voltage (VOC), and fill factor (FF). The models are trained and evaluated using an experimentally reported dataset compiled by Sahu et al. Correlation analysis demonstrates that material characteristics such as polarizability, bandgap, dipole moment, and charge transfer are statistically associated with OSC performance. The predictive performance of the GRNN model is compared with that of the SVM and Tree Boost models, showing consistently lower prediction errors within the considered dataset. In addition, sensitivity analysis is performed to assess the relative importance of the predictor variables and to examine the influence of kernel functions on GRNN performance. The results indicate that machine learning models, particularly GRNN, can serve as effective data-driven tools for predicting the performance of organic solar cells and for supporting computational screening studies.

Atasi Ghosh

Xin Kong, Bin Liu, Zhongqiu Tong et al.

Abstract Metallic phthalocyanines are promising electrocatalysts for CO2 reduction reaction (CO2RR). However, their catalytic activity and stability (especially under high potential) are still unsatisfactory. Herein, we synthesized a covalent organic polymer (COP‐CoPc) by introducing charge‐switchable viologen ligands into cobalt phthalocyanine (CoPc). The COP‐CoPc exhibits great activity for CO2RR, including a high Faradaic efficiency over a wide potential window and the highest CO partial current density among all ligand‐tuned phthalocyanine catalysts reported in the H‐type cell. Particularly, COP‐CoPc also shows great potential for practical applications, for example, a FECO of >95% is realized at a large current density of 150 mA/cm2 in a two‐electrode membrane electrode assembly reactor. Ex situ and in situ X‐ray absorption fine structure spectroscopy measurements and theory calculations reveal that when the charge‐switchable viologen ligands switch to neutral‐state ones, they can act as electron donors to enrich the electron density of Co centers in COP‐CoPc and enhance the desorption of *CO, thus improving the CO selectivity. Moreover, the excellent reversible redox capability of viologen ligands and the increased Co–N bonding strength in the Co–N4 sites enable COP‐CoPc to possess outstanding stability under elevated potentials and currents, enriching the knowledge of charge‐switchable ligands tailored CO2RR performance.

Soham Das, Soumya Kanti Biswas, Abhishek Kundu et al.

In this experimental investigation, a Physical Vapor Deposition (PVD) process was employed to deposit TiAlN coating onto a Si substrate. The nitrogen flow rate, bias voltage, and substrate-to-target distance were selected as input parameters, each with three different levels. The design of these input parameters was structured according to Taguchi's L9 Orthogonal Array (OA). Following deposition, the mechanical, microstructural, structural, and electrochemical properties of the TiAlN coating were meticulously characterized and analyzed to discern the influence of the selected parameters on its various properties. Microstructural analysis revealed a homogeneous structure throughout the film. Additionally, the mechanical properties of the film exhibited notable performance under the specified parameters. However, it was observed that no consistent trend could be identified across different properties concerning the applied parameters. To elucidate the complex relationships among these variables, the Least Squares Method (LSM) regression analysis technique was employed. This analytical approach facilitated the establishment of correlations among the diverse parameters, enhancing the understanding of their collective impact on the TiAlN coating properties. The understanding of analytical results will be useful for predicting the values between the two extremities to measure the performance parameters where the experimental results are not available.

JIANG Wuxiong, WU Wenxing, CHEN Pinghu, YANG Tong, LI Huijie, QIU Zhangjun

IN738LC alloy is a typical γ’ phase precipitation-strengthened nickel-based superalloy, commonly used in high-temperature components such as gas turbines and aero-engines.In order to further enhance its high-temperature wear resistance, IN738 alloy samples were prepared using laser cladding technology with four different laser powers in a 99.99%pure nitrogen environment, followed by heat treatment at 850 ℃for 24 h.The microstructure and properties were studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), high-temperature friction and wear testing machines and JMatPro software.Results showed that with the increase in laser power, the mean hardness of the samples without heat treatment increased gradually from 40.74 HRC to 41.92 HRC, while the mean hardness of the samples after heat treatment was 43.0 HRC.The average friction coefficients of the samples without heat treatment and after heat treatment at normal temperature were 0.70 and 0.65, respectively.The average friction coefficient at 800 ℃of the samples after heat treatment was 0.35.The wear resistance of the samples first increased and then decreased with the increase in laser power within a certain range of laser power.The wear resistance of the samples prepared at room temperature and at 800 ℃was highest when the laser power was 750 W and 650 W,respectively.The wear resistance of samples prepared under the same laser power at a high temperature of 800 ℃was much better than that at room temperature.

Daniel E Widdowson, Vitaliy A Kurlin

With the advent of self-driving labs promising to synthesize large numbers of new materials, new automated tools are required for checking potential duplicates in existing structural databases before a material can be claimed as novel. To avoid duplication, we rigorously define the novelty metric of any periodic material as the smallest distance to its nearest neighbor among already known materials. Using ultra-fast structural invariants, all such nearest neighbors can be found within seconds on a typical computer even if a given crystal is disguised by changing a unit cell, perturbing atoms, or replacing chemical elements. This real-time novelty check is demonstrated by finding near-duplicates of the 43 materials produced by Berkeley's A-lab in the world's largest collections of inorganic structures, the Inorganic Crystal Structure Database and the Materials Project. To help future self-driving labs successfully identify novel materials, we propose navigation maps of the materials space where any new structure can be quickly located by its invariant descriptors similar to a geographic location on Earth.

Muhammad Zubair Khan, O. Peil, Apoorva Sharma et al.

Magnetic monolayers show great promise for future applications in nanoelectronics, data storage, and sensing. The research in magnetic two‐dimensional (2D) materials focuses on synthetic iodides and tellurides, which suffer from a lack of ambient stability. So far, naturally occurring layered magnetic materials have been overlooked. These minerals offer a unique opportunity to explore complex air‐stable layered systems with high concentration of magnetic ions. Magnetic ordering in iron‐rich phyllosilicates is demonstrated, focusing on minnesotaite, annite, and biotite. These naturally occurring layered materials integrate local moment baring ions of iron via magnesium/aluminum substitution in their octahedral sites. Self‐inherent capping by silicate/aluminate tetrahedral groups enables air stability of ultra‐thin layers. Their structure and iron oxidation states are determined via Raman and X‐ray spectroscopies. Superconducting quantum interference device magnetometry measurements are performed to examine the magnetic ordering. Paramagnetic or superparamagnetic characteristics at room temperature are observed. Below 40 K ferrimagnetic or antiferromagnetic ordering occurs. In‐field magnetic force microscopy on exfoliated flakes confirms that the paramagnetic response at room temperature persists down to monolayers. Further, a correlation between the mixture of the oxidation states of iron and the critical ordering temperature is established, indicating a path to design materials with higher critical temperatures via oxidation state engineering.

R. Torsi, Kyle T. Munson, Rahul Pendurthi et al.

Substitutionally-doped 2D transition metal dichalcogenides are primed for next-generation device applications such as field effect transistors (FET), sensors, and optoelectronic circuits. In this work, we demonstrate substitutional Rhenium (Re) doping of MoS 2 monolayers with controllable concentrations down to 500 parts-per-million (ppm) by metal-organic chemical vapor deposition (MOCVD). Surprisingly, we discover that even trace amounts of Re lead to a reduction in sulfur site defect density by 5-10×. Ab initio models indicate the free-energy of sulfur-vacancy formation is increased along the MoS 2 growth-front when Re

R. Venturini, Ankita Sarkar, P. Šutar et al.

We investigated temperature ($T$) dependent ultrafast near-infrared (NIR) transient reflectivity dynamics in coexisting superconducting (SC) and charge density wave (CDW) phases of two-dimensional 2H-NbSe$_{2}$ using NIR and visible excitations. With visible pump-photon excitation (400 nm) we find a slow high-energy quasiparticle relaxation channel which is present in all phases. In the CDW phase, we observe a distinctive transient response component, irrespective of the pump-photon energy. The component is marked by the absence of coherent amplitude mode oscillations and a relatively slow, picosecond rise time, which is different than in most of the typical CDW materials. In the SC phase, another tiny component emerges that is associated with optical suppression of the SC phase. The transient reflectivity relaxation in the CDW phase is dominated by phonon diffusive processes with an estimated low-$T$ heat diffusion constant anisotropy of $\sim30$. Strong excitation of the CDW phase reveals a weakly non-thermal CDW order parameter (OP) suppression. Unlike CDW systems with a larger gap, where the optical OP suppression involves only a small fraction of phonon degrees of freedom, the OP suppression in 2H-NbSe$_{2}$ is characterised by the excitation of a large amount of phonon degrees of freedom and significantly slower dynamics.

Rakesh Chaudhari, Rushikesh Bhatt, Vatsal Vaghasia et al.

In the present study, the Gas metal arc welding (GMAW) based Wire-arc additive manufacturing (WAAM) process was preferred for the fabrication of multi-layered structures and their investigations of mechanical properties on metal core wire. Based on literature work, preliminary trials, machine limits, travel speed (TS), voltage (V), and gas mixture ratio (GMR) were identified as machining parameters along with output factors of bead width (BW), bead height (BH), and depth-of-penetration (DOP). Experiments were conducted by following the Box-Behnken design. The feasibility of the generated non-linear regression models has been validated through the statistical analysis of variance and residual plots. The multi-layered structure has been successfully fabricated at the optimized parametric settings of TS at 24 mm/s; the voltage at 24 V, and GMR at 1 which was obtained through the heat transfer search (HTS) algorithm. The fabricated structure was observed to be uniform. The structure exhibited uniform bead-on-bead deposition for the deposited layers. The fabricated multi-layered structure underwent a detailed microstructural and mechanical examinations. Microstructural examination revealed dense needles at the bottom section of the structure as compared to the top section, as the bottom section undergoes multiple heating and cooling cycles. When comparing the multilayer structure to the metal core wire, all the properties exhibited favorable tensile characteristics. The obtained strength from the impact test results highlights the impressive ductility of the multi-layer deposition. Fractography of tensile and impact test specimens has shown the occurrences of larger dimples and suggested a ductile fracture. Lastly, the hardness value in all the sections of the built structure was observed to be uniform, suggesting uniform deposition across the built multi-layer structure. The authors consider the current work will be highly beneficial for users in fabricating multi-layer structures at optimized parametric settings and their investigations for mechanical properties for metal core wire.

Cheng Yu, Long Li, Shiwen Wang et al.

Nanomaterials (NMs) have increasingly been used for the diagnosis and treatment of head and neck cancers (HNCs) over the past decade. HNCs can easily infiltrate surrounding tissues and form distant metastases, meaning that most patients with HNC are diagnosed at an advanced stage and often have a poor prognosis. Since NMs can be used to deliver various agents, including imaging agents, drugs, genes, vaccines, radiosensitisers, and photosensitisers, they play a crucial role in the development of novel technologies for the diagnosis and treatment of HNCs. Indeed, NMs have been reported to enhance delivery efficiency and improve the prognosis of patients with HNC by allowing targeted delivery, controlled release, responses to stimuli, and the delivery of multiple agents. In this review, we consider recent advances in NMs that could be used to improve the diagnosis, treatment, and prognosis of patients with HNC and the potential for future research.

Xuanxin Hu, Nuohao Liu, Vrishank Jambur et al.

Traditionally, the formation of amorphous shear bands (SBs) in crystalline materials has been undesirable, because SBs can nucleate voids and act as precursors to fracture. They also form as a final stage of accumulated damage. Only recently SBs were found to form in undefected crystals, where they serve as the primary driver of plasticity without nucleating voids. Here, we have discovered trends in materials properties that determine when amorphous shear bands will form and whether they will drive plasticity or lead to fracture. We have identified the materials systems that exhibit SB deformation, and by varying the composition, we were able to switch from ductile to brittle behavior. Our findings are based on a combination of experimental characterization and atomistic simulations, and they provide a potential strategy for increasing toughness of nominally brittle materials.

F. Fayose, A. Olaniyan, K. Ogunleye et al.

Weeding is currently still carried out manually in Nigeria and some of the African countries. This is despite the  efforts that have been made to develop different types of weeding machines in Nigeria with different drive mechanisms, features and designs.  Up to this point, no model or design have been commercialized but they remain in the prototype stage partly due  to sophistication, poor quality and low efficiency. In this study, a prototype of motorised weeding machine, actuated by a reciprocating mechanism was designed and fabricated for use on most subsistent crops plots.   The reciprocation prevented the need to move the blades back and front as this action is automatically achieved in one process.The design features included 20o rake angle of the cutting blade, a working depth of 2.54cm and 28cm  width of cut. Dimensions and the thickness of blades were designed according to the principles of  general soil mechanics. Other machine elements were designed following PSG TECH procedures. After fabrication and assembly, the machine was tested on a 10m 10m plot planted with maize and test result indicated a functional efficiency of 98%, quality performance efficiency of 82.7% and field capacity of 0.036m2/s as against 0.01m2/s with manual weeding. The material for the construction was sourced from locally available materials.The weeding machine has an effective cutting width of 27.5 cm and a production cost of NGN 175, 000.00.

Xinxin Zhang, Yupeng Zhang, You Lv et al.

In the present work, a novel one-step plasma electrolytic oxidation (PEO) method is developed for the formation of PEO/Mg-Al layered double hydroxide (LDH) composite coating on AZ31 Mg alloy. Through the control of electrolyte concentration, a Mg-Al LDH layer was formed on the surface of the resultant PEO coating. The corrosion properties of the composite coating were evaluated by electrochemical analysis, hydrogen evolution measurement and salt spraying testing, which exhibited improved corrosion resistance due to the presence of the Mg-Al LDH layer. This work provides a new strategy to take advantage of alloying elements in Mg alloys in PEO treatment to enhance corrosion resistance.

W. Andrews, L. Engineering, U. Freiburg et al.

This work presents a critical overview of the effects of different aspects of model formulation on crack path selection in quasi-static phase field fracture. We consider different evolution methods, mechanics formulations, fracture dissipation energy formulations, and forms of the irreversibility condition. The different model variants are implemented with common numerical methods based on staggered solution of the phase-field and mechanics sub-problems via FFT-based solvers. These methods mix standard approaches with novel elements, such as the use of bound-constrained conjugate gradients for the phase field sub-problem and a heuristic method for near-equilibrium evolution. We examine differences in crack paths between model variants in simple model systems and microstructures with randomly heterogeneous Young’s modulus. Our results indicate that near-equilibrium evolution methods are preferable for quasi-static fracture of heterogeneous microstructures compared to minimization and time-dependent methods. In examining mechanics formulations, we find distinct effects of crack driving force and the model for contact implicit in phase field fracture. Our results favor the use of a strain-spectral decomposition for the crack driving force but not the contact model. Irreversibility condition and fracture dissipation energy formulation were also found to affect crack path selection, but systematic effects were difficult to deduce due to the overall sensitivity of crack selection within the heterogeneous microstructures. Our findings support the use of the AT1 model over the AT2 model and irreversibility of the phase field within a crack set rather than the entire domain. Sensitivity to these differences in formulation was reduced but not eliminated by reducing the crack width parameter (cid:96) relative to the size scale of the random microstructures. phase field fracture formulations affect crack paths in a set of randomly generated, elastically heterogeneous two-dimensional (2-D) microstructures.

Ivan Novikov, Olga Kovalyova, Alexander Shapeev et al.

In computational materials science, a common means for predicting macroscopic (e.g., mechanical) properties of an alloy is to define a model using combinations of descriptors that depend on some material properties (elastic constants, misfit volumes, etc.), representative for the macroscopic behavior. The material properties are usually computed using special quasi-random structures (SQSs), in tandem with density functional theory (DFT). However, DFT scales cubically with the number of atoms and is thus impractical for a screening over many alloy compositions. Here, we present a novel methodology which combines modeling approaches and machine-learning interatomic potentials. Machine-learning interatomic potentials are orders of magnitude faster than DFT, while achieving similar accuracy, allowing for a predictive and tractable high-throughput screening over the whole alloy space. The proposed methodology is illustrated by predicting the room temperature ductility of the medium-entropy alloy Mo-Nb-Ta.

Hang Chi, Jagadeesh S. Moodera

The quantum anomalous Hall effect refers to the quantization of Hall effect in the absence of applied magnetic field. The quantum anomalous Hall effect is of topological nature and well suited for field-free resistance metrology and low-power information processing utilizing dissipationless chiral edge transport. In this Perspective, we provide an overview of the recent achievements as well as the materials challenges and opportunities, pertaining to engineering intrinsic/interfacial magnetic coupling, that are expected to propel future development of the field.

Chrysoula Litina, Abir Al-Tabbaa