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Surface phase diagram of CsSnI3 from first-principles calculations

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arXiv 2024年

作者： Li, Kejia Khamdang, Chadawan Wang, Mengen Department of Electrical and Computer Engineering State University of New York at Binghamton BinghamtonNY13902 United States Materials Science and Engineering Program State University of New York at Binghamton BinghamtonNY13902 United States

CsSnI3 is widely studied as an environmentally friendly Pb-free perovskite material for optoelectronic device applications. To further improve material and device performance, it is important to understand the surface structures of CsSnI3. We generate surface structures with various stoichiometries, perform density functional theory calculations to create phase diagrams of the CsSnI3 (001), (110), and (100) surfaces, and determine the most stable surfaces under a wide range of Cs, Sn, and I chemical potentials. Under I-rich conditions, surfaces with Cs vacancies are stable, which lead to partially occupied surface states above the valence band maximum. Under I-poor conditions, we find the stoichiometric (100) surface to be stable under a wide region of the phase diagram, which does not have any surface states and can contribute to long charge carrier lifetimes. Consequently, the I-poor (Sn-rich) conditions will be more beneficial to improve the device performance. © 2024, CC BY-NC-SA.

关键词： Tin compounds

materials Discovery with Extreme Properties via Reinforcement Learning-Guided Combinatorial Chemistry

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arXiv 2023年

作者： Kim, Hyunseung Choi, Haeyeon Kang, Dongju Lee, Won Bo Na, Jonggeol School of Chemical and Biological Engineering Seoul National University Korea Republic of Department of Chemical Engineering and Materials Science Ewha Womans University Korea Republic of Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

The goal of most materials discovery is to discover materials that are superior to those currently known. Fundamentally, this is close to extrapolation, which is a weak point for most machine learning models that learn the probability distribution of data. Herein, we develop reinforcement learning-guided combinatorial chemistry, which is a rule-based molecular designer driven by trained policy for selecting subsequent molecular fragments to get a target molecule. Since our model has the potential to generate all possible molecular structures that can be obtained from combinations of molecular fragments, unknown molecules with superior properties can be discovered. We theoretically and empirically demonstrate that our model is more suitable for discovering better compounds than probability distribution-learning models. In an experiment aimed at discovering molecules that hit seven extreme target properties, our model discovered 1,315 of all target-hitting molecules and 7,629 of five target-hitting molecules out of 100,000 trials, whereas the probability distribution-learning models failed. Moreover, it has been confirmed that every molecule generated under the binding rules of molecular fragments is 100% chemically valid. To illustrate the performance in actual problems, we also demonstrate that our models work well on two practical applications: discovering protein docking molecules and HIV inhibitors. © 2023, CC BY-NC-SA.

关键词： Probability distributions

Defect formation in CsSnI3 from Density Functional Theory and Machine Learning

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arXiv 2024年

作者： Khamdang, Chadawan Wang, Mengen Department of Electrical and Computer Engineering State University of New York at Binghamton BinghamtonNY13902 United States Materials Science and Engineering Program State University of New York at Binghamton BinghamtonNY13902 United States

Sn-based perovskites as low-toxicity materials are actively studied for optoelectronic applications. However, their performance is limited by p-type self-doping, which can be suppressed by substitutional doping on the cation sites. In this study, we combine density functional theory (DFT) calculations with machine learning (ML) to develop a predictive model and identify the key descriptors affecting formation energy and charge transition levels of the substitutional dopants in CsSnI3. Our DFT calculations create a dataset of formation energies and charge transition levels and show that Y, Sc, Al, Zr, Nb, Ba, and Sr are effective dopants that pin the Fermi level higher in the band gap, suppressing the p-type self-doping. We explore ML algorithms and propose training a random forest regression model to predict the defect formation properties. This work shows the predictive capability of combining DFT with machine learning and provides insights into the important features that determine the defect formation energetics. © 2024, CC BY-NC-SA.

关键词： Perovskite

Pvc Gel-Based Electro-Adhesion on Extremely Rough Surfaces

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SSRN

SSRN 2024年

作者： Wang, Zijun Dong, Yujia Annapooranan, Raja Li, Chenghai Chambers, Robert Cai, Shengqiang Materials Science and Engineering Program University of California La Jolla San DiegoCA92093 United States Department of Mechanical and Aerospace Engineering University of California La Jolla San DiegoCA92093 United States

Electrostatic adhesion, also known as electro-adhesion, has been employed in many robotic devices for dynamic adhesion and shows fast switching between adhesive/non-adhesive states on demand. However, a well-known challenge for electro-adhesion is to achieve strong adhesion on rough surfaces with a reasonably low operating voltage. Herein, we report a simple strategy to fabricate electro-adhesion pads based on polyvinyl chloride (PVC) gel, which can achieve strong adhesion (ten times stronger than silicone rubber-based electro-adhesion pads) on rough conductive surfaces with a relatively low operating voltage ( © 2024, The Authors. All rights reserved.

关键词： Adhesion

An application of conjugate gradient technique for determination of thermal conductivity as an inverse engineering problem 3

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An application of conjugate gradient technique for determina...

3rd International Conference on Advances in Mechanical engineering and Nanotechnology, ICAMEN 2021

作者： Pandey, Vivek Bekele, Addisu Ahmed, Gulam Mohammed Sayeed Jee Kanu, Nand Singh, Gyanendra Kumar Department of Thermal and Aerospace Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia Centre of Excellence for Advanced Manufacturing Engineering Program of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia Department of Mechanical Engineering S. V. National Institute of Technology Surat India Department of Mechanical Design and Manufacturing Engineering School of Mechanical Chemical and Materials Engineering Adama Science and Technology University Adama Ethiopia

Inverse problems frequently occur when boundary conditions/thermal properties of a material are unknown, and are determined from known internal temperature measurements. A direct problem is the opposite of an inverse problem. For example, it would be the task of determining the temperature field within a material body, given boundary conditions and thermal properties. In an ill-posed, inverse problem, small variations in internal temperature measurement cause large variations in the estimated quantity such as boundary heat flux. Measured temperature variations may be due to noise, measurement error and instrumentation error, among other factors. There are various methods for solving inverse problems in materials engineering. In the paper, an inverse problem of estimating boundary heat flux for one-dimensional heat conduction is solved using the classical method of Beck and temperature dependent thermal conductivity is estimated using the more recent and advanced Conjugate Gradient method (CGM). The temperature values from the finite difference application to a direct heat transfer problem are used along with noise added to the data, in order to simulate real world, experimental conditions. The data is applied to the inverse problem of finding boundary heat flux and thermal conductivity. It is seen that Conjugate Gradient Method (CGM) along with sequential function specification method recovers the boundary heat flux and thermal conductivity quite accurately for noise levels of 1% and 2%. It is further observed that addition of future time steps stabilize the algorithm and increase accuracy of the desired results. It is also observed that CGM can recover the temperature dependent thermal conductivity quickly within few iterations, for different values of thermal conductivity function coefficients, k0and k1. CGM is found to be fast and robust when applied to one-dimensional case and can be extended to complex geometries. © 2021 Elsevier Ltd.

关键词： Inverse problems

Experiment on intrinsically nonequilibrium distribution of large ions in charged small nanopores

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arXiv 2024年

作者： Qiao, Yu Wang, Meng Program of Materials Science and Engineering University of California La Jolla San DiegoCA92093 United States Department of Structural Engineering University of California La Jolla San DiegoCA92093-0085 United States

Recent theoretical research on locally nonchaotic gravitational energy barrier led to an interesting finding: beyond the boundaries of Boltzmann’s H-theorem, there may be macroscopic systems with nontrivial energy properties. The fundamental mechanism is rooted in the intrinsically nonequilibrium steady state. In the current investigation, we experimentally verify this concept, with the weak gravitational force being changed to the strong Coulomb force. The tests are performed on capacitive cells with the same nanoporous electrodes and various electrolyte concentrations. The key characteristic is that the nanopore size is only slightly larger than the ion size, less than twice the ion size. The confinement effect of the nanopore walls plays the role of the spontaneously nonequilibrium dimension (SND). At first glance, the capacitive cells exhibit "normal" charge curves. However, their steady-state ion distribution significantly differs from thermodynamic equilibrium. The measured potential difference is nearly an order of magnitude larger than the prediction of equilibrium thermodynamics. Such phenomena are in line with the molecular dynamics simulations reported in the open literature. © 2024, CC BY.

关键词： Supercapacitor

Self-templated formation of cobalt-embedded hollow N-doped carbon spheres for efficient oxygen reduction

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Nano Research 2021年第8期14卷 2819-2825页

作者： Ayaz Mahsud Jianian Chen Xiaolei Yuan Fenglei Lyu Qixuan Zhong Jinxing Chen Yadong Yin Qiao Zhang Institute of Functional Nano&Soft Materials(FUNSOM) Jiangsu Key Laboratory for Carbon-Based Functional Materials&DevicesJoint International Research Laboratory of Carbon-Based Functional Materials and DevicesSoochow University199 Ren’ai RoadSuzhou 215123China School of Chemistry and Chemical Engineering Nantong UniversityNantong9 Seyuan RoadNantong226019China Department of Chemistry Materials Science and Engineering programand UCR Center for CatalysisUniversity of CaliforniaRiversideCA 92521USA

The slow kinetics at the cathode of oxygen reduction reaction(ORR)seriously limits the efficiencies of fuel cells and metal-air ***,the state-of-the-art ORR electrocatalyst,suffers from high cost,low earth abundance,and poor *** a self-templated strategy based on metal-organic frameworks(MOFs)is proposed for the fabrication of hollow nitrogen-doped carbon spheres that are embedded with cobalt nanoparticles(Co/HNC).The Co/HNC manifests better ORR activities,methanol tolerance,and stability than commercial Pt/*** high ORR performance of Co/NHC can be attributed to the hollow structure which provides enlarged electrochemically active surface area,the formation of more Co-N species,and the introduction of *** work highlights the significance of rational engineering of MOFs for enhanced ORR activity and stability and offers new routes to the design and synthesis of high-performance electrocatalysts.

关键词： cobalt self-templated metal organic framework hollow sphere oxygen reduction reaction

In-situ Environmental TEM Observations of Structural Evolution of Oxygenated Cu(110) in CO

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Microscopy and Microanalysis 2022年第S1期28卷 186-188页

作者： Sun, Xianhu Wang, Jianyu Chen, Xiaobo Ye, Shuonan Liang, Zhilu Yang, Judith C Zhou, Guangwen Department of Mechanical Engineering & Materials Science and Engineering Program State University of New York at Binghamton Binghamton NY USA Department of Chemical and Petroleum Engineering University of Pittsburgh Pittsburgh PA USA

HIGH-PERFORMANCE THERMOPLASTIC-BASED MAGNETIC COMPOSITES

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HIGH-PERFORMANCE THERMOPLASTIC-BASED MAGNETIC COMPOSITES

SAMPE 2023 Conference and Exhibition

作者： Arigbabowo, Oluwasola K. Tate, Jitendra Geerts, Wilhelmus J. Texas State University Materials Science Engineering and Commercialization Program 601 University Drive San MarcosTX78666 United States Ingram School of Engineering Texas State University 601 University Drive San MarcosTX78666 United States Department of Physics Texas State University 601 University Drive San MarcosTX78666 United States

ISBN: (纸本)9781934551431

Magnetic polymer-based composites combine the cost-effectiveness, low density, and manufacturing flexibility of conventional polymers with the unique characteristics of magnetic powders/fillers to form multifunctional magneto polymeric composites that offer superior properties to conventional materials. At higher temperatures, magnetic properties change significantly and the particles within the magnetic powders experience sporadic motion due to the heat which causes misalignment of the magnetic domains, leading to a decrease in magnetism. Due to these adverse temperature effects, high-performance polymers such as polyetheretherketone (PEEK), polyetherimide (PEI) or other high-temperature thermoplastics have been considered suitable matrix for the magnetic fillers, thereby creating a much wider usage for magneto polymeric composite in applications that requires higher temperature (typically above 175 oC). Thus, this review discusses the fabrication processes-injection molding, fused filament fabrication;magnetic performance, and applications of high-performance thermoplastic-based magnetic composites that can be viable for stringent engineering devices such as sensors, actuators, motors, and generators. © 2023 Soc. for the Advancement of Material and Process engineering. All rights reserved.

关键词： Fabrication