jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Oscar Bulancea-Lindvall | Joel Davidsson | Rickard Armiento | Igor A. Abrikosov
Source: arXiv (Cornell University) (preprint, 2023-04-27)
Field: Materials Science — Materials Chemistry

The Chlorine Vacancy in 4H-SiC: An NV-like Defect With Telecom Emission The diamond nitrogen vacancy (NV) center remains an ever increasing topic of interest. At present, it is considered an ideal example of a solid-state qubit applicable in quantum communication, computing, and sensing alike. With its success, the search for defects that share or improve upon its advantageous features is an ongoing endeavor. By performing large-scale high-throughput screening of 52600 defects in 4H silicon carbide (SiC), we identify a collection of NV-like color-centers of particular interest. From this list, the single most promising candidate consists of a silicon vacancy and chlorine substituted on the carbon site, and is given the name of the chlorine vacancy (ClV) center. Through high-accuracy first-principle calculations, we confirm that the ClV center is similar to the NV center in diamond in its local structure and shares many qualitative and quantitative features in the electronic structure and spin properties. In contrast to the NV center, however, the ClV center in SiC exhibits emission in the telecom range near the C-band. Diamond ; Vacancy defect ; Silicon carbide ; Nitrogen-vacancy center ; Qubit ; Materials science ; Carbon fibers ; Optoelectronics ; Physics ; Quantum ; Condensed matter physics ; Quantum mechanics Diamond and Carbon-based Materials Research ; Silicon Carbide Semiconductor Technologies ; Semiconductor materials and devices
Authors: T. Knoke | S. Kinnewig | S. Beuchler | A. Demircan | U. Morgner | T. Wick
Source: arXiv (Cornell University) (preprint, 2023-03-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Domain Decomposition with Neural Network Interface Approximations for time-harmonic Maxwell's equations with different wave numbers In this work, we consider the time-harmonic Maxwell's equations and their numerical solution with a domain decomposition method. As an innovative feature, we propose a feedforward neural network-enhanced approximation of the interface conditions between the subdomains. The advantage is that the interface condition can be updated without recomputing the Maxwell system at each step. The main part consists of a detailed description of the construction of the neural network for domain decomposition and the training process. To substantiate this proof of concept, we investigate a few subdomains in some numerical experiments with low frequencies. Therein the new approach is compared to a classical domain decomposition method. Moreover, we highlight current challenges of training and testing with different wave numbers and we provide information on the behaviour of the neural-network, such as convergence of the loss function, and different activation functions. Artificial neural network ; Domain decomposition methods ; Domain (mathematical analysis) ; Interface (matter) ; Convergence (economics) ; Feedforward neural network ; Maxwell's equations ; Time domain ; Computer science ; Frequency domain ; Harmonic ; Decomposition ; Decomposition method (queueing theory) ; Algorithm ; Mathematics ; Mathematical analysis ; Physics ; Artificial intelligence ; Acoustics ; Finite element method Magnetic Properties and Applications ; Electromagnetic Simulation and Numerical Methods ; Model Reduction and Neural Networks
Authors: Chinnasami Sivaji | Prabakaran Nanjundan | M Ramachandran | Jaganathan Rajamanickam | Lizhen Huang | Guri Krigsvoll | Fred Johansen | Yongping Liu | Xiaoling Zhang | W Strassmann | Paul | Sreedhar Raju | S Balaguru | Surjit Bawa | Singh | Matthias Buyle | Johan Braet | Amaryllis Audenaert | S Aswini | S Tharaniya | R Joey Persul | B Avinash | P Lingam | Kogila | Les Ruddock | Jorge Lopes | Mehdi Fuladipanah | H Azamathulla | Ozgur Kisi | Mehdi Kouhdaragh | Vishwandham Mandala | Andrew Dainty | Alan Bryman | Andrew Df Price | Abdullateef Olanrewaju | Seong Yeow Tan | Lee Kwan | Menoka Bal | David Bryde | Damian Fearon | Edward Ochieng | Patricia Carrillo | J Venkataramana | V Akshaya | Vishwanadham Mandala | P Chunduru Anilkumar | R Vishnuraja | Aarthi | Kogila Palanimuthu | Leta Birhanu Gutu | Buliyohannis Tesfaye | Yoseph Tasisa | Melkamu Shiferaw Belayneh | Desalegn Tamiru | Shiferaw | M Sangeetha Rajkumar | Vimala Ramachandran | Prabakaran Saravanan | Nanjundan | Wesam Alaloul | Muhammad Salah | Muhammad Ali Musarat | Ali Babar | Qaiser Rabbani | Ahsen Iqbal | Waqas Maqsoom | Farooq | Venkata Ponnada | Tulasiramu | Sv Naga | Srinivasu | Yirgalem Tasisa | Kogila Bekele | Palanimuthu | Sujatha Sridharan | Ambika Zutshi | Andrew Creed | Martin Betts | Lim Cher | Krishan Mathur | George Ofori | Jill Wells | L Jisha | P Jayaprabha | S Gnanawel | K Gowtham | P Kumar | N Diwakar | Suseela Sellamuthu | Srinivas Vaddadi | Srinivas Venkata | Hemant Petwal | Ravi Hosur | R Vishwanadham Mandala | Jagendra Dhanapal
Source: Journal on Applied and Chemical Physics (article, 2023-09-20)
Field: Materials Science — Polymers and Plastics

Optimal Selection of Cotton Fabrics: A WASPAS Method Approach Always used for cotton-rich materials. WASPAS Cotton Fabric Selection in this paper, “the WASPAS method, a relatively fresh and computationally powerful MCDM (Multi-Criteria Decision Making) tool”, is suggested to rank ten candidate cotton fabrics according to four cloth properties such as: “cover, thickness, area density, and permeability”. The suggested fabrics are evaluated and chosen in order to achieve the best thermal comfort characteristics. “Sample Number 3 ranks first (best option) with the highest evaluation score of 0.95281, while Sample Number 6 ranks tenth with the lowest evaluation score of 0.50685.” The proposed method's ranking results demonstrate a substantial agreement in ranking with previous approaches, as evidenced by the extremely high standard coefficients of correlation. With rank coefficients of correlation higher than 0.90, the ranking methods provided by the four hypothetical weight sets have the highest degree of agreement. Furthermore, even if the original making choices team is changed, that will be no rank reversal. As a result, sensitivity analyses based on altering criterion weights and the impact of dynamic matrices improve the proposed approach's stability and robustness in terms of ranking success. Selection (genetic algorithm) ; Computer science ; Agricultural engineering ; Materials science ; Business ; Artificial intelligence ; Engineering Textile materials and evaluations ; Optimization and Packing Problems
Authors: Jordan Maximov | Galya Duncheva | Angel Anchev | Vladimir Dunchev | Vladimir Todorov | Yaroslav Argirov
Source: Metals (article, 2023-11-24)
Field: Materials Science — Materials Chemistry

Influence of an Ageing Heat Treatment on the Mechanical Characteristics of Iron-Aluminium Bronzes with β-Transformation Obtained via Centrifugal Casting: Modelling and Optimisation Aluminium bronzes possess a unique combination of high strength and wear and corrosion resistance in aggressive environments; thus, these alloys find wide application in marine, shipbuilding, aviation, railway, offshore platform applications and other fields. Iron-aluminium bronzes (IABs) are the cheapest and most widely used. When the aluminium content is above 9.4 wt%, IAB is biphasic (i.e., it undergoes β-transformation) and can be subjected to all heat-treatment types, depending on the desired operating behaviour of the bronze component. This article presents correlations (mathematical models) between the primary mechanical characteristics (yield limit, tensile strength, elongation, hardness and impact toughness) and the ageing temperature and time of quench at 920 °C in water of Cu-11Al-6Fe bronze, obtained using the centrifugal casting method. The microstructure evolution was evaluated depending on the ageing temperature and time changes. Overall, the research was conducted in three successive inter-related stages: a one-factor-at-a-time study, planned experiment, and optimisations. Four optimisation tasks, which have the greatest importance for practice, were formulated and solved. The defined multiobjective optimisation tasks were solved by searching for the Pareto-optimal solution approach. The decisions were made through a nondominated sorting genetic algorithm (NSGA-II) using QstatLab. The optimisation results were verified experimentally. Additional samples were made for this purpose, quenched at 920 °C in water and subjected to subsequent ageing with the optimal values of the governing factors (ageing temperature and time) for the corresponding optimisation task. The comparison of the results for the mechanical characteristics with the theoretical optimisation results presents a good agreement. Aluminium ; Materials science ; Ultimate tensile strength ; Metallurgy ; Casting ; Toughness ; Ageing ; Corrosion ; Quenching (fluorescence) ; Multi-objective optimization ; Brass ; Computer science ; Copper Metallurgy and Material Science ; Aluminum Alloy Microstructure Properties ; Additive Manufacturing Materials and Processes
Authors: A. Mark Payne | Haoyang Wu | Hao‐Wei Pang | Colin A. Grambow | Duminda S. Ranasinghe | Xiaorui Dong | Alon Grinberg Dana | William H. Green
Source: ChemRxiv (preprint, 2023-10-20)
Field: Materials Science — Materials Chemistry

Towards Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions To obtain accurate enthalpies of formation of a chemical species, Hf, one needs a procedure to quantitatively connect the results from quantum mechanical (QM) calculations with the experimental enthalpies of elements in their standard state, often along with additional empirical corrections. Although QM methods continue to improve, accuracy gains from new methods are usually realized if the calculations for Hf are properly corrected. One such approach is to use atomization energy corrections (AECs) followed by bond additivity corrections (BACs), such as those defined by Petersson et al. or Anantharaman and Melius. Another approach is to utilize isodesmic reactions (IDRs) which are error-canceling reactions that can be constructed systematically as shown by Buerger et al. In this work, we implement all of these approaches in Arkane, an open-source software that can calculate species thermochemistry from computations done by a wide variety of QM software packages. As part of this work, we curate a diverse database of over 400 reference species from the available literature for use in fitting BACs or to participate in IDRs, and also provide AECs and BACs for 15 commonly used levels of theory using the workflow implemented. When comparing the approaches, we find that both BAC types yield results of similar accuracy, though the Anantharaman and Melius-type BACs seem to generalize better. Further, although the IDRs approach is often as accurate as the BAC approaches and sometimes even more advantageous, we find that this method appears to be less robust than the BAC methods. In particular, the accuracy of the IDRs approach is sensitive to the chosen reference species and reactions. Therefore, in addition to providing the automated AECs and BACs fitting procedure, we also propose improved methods to select IDRs. Isodesmic reaction ; Thermochemistry ; Workflow ; Computer science ; Additive function ; Quantum ; Software ; Quantum chemical ; Bond energy ; Python (programming language) ; Computational science ; Computational chemistry ; Algorithm ; Statistical physics ; Chemistry ; Mathematics ; Density functional theory ; Physics ; Physical chemistry ; Molecule ; Quantum mechanics Machine Learning in Materials Science ; Chemical Thermodynamics and Molecular Structure ; Thermal and Kinetic Analysis
Authors: Thu Ha Nguyen | Yongcheng Mu | Jiangwen Sun | Jing He
Source:  (article, 2023-09-03)
Field: Materials Science — Materials Chemistry

An Approach to Developing Benchmark Datasets for Protein Secondary Structure Segmentation from Cryo-EM Density Maps More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5-10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study the effect of secondary structure content and data quality on the performance of DeepSSETracer, a deep learning method that segments regions of protein secondary structures from cryo-EM map components. Results show that various content levels in the secondary structure and data quality influence the performance of segmentation for DeepSSETracer. Segmentation ; Benchmark (surveying) ; Computer science ; Artificial intelligence ; Deep learning ; Test data ; Protein secondary structure ; Quality (philosophy) ; Set (abstract data type) ; Pattern recognition (psychology) ; Data set ; Data mining ; Test set ; Image segmentation Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Genomics and Phylogenetic Studies
Authors: Mihai Vrabie | CAFTANACHI MIHAELA | Cretescu Igor | María Harja
Source: Journal of International Scientific Publications : Ecology & Safety. (article, 2023-01-01)
Field: Materials Science — General Materials Science

THE USE OF WATER REDUCING ADDITIVES FOR DEVELOPMENT OF NEW ECOLOGICAL AND HIGH-PERFORMANCE MATERIALS The decreasing amount of the world's water supply is a significant issue nowadays. Global warming is one of the key factors contributing to the increasing loss of water supplies, but wasteful water usage for domestic and industrial use is also a major factor. Environmental science ; Ecology ; Biochemical engineering ; Biology ; Engineering Material Properties and Applications
Authors: I.M. van Damme | P. Mestres-Fitó | H.J. Ramaker | A.W.C. van Hulsbergen | A.E.D.M. van der Heijden | R.F. Kranenburg | A.C. van Asten
Source: TNO Repository (article, 2023-01-01)
Field: Chemistry — Spectroscopy

Rapid and on-scene chemical identification of intact explosives with portable near-infrared spectroscopy and multivariate data analysis There is an ongoing forensic and security need for rapid, on-scene, easy-to-use, non-invasive chemical identification of intact energetic materials at pre-explosion crime scenes. Recent technological advances in instrument miniaturization, wireless transfer and cloud storage of digital data, and multivariate data analysis have created new and very promising options for the use of near-infrared (NIR) spectroscopy in forensic science. This study shows that in addition to drugs of abuse, portable NIR spectroscopy with multivariate data analysis also offers excellent opportunities to identify intact energetic materials and mixtures. NIR is able to characterize a broad range of chemicals of interest in forensic explosive investigations, covering both organic and inorganic compounds. NIR characterization of actual forensic casework samples convincingly shows that this technique can handle the chemical diversity encountered in forensic explosive investigations. The detailed chemical information contained in the 1350–2550 nm NIR reflectance spectrum allows for correct compound identification within a given class of energetic materials, including nitro-aromatics, nitro-amines, nitrate esters, and peroxides. In addition, the detailed characterization of mixtures of energetic materials, such as plastic formulations containing PETN (pentaerythritol tetranitrate) and RDX (trinitro triazinane), is feasible. The results presented illustrate that the NIR spectra of energetic compounds and mixtures are sufficiently selective to prevent false-positive results for a broad range of food-related products, household chemicals, raw materials used for the production of home-made explosives, drugs of abuse, and products that are sometimes used to create hoax improvised explosive devices. However, for frequently encountered pyrotechnic mixtures, such as black powder, flash powder, and smokeless powder, and some basic inorganic raw materials, the application of NIR spectroscopy remains challenging. Another challenge is presented by casework samples of contaminated, aged, and degraded energetic materials or poor-quality HMEs (home-made explosives), for which the spectral signature deviates significantly from the reference spectra, potentially leading to false-negative outcomes. Explosive material ; Forensic identification ; Identification (biology) ; Spectroscopy ; Near-infrared spectroscopy ; Chemometrics ; Characterization (materials science) Mass Spectrometry Techniques and Applications ; Forensic Fingerprint Detection Methods ; Spectroscopy and Chemometric Analyses
Authors: Tristan Madeleine | Nina Podoliak | Oleksandr Buchnev | Ingrid Membrillo Solis | G. D’Alessandro | Jacek Brodzki | Malgosia Kaczmarek
Source: arXiv (Cornell University) (preprint, 2023-06-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Topological learning for the classification of disorder: an application to the design of metasurfaces Structural disorder can improve the optical properties of metasurfaces, whether it is emerging from some large-scale fabrication methods, or explicitly designed and built lithographically. Correlated disorder, induced by a minimum inter-nanostructure distance or by hyperuniformity properties, is particularly beneficial in some applications such as light extraction. We introduce numerical descriptors inspired from topology to provide quantitative measures of disorder whose universal properties make them suitable for both uncorrelated and correlated disorder, where statistical descriptors are less accurate. We prove theoretically and experimentally the accuracy of these topological descriptors of disorder by using them to design plasmonic metasurfaces of controlled disorder, that we correlate to the strength of their surface lattice resonances. These tools can be used for the fast and accurate design of disordered metasurfaces, or to help tuning large-scale fabrication methods. Uncorrelated ; Lattice (music) ; Fabrication ; Topology (electrical circuits) ; Nanostructure ; Computer science ; Scale (ratio) ; Materials science ; Nanotechnology ; Physics ; Mathematics ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Plasmonic and Surface Plasmon Research
Authors: Srinivisan Mahendran | Jesús Carrete | Andreas Isacsson | Georg K. H. Madsen | Paul Erhart
Source: arXiv (Cornell University) (preprint, 2023-10-13)
Field: Materials Science — Materials Chemistry

Quantitative predictions of the thermal conductivity in transition metal dichalcogenides: The impact of point defects in MoS$_2$ and WS$_2$ monolayers Transition metal dichalcogenides are investigated for various applications at the nanoscale thanks to their unique combination of properties and dimensionality. For many of the anticipated applications, heat conduction plays an important role. At the same time, these materials often contain relatively large amounts of point defects. Here, we provide a systematic analysis of the impact of intrinsic and selected extrinsic defects on the lattice thermal conductivity of MoS$_2$ and WS$_2$ monolayers. We combine Boltzmann transport theory and the Green's function-based T-matrix approach for the calculation of scattering rates. The force constants for the defect configurations are obtained from density functional theory calculations via a regression approach, which allows us to sample a rather large number of defects at a moderate computational cost and to systematically enforce both the translational and rotational acoustic sum rules. The calculated lattice thermal conductivity is in quantitative agreement with experimental data for heat transport and defect concentrations for both MoS$_2$ and WS$_2$. Crucially, this demonstrates that the strong deviation from a 1/T-temperature dependence of the lattice thermal conductivity observed experimentally, can be fully explained by the presence of point defects. We furthermore predict the scattering strengths of the intrinsic defects to decrease in the sequence $V_{Mo}\approx V_{2S}^=&gt;V_{2S}^\perp&gt;V_S&gt;S_{ad}$ in both materials, while the scattering rates for the extrinsic (adatom) defects decrease with increasing mass such that Li$_{ad}$&gt;Na$_{ad}$&gt;K$_{ad}$. Compared to earlier work, we find that both intrinsic and extrinsic adatoms are relatively weak scatterers. We attribute this difference to the treatment of the translational and rotational acoustic sum rules, which if not enforced can lead to spurious contributions in the zero-frequency limit. Condensed matter physics ; Thermal conductivity ; Scattering ; Monolayer ; Materials science ; Thermal conduction ; Conductivity ; Density functional theory ; Crystallographic defect ; Lattice (music) ; Boltzmann equation ; Thermodynamics ; Chemistry ; Physics ; Nanotechnology ; Computational chemistry ; Quantum mechanics ; Physical chemistry 2D Materials and Applications ; Machine Learning in Materials Science ; Advanced Chemical Physics Studies
Authors: Ömer Tuğşad Birinci
Source:  (article, 2023-01-01)
Field: Materials Science — Polymers and Plastics

Temiz Kumlarda Dinamik Yükleme Sonucu Aşırı Boşluk Suyu Basıncı Oranı Değişiminin LSTM Sinir Ağı İle Tahmin Edilmesi Niigata depreminden sonra zemin dinamii zerine olan aratrmalarn younlat zemin svlamas iin olduka fazla miktarda teorik Geology Textile materials and evaluations
Authors: Ashesh Ghosh
Source: arXiv (Cornell University) (preprint, 2023-03-29)
Field: Materials Science — Materials Chemistry

Importance of Many Particle Correlations to the Collective Debye-Waller Factor in a Single-Particle Activated Dynamic Theory of the Glass Transition We theoretically study the importance of many body correlations on the collective Debye Waller (DW) factor in the context of the Nonlinear Langevin Equation (NLE) single particle activated dynamics theory of glass transition and its extension to include collective elasticity (ECNLE theory). This microscopic force-based approach envisions structural alpha relaxation as a coupled local-nonlocal process involving correlated local cage and longer range collective barriers. The crucial question addressed here is the importance of the deGennes narrowing contribution versus a literal Vineyard approximation for the collective DW factor that enters the construction of the dynamic free energy in NLE theory. While the Vineyard-deGennes approach-based NLE theory and its ECNLE theory extension yields predictions that agree well with experimental and simulation results, use of a literal Vineyard approximation for the collective DW factor massively overpredicts the activated relaxation time. The current study suggests many particle correlations are crucial for a reliable description of activated dynamics theory of model hard sphere fluids. Statistical physics ; Physics ; Context (archaeology) Material Dynamics and Properties ; Theoretical and Computational Physics ; Advanced Thermodynamics and Statistical Mechanics