jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Anna N. Morozovska | Sergei V. Kalinin | Mykola E. Yelisieiev | Jonghee Yang | Mahshid Ahmadi | Eugene А. Eliseev | Dean R. Evans
Source: arXiv (Cornell University) (preprint, 2022-02-24)
Field: Chemistry — Physical and Theoretical Chemistry

Dynamic control of ferroionic states in ferroelectric nanoparticles The polar states of uniaxial ferroelectric nanoparticles interacting with a surface system of electronic and ionic charges with a broad distribution of mobilities is explored, which corresponds to the experimental case of nanoparticles in solution or ambient conditions. The nonlinear interactions between the ferroelectric dipoles and surface charges with slow relaxation dynamics in an external field lead to the emergence of a broad range of paraelectric-like, antiferroelectric-like ionic, and ferroelectric-like ferroionic states. The crossover between these states can be controlled not only by the static characteristics of the surface charges, but also by their relaxation dynamics in the applied field. Obtained results are not only promising for advanced applications of ferroelectric nanoparticles in nanoelectronics and optoelectronics, they also offer strategies for experimental verification. Ferroelectricity ; Materials science ; Nanoparticle ; Dielectric ; Dipole ; Ionic bonding ; Relaxation (psychology) ; Condensed matter physics ; Antiferroelectricity ; Polar ; Chemical physics ; Nanotechnology ; Polarization (electrochemistry) ; Optoelectronics ; Chemistry ; Physics ; Ion ; Physical chemistry Electrostatics and Colloid Interactions ; Ferroelectric and Piezoelectric Materials ; Liquid Crystal Research Advancements
Authors: Q. Zou
Source: Institutional Repositories DataBase (IRDB) (article, 2022-09-01)
Field: Chemistry — Organic Chemistry

Discovery of subnanoparticles for multi-electron transfer reaction Alloy subnanoparticles, as a new class of nanomaterial, have attracted much attention due to their potential for excellent catalysts.The unique properties and application of SNPs remain to be discovered.However, because of the myriad compositions of alloy sub-nanoparticles, it is not easy to study them comprehensively.Recently, AI (Artificial intelligence) technology is permeating into every traditional field.For example, AI chemistry has become a hot topic realizing high-throughput material discovery.The interdisciplinary field of subnano-science and AI may provide vast novel materials that allow providing solutions to various social problems.Based on such conditions, my doctoral research was carried out. Yield (engineering) ; Work (physics) ; Process (computing) ; Transfer (computing) Radical Photochemical Reactions ; Electron Spin Resonance Studies ; Photochemistry and Electron Transfer Studies
Authors: Hyeon wook Lim | Young sam Kim | Kyu-jin Jo | Seok-Choi | Chang Woo Lee | Dasol Kim | Ki hyeon Kwon | Hoe don Kwon | Soo bin Hwang | Byung‐Joon Choi | Cheol‐Woong Yang | Eun Ji Sim | Mann–Ho Cho
Source: arXiv (Cornell University) (preprint, 2022-09-30)
Field: Materials Science — Materials Chemistry

Advanced interfacial phase change material: structurally confined and interfacially extended superlattice Interfacial Phase Change Memory (iPCM) retrench unnecessary power consumption due to wasted heat generated during phase change by reducing unnecessary entropic loss. In this study, an advanced iPCM (GeTe/Ti-Sb2Te3 Superlattice) is synthesized by doping Ti into Sb2Te3. Structural analysis and density functional theory (DFT) calculations confirm that bonding distortion and structurally well-confined layers contribute to improve phase change properties in iPCM. Ti-Sb2Te3 acts as an effective thermal barrier to localize the generated heat inside active region, which leads to reduction of switching energy. Since Ge-Te bonds adjacent to short and strong Ti-Te bonds are more elongated than the bonds near Sb-Te, it is easier for Ge atoms to break the bond with Te due to strengthened Peierls distortions (Rlong/Rshort) during phase change process. Properties of advanced iPCM (cycling endurance, write speed/energy) exceed previous records. Moreover, well-confined multi-level states are obtained with advanced iPCM, showing potential as a neuromorphic memory. Our work paves the way for designing superlattice based PCM by controlling confinement layers. Superlattice ; Phase-change memory ; Materials science ; Neuromorphic engineering ; Phase (matter) ; Distortion (music) ; Work (physics) ; Density functional theory ; Thermoelectric effect ; Condensed matter physics ; Optoelectronics ; Nanotechnology ; Computer science ; Thermodynamics ; Layer (electronics) ; Computational chemistry ; Chemistry ; Physics Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing ; Transition Metal Oxide Nanomaterials
Authors: Dandan Liu | Han Yang | Bin Wang | Stephen Grigg
Source: e-Journal of Nondestructive Testing (article, 2022-12-19)
Field: Materials Science — Metals and Alloys

Hydrogen induced cracks monitored with acoustic emission under the laboratory condition Hydrogen induced cracking (HIC) is a common form of failure in steel exposed to hydrogen rich environments, which always occurs inside material making their detection difficult. Acoustic Emission (AE) is a promising Nondestructive Evaluation technique for crack detection. However, it is challenging to distinguish the signals generated from HIC, corrosions and bubbles. In this study, these mixed AE signals were obtained by electrochemical hydrogen charging on A516 carbon steel with the solution of 0.5 mol/L H2SO4 and 0.5 g/L NaAsO2. Microstructures of the sample’s cross-section were observed to verify the existence of HIC. moreover, separate signals of bubbles and corrosions were acquired from just exposures to 0.5 mol/L H2SO4. After analyzing, key parameters from the AE signals, i.e. the peak frequency, the spectrum gravity, the duration and energy, were identified to differentiate the source mechanisms. Results show that the peak frequency and the spectrum gravity of corrosion signals are higher than those of HIC and bubbles, while the duration and energy of HIC signals are higher than those of the other two kinds of signals. To reduce manual operations, the unsupervised learning algorithms, Principal Components Analysis (PCA) and K-means, were used for clustering, for further understanding of these clusters and their evolution with time. Acoustic emission ; Hydrogen ; Cracking ; Materials science ; Corrosion ; Microstructure ; SIGNAL (programming language) ; Hydrogen sensor ; Energy (signal processing) ; Composite material ; Acoustics ; Analytical Chemistry (journal) ; Computer science ; Chemistry ; Physics Hydrogen embrittlement and corrosion behaviors in metals ; Non-Destructive Testing Techniques ; Corrosion Behavior and Inhibition
Authors: Sana Bougueroua | Ylène Aboulfath | Dominique Barth | Marie‐Pierre Gaigeot
Source: ChemRxiv (preprint, 2022-10-27)
Field: Chemistry — Spectroscopy

Algorithmic graph theory for post-processing molecular dynamics trajectories This paper reviews some of the graph theory-based methods that were recently developed in our group for post-processing molecular dynamics trajectories. We show that the use of algorithmic graph theory not only provides a direct and fast methodology to identify conformers that are sampled over time, but it also allows to follow in time the interconversions between the conformers through graphs of transitions, also provides statistical characterizations, that would otherwise be hard to obtain. Examples for a gas phase peptide and for the more complex inhomogeneous charged air-liquid water interface are presented in order to demonstrate the power of topological 2D-graphs and their versatility and transferability. Computer science ; Transferability ; Conformational isomerism ; Graph theory ; Molecular dynamics ; Graph ; Theoretical computer science ; Statistical physics ; Topology (electrical circuits) ; Computational chemistry ; Mathematics ; Chemistry ; Molecule ; Physics ; Machine learning ; Combinatorics ; Quantum mechanics Mass Spectrometry Techniques and Applications ; Spectroscopy and Quantum Chemical Studies ; Origins and Evolution of Life
Authors: Viki Kumar Prasad | Alberto Otero‐de‐la‐Roza | Gino A. DiLabio
Source: ChemRxiv (preprint, 2022-02-21)
Field: Materials Science — Materials Chemistry

Small basis set density-functional theory methods corrected with atom-centered potentials Density-functional theory (DFT) is currently the most popular method for modeling non-covalent interactions and thermochemistry. The accurate calculation of non-covalent interaction energies, reaction energies, and barrier heights requires choosing an appropriate functional and, typically, a relatively large basis set. Deficiencies of the density-functional approximation and the use of a limited basis set are the leading sources of error in the calculation of non-covalent and thermochemical properties in molecular systems. In this article, we present three new DFT methods based on the BLYP, M062X and CAM-B3LYP functionals in combination with the 6-31G* basis set and corrected with atom-centered potentials (ACPs). ACPs are one-electron potentials that have the same form as effective-core potentials, except they do not replace any electrons. The ACPs developed in this work are used to generate energy corrections to the underlying DFT/basis-set method such that the errors in predicted chemical properties are minimized while maintaining the low computational cost of the parent methods. ACPs were developed for the elements H, B, C, N, O, F, Si, P, S, and Cl. The ACP parameters were determined using an extensive training set of 118,655 data points, mostly of complete basis set coupled-cluster level quality. The target molecular properties for the ACP-corrected methods include non-covalent interaction energies, molecular conformational energies, reaction energies, barrier heights, and bond separation energies. The ACPs were tested first on the training set and then on a validation set of 42,567 additional data points. We show that the ACP-corrected methods can predict the target molecular properties with accuracy close to complete basis set wavefunction theory methods, but at a computational cost of double-ζ DFT methods. This makes the new BLYP/6-31G*-ACP, M062X/6-31G*-ACP, and CAM-B3LYP/6-31G*-ACP methods uniquely suited to the calculation of non-covalent, thermochemical, and kinetic properties in large molecular systems. Basis set ; Density functional theory ; Basis (linear algebra) ; Thermochemistry ; Atom (system on chip) ; Coupled cluster ; Covalent bond ; Set (abstract data type) ; Work (physics) ; Computational chemistry ; Chemistry ; Cluster (spacecraft) ; Atomic physics ; Molecule ; Statistical physics ; Physics ; Thermodynamics ; Quantum mechanics ; Mathematics ; Computer science ; Physical chemistry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Thermal and Kinetic Analysis
Authors: Xinyan Zhang | Jialin Chen | Ruoxi Chen | Chan Wang | Tong Cai | Hongsheng Chen | Lin Xiao
Source: arXiv (Cornell University) (preprint, 2022-11-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A perspective on meta-boundaries The judicious design of electromagnetic boundary provides a crucial route to control light-matter interactions, and it is thus fundamental to basic science and practical applications. General design approaches rely on the manipulation of bulk properties of superstrate or substrate and on the modification of boundary geometries. Due to the recent advent of metasurfaces and low-dimensional materials, the boundary can be flexibly featured with a surface conductivity, which can be rather complex but provide an extra degree of freedom to regulate the propagation of light. In this perspective, we denote the boundary with a non-zero surface conductivity as the meta-boundary. The meta-boundaries are categorized into four types, namely isotropic, anisotropic, biisotropic and bianisotropic meta-boundaries, according to the electromagnetic boundary conditions. Accordingly, the latest development for these four kinds of meta-boundaries are reviewed. Finally, an outlook on the research tendency of meta-boundaries is provided, particularly on the manipulation of light-matter interactions by simultaneously exploiting meta-boundaries and metamaterials. Boundary (topology) ; Isotropy ; Metamaterial ; Perspective (graphical) ; Boundary value problem ; Computer science ; Physics ; Theoretical physics ; Geometry ; Mathematics ; Optics ; Mathematical analysis Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Advanced Antenna and Metasurface Technologies
Authors: Onkar Lotlikar | Dhwani Kapadia | Sreela Dasgupta
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2022-10-08)
Field: Chemistry — Analytical Chemistry

PFAS Degradation Techniques – A Road towards Alleviating Organic Pollution <strong>ABSTRACT: </strong>PFAS are commonly found pollutants in soil and water bodies. Of all the PFAS that are found, PFOA and PFOS are the most hazardous ones. The review focuses upon Adsorption, Sonochemical Degradation, Photocatalysts, and Bio-remediation as techniques for the removal and degradation of PFA. Degradation (telecommunications) ; Environmental science ; Pollution ; Environmental planning ; Environmental protection ; Computer science ; Telecommunications Analytical chemistry methods development ; Per- and polyfluoroalkyl substances research
Authors: Connor Hainje | Cody A. Nizinski | SL Jackson | Richard E. Clark | Forrest D. Heller | Ian J. Schwerdt | Buck, Edgar | David Meier | Alexander Hagen
Source: arXiv (Cornell University) (preprint, 2022-12-01)
Field: Materials Science — Materials Chemistry

Investigation of process history and phenomenology of plutonium oxides using vector quantizing variational autoencoder Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO2) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample. Scanning electron microscope ; Materials science ; Biological system ; Autoencoder ; Phenomenology (philosophy) ; Particle (ecology) ; Computer science ; Artificial intelligence ; Pattern recognition (psychology) ; Artificial neural network ; Composite material ; Geology Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Radioactive element chemistry and processing
Authors: Zheng Li | Jin Xue | Marc de | Jaehwan Kim | Hao Nong | Daniel Chong | Khee Yong Lim | Elgin Quek | Rajeev J. Ram
Source: Research Square (preprint, 2022-09-06)
Field: Materials Science — Materials Chemistry

A sub-wavelength Si LED integrated in a CMOS platform Optoelectronics ; CMOS ; Wavelength ; Materials science ; Light-emitting diode Silicon Nanostructures and Photoluminescence ; Photonic and Optical Devices ; Thin-Film Transistor Technologies
Authors: Emily Franklin | Hannes Röst
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-03-04)
Field: Chemistry — Spectroscopy

Comparing Machine Learning Architectures for the Prediction of Peptide Collisional Cross Section 1 Abstract Mass spectrometry is the method of choice in large-scale proteomics studies. One common method is data-independent acquisition (DIA), which allows for high-throughput analysis of biological samples, but also produces complex data. Methods of peptide separation, in addition to retention time, improve data analysis and there has been increasing interest in separating peptides based on collisional cross section (CCS), which is a measure of the size of a peptide. However, existing libraries that are used during data analysis lack CCS measurements, and this data is expensive and time-consuming to acquire. This has led to the desire to predict library values for mass spectrometry analysis. Here we compare three deep learning architectures, LSTM, CNN, and transformer, for the tasks of retention time and collisional cross section prediction. We show that the LSTM and CNN models perform similarly and that the transformer has a lower performance than expected. Computer science ; Transformer ; Deep learning ; Mass spectrometry ; Artificial intelligence ; Data mining ; Machine learning ; Chemistry ; Chromatography ; Engineering Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography
Authors: Jean‐Louis Bobet | Q. Gouty | F. J. Castro | G. Urretavizcaya | Jocelyn Sabatier
Source: SSRN Electronic Journal (article, 2022-01-01)
Field: Materials Science — General Materials Science

Experimental and Theoretical Approach of the Hydrolysis of Pelleted Magnesium Alloys Scraps Magnesium ; Hydrolysis ; Metallurgy ; Pulp and paper industry ; Chemistry ; Biochemical engineering ; Materials science ; Process engineering ; Food science ; Engineering ; Organic chemistry Material Properties and Applications
Authors: Leonard M. Akuwueke | Chinwuba Victor Ossia | Harold U. Nwosu
Source: Proceedings on Engineering Sciences (article, 2022-05-05)
Field: Materials Science — Polymers and Plastics

OPTIMIZATION OF THE MECHANICAL PROPERTIES OF CHEMICALLY ACTIVATED CARBON COMPOSITES IN ORGANIC FRICTION LININGS BY BOX-BEHNKEN DESIGN This study presents the development and physicomechanical optimization of friction lining composites from organic chemically activated carbon. Three types of chemically activated carbon from palm kernel shells (PKS) and coconut shell (CS) giving 3 volumetric ratios of CS (XCS) with 3 particle sizes (XPS) and 3 reinforcement weight concentrations (XWT). The composites were experimentally evaluated for mechanical properties (flexural strength FS, tensile strength TS, hardness H and density D) performance using box-behnken design. ANOVA was used to determine the effects of XPS, XCS and XWT. Results showed that all properties exhibited positive main effects from XPS of order > > > , and a positive XPS and XCS interaction. All properties except hardness exhibited negative XPS and XWT , negative XWT and XCS, and positive XPS and XCS interactions. All, except hardness, showed all positive quadratic effect from XPS, XWT and XCS. The experimental and predicted values showed little or no difference. The friction lining composites optimal properties obtained include: hardness = 87.375 at = 8%wt, = 100%, = 60; density = 0.97/ 3 at = 100%, = 60 and = 4%wt = 39.97696; at = 93.33%, = 150, = 4% and = 28.65 at = 100%, = 150, = 4%. Hence, all the process variables were relevant for the development of friction-linings using agro-wastes chemically activated carbon. X-ray photoelectron spectroscopy ; Materials science ; Box–Behnken design ; Composite material ; Carbon fibers ; Flexural strength ; Ultimate tensile strength ; Response surface methodology ; Chemical engineering ; Composite number ; Chemistry ; Chromatography Natural Fiber Reinforced Composites ; Tribology and Wear Analysis ; Soil Mechanics and Vehicle Dynamics
Authors: Md. Ariful Islam
Source: American Journal of Advanced Technology and Engineering Solutions (article, 2022-12-01)
Field: Materials Science — Materials Chemistry

IRRADIATION-ENHANCED CREEP–FATIGUE INTERACTION IN HIGH-TEMPERATURE AUSTENITIC STEEL: CURRENT UNDERSTANDING AND CHALLENGES This study presents a comprehensive quantitative assessment of irradiation-enhanced creep–fatigue interaction in high-temperature austenitic stainless steels (304/304L, 316/316L/316H/316LN, and 347H), materials that anchor nuclear, petrochemical, and advanced power infrastructures. Creep–fatigue interaction the concurrent action of time-dependent creep and cyclic plasticity becomes critically accelerated under neutron irradiation, which alters microstructural pathways through hardening, dislocation channeling, and radiation-induced segregation. To quantify these coupled effects, a cross-sectional, case-based dataset of 168 tests across 12 campaigns was curated, harmonizing variables for dose (dpa), test temperature, strain range, tensile-hold duration, environment, and metallurgy. Multiple linear and mixed-effects regressions were pre-specified to estimate adjusted associations between these predictors and log life (ln Nf), explicitly testing irradiation–temperature (dose×T) and irradiation–dwell (dose×hold) interactions. Energy-augmented models incorporating cycle-resolved hysteresis and creep work were used to link statistical effects to physical damage mechanisms, while an expert Likert survey (n = 18) independently captured practitioner consensus on variable salience and data quality constraints. Results demonstrate that dose, temperature, strain range, and tensile hold each impose statistically significant, independent life penalties. Two interactions dominate: higher temperature steepens the life reduction per unit dose (negative dose×T), and irradiation amplifies dwell sensitivity (negative dose×hold). Metallurgical stabilization offers a modest but significant attenuation of irradiation-related life debit. Energy-augmented extensions confirm that increased creep power during tensile holds correlates with reduced life, aligning regression coefficients with mechanistic expectations. Cross-validation, penalized stability checks, and environment-stratified analyses verify the robustness of these findings, with stronger dwell penalties observed in oxidizing atmospheres. Expert ratings converge with quantitative results, underscoring the high salience of irradiation dose, temperature coupling, and dwell-time effects. The study provides a transparent, reproducible framework linking microstructural mechanisms, empirical data, and statistical modeling to quantify irradiation-modified creep–fatigue behavior. The findings support the development of interaction-aware assessment tools for life prediction, inspection scheduling, and code-based design in the life extension of nuclear and high-temperature energy systems. Creep ; Bivariate analysis ; Robustness (evolution) ; Austenite ; Ultimate tensile strength ; Plasticity ; Dwell time ; Power law Fusion materials and technologies ; High Temperature Alloys and Creep ; Nuclear Materials and Properties