jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sruti Sangeeta Jena | Shakti Singh | Sharat Chandra
Source: arXiv (Cornell University) (preprint, 2023-09-14)
Field: Materials Science — Ceramics and Composites

Characterizing MRO in atomistic models of vitreous SiO$_2$ generated using ab-initio molecular dynamics Vitreous silica is the most versatile material for scientific and commercial applications. Although large-scale atomistic models of vitreous-SiO$_2$ (v-SiO$_2$) having medium-range order (MRO) have been successfully developed by melt-quench through classical molecular dynamics, the MRO is not well studied for the smaller-scale models developed by melt-quench using ab-initio molecular dynamics (AIMD). In this study, we obtain atomistic models of v-SiO$_2$ by performing melt-quench simulation using AIMD. The final structure is compared with the experimental data and some recent atomistic models, on the basis of the structural properties. Since AIMD allows for the estimation of electronic structure, a detailed study of electronic properties is also done. It shows the presence of defect states mainly due to dangling bonds in the band-gap region of electronic density of states, whereas the edge-shared type of defective structures in the glassy models are found to contribute mainly in the valence band. In addition, Oxygen and Silicon vacancies as well as bridging Oxygen type of defects were created and their contributions to the band-gap were studied. Materials science ; Molecular dynamics ; Dangling bond ; Electronic structure ; Chemical physics ; Band gap ; Ab initio ; Bridging (networking) ; Silicon ; Valence (chemistry) ; Computational chemistry ; Chemistry ; Optoelectronics ; Computer science Glass properties and applications ; Photonic Crystals and Applications ; Crystal Structures and Properties
Authors: Tim Gould
Source: ChemRxiv (preprint, 2023-01-27)
Field: Materials Science — Materials Chemistry

Toward routine Kohn-Sham inversion using the "Lieb-response" approach Kohn-Sham inversion, in which the effective Kohn-Sham mean-field potential is found for a given density, provides insights into the nature of exact density functional theory (DFT) that can be exploited for the development of density functional approximations. Unfortunately, and despite significant and sustained progress in both theory and software libraries, KS inversion remains rather difficult in practice, and especially in finite basis sets. The present work presents a Kohn-Sham inversion method, dubbed the “Lieb-response” approach, that naturally works with existing Fock-matrix DFT infrastructure in finite basis sets, is numerically efficient, and directly provides meaningful matrix and energy quantities for pure-state and ensemble systems. Some additional work yields potentials. It thus enables the routine inversion of even difficult KS systems, as illustrated on a variety of problems within this work; and provides outputs that can be used for embedding schemes or machine learning of density functional approximations. The effect of finite basis sets on Kohn-Sham inversion is also analysed and investigated. Kohn–Sham equations ; Inversion (geology) ; Density functional theory ; Embedding ; Density matrix ; Computer science ; Basis (linear algebra) ; Statistical physics ; Mathematics ; Algorithm ; Physics ; Quantum mechanics ; Artificial intelligence ; Quantum ; Geometry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Ciprian BUZNA | Marinel Nicolae HORABLAGA | Luana SABO | Andreea Lidia JURJESCU | F. Sala
Source: LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT (article, 2023-07-19)
Field: Chemistry — Analytical Chemistry

CHARACTERIZATION OF SOME AROMATIC AND MEDICINAL PLANTS SPECIES BASED ON UAV IMAGES The study used imaging analysis to characterize several species of aromatic and medicinal plants. UAV images were taken on five aromatic and medicinal plants species, cultivated by SCDA Lovrin, Timis county, Romania. The biological material was represented by Lavandulua x intermedia (Lavandin), P1; Hyssopus officinalis L., P2, P6; Origanum vulgare L., P3; Thymus serpyllum L., P4; Salvia officinalis L., P5 (P1 to P6 species code in the article). The images were analyzed (four repetitions) and the values of the RGB color parameters were obtained. The ANOVA test confirmed the presence of variance and the safety of the data (F&gt;F crit, p&lt;0.001; Alpha=0.001). The correlation analysis highlighted positive and negative correlations of different intensity levels between RGB parameters and calculated ratios (R/G, R/B, G/R, G/B, B/R, B/G). The variation of G in relation to R was described by a polynomial equation of degree 3 (R2=0.956), and the variation of B in relation to R was described by a polynomial equation of degree 2 (R2=0.736). High variability was recorded in the case of parameter B (CVB=23.44534), plant P3 (Origanum vulgare L.), and low variability was recorded in the case of color parameter G (CVG=2.66030), plant P2 (Hyssopus officinalis L.). Based on PCA, the distribution diagram of plant species in relation to RGB color parameters and calculated ratios, as biplot, was obtained. PC1 explained 66.037% of variance, and PC2 explained 33.095% of variance in relation to RGB, and PC1 explained 58.923% of variance, and PC2 explained 36.46% of variance in relation to the calculated ratios. The cluster analysis facilitated the grouping of plant species (P1 to P6) based on similarity in relation to the RGB color parameter values (Coph.corr. = 0.959). Characterization (materials science) ; Aromatic plants ; Computer science ; Environmental science ; Artificial intelligence ; Biology ; Botany ; Nanotechnology ; Materials science Spectroscopy and Chemometric Analyses ; Flavonoids in Medical Research
Authors: Lucas Pagano | Guillaume Thibault | Walid Bousselham | Jessica L. Riesterer | Xubo Song | Joe W. Gray
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-11-01)
Field: Materials Science — Surfaces, Coatings and Films

Efficient semi-supervised semantic segmentation of electron microscopy cancer images with sparse annotations Electron microscopy (EM) enables imaging at nanometer resolution and can shed light on how cancer evolves to develop resistance to therapy. Acquiring these images has become a routine task; however, analyzing them is now the bottleneck, as manual structure identification is very time-consuming and can take up to several months for a single sample. Deep learning approaches offer a suitable solution to speed up the analysis. In this work, we present a study of several state-of-the-art deep learning models for the task of segmenting nuclei and nucleoli in volumes from tumor biopsies. We compared previous results obtained with the ResUNet architecture to the more recent UNet++, FracTALResNet, SenFormer, and CEECNet models. In addition, we explored the utilization of unlabeled images through semi-supervised learning with Cross Pseudo Supervision. We have trained and evaluated all of the models on sparse manual labels from three fully annotated in-house datasets that we have made available on demand, demonstrating improvements in terms of 3D Dice score. From the analysis of these results, we drew conclusions on the relative gains of using more complex models, semi-supervised learning as well as next steps for the mitigation of the manual segmentation bottleneck. Artificial intelligence ; Bottleneck ; Computer science ; Segmentation ; Deep learning ; Task (project management) ; Pattern recognition (psychology) ; Supervised learning ; Machine learning ; Sample (material) ; Identification (biology) ; Market segmentation ; Visualization ; Artificial neural network Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Machine Learning in Materials Science
Authors: Rutvik Mehenge | Vikash Prasad
Source: World Journal of Advanced Engineering Technology and Sciences (article, 2023-09-15)
Field: Materials Science — Materials Chemistry

Experimental assessment of precision temperature control electronic architecture for solar-powered TEC refrigerator This study presents experimental research concerning an active thermoelectric cooling control architecture applied to portable, solar-powered medical refrigerators. A specialized Electronic Control Unit (ECU) has been devised for regulating thermoelectric cooling, enabling users to define operational thresholds for the thermoelectric coolers through the system's architecture. The TEC1-12706 thermoelectric cooling system was employed. The system is engineered to swiftly cool the medical refrigerator's storage cabinet by up to 6 °C within 30 minutes and maintain a critical temperature range of 2 °C to 8 °C, vital for safeguarding thermolabile vaccines and medications. The control unit design encompasses a closed-loop control approach utilizing an Arduino Nano, a Linear voltage regulator, and a solar-powered battery charging setup. The Arduino issues signals based on preset points through sensors, thereby regulating the refrigeration system's desired temperature, while a relay module serves as an ON-OFF controller for temperature management. Preliminary results affirm that, in conjunction with a heat sink and DC fan, the thermoelectric cooler successfully achieves the intended temperature range, demonstrating promising cooling capabilities. Thermoelectric cooling ; Temperature control ; Control unit ; Thermoelectric effect ; TEC ; Refrigerator car ; Automotive engineering ; Refrigeration ; Heat sink ; Engineering ; Electrical engineering ; Mechanical engineering ; Computer science Advanced Thermoelectric Materials and Devices ; Refrigeration and Air Conditioning Technologies ; Advanced Thermodynamics and Statistical Mechanics
Authors: Jiankun Fang | Shihao Cao | Zhaoyang Li
Source: Highlights in Science Engineering and Technology (article, 2023-05-21)
Field: Chemistry — Inorganic Chemistry

Fisher Linear Discriminant and Systematic Cluster Analysis based on analysis and identification of the composition of ancient glass products The Silk Road was a channel of cultural exchange between China and the West in ancient times, of which glass was a valuable physical evidence of early trade exchanges. Therefore, it is important to analyze the ancient glass products for the research related to ancient times. In this paper, in order to get the classification law of high potassium and lead-barium glass, firstly, the discriminant relationship function was obtained by using Fisher Linear Discriminant Analysis. Secondly, the data were downscaled by Principal Component Analysis to get five principal components, and then Fisher Linear Discriminant Analysis was used to get the discriminant function, and the results all passed the cross-check, and the model accuracy was 95.29% and 91.43%, respectively. The subclasses were classified by Systematic Clustering Model and Elbow Method, and it was concluded that the high potassium glass was mainly divided into two subclasses based on whether the silica content was greater than 80%; the lead-barium glass was mainly divided into four subclasses based on the content of three different chemical components: silica, barium oxide and phosphorus pentoxide. And through the reasonableness and sensitivity analysis, this paper got that different chemical compositions have different size influence on the classification of glass. Linear discriminant analysis ; Principal component analysis ; Discriminant function analysis ; Mathematics ; Barium ; Mineralogy ; Identification (biology) ; Statistics ; Materials science ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Computer science ; Metallurgy ; Botany Pigment Synthesis and Properties ; Geochemistry and Geologic Mapping ; Heavy Metals in Plants
Authors: Ciprian BUZNA | Marinel Nicolae HORABLAGA | Luana SABO | Andreea Lidia JURJESCU | F. Sala
Source: LIFE SCIENCE AND SUSTAINABLE DEVELOPMENT (article, 2023-07-19)
Field: Chemistry — Analytical Chemistry

CHARACTERIZATION OF SOME AROMATIC AND MEDICINAL PLANTS SPECIES BASED ON UAV IMAGES The study used imaging analysis to characterize several species of aromatic and medicinal plants. UAV images were taken on five aromatic and medicinal plants species, cultivated by SCDA Lovrin, Timis county, Romania. The biological material was represented by Lavandulua x intermedia (Lavandin), P1; Hyssopus officinalis L., P2, P6; Origanum vulgare L., P3; Thymus serpyllum L., P4; Salvia officinalis L., P5 (P1 to P6 species code in the article). The images were analyzed (four repetitions) and the values of the RGB color parameters were obtained. The ANOVA test confirmed the presence of variance and the safety of the data (F&gt;F crit, p&lt;0.001; Alpha=0.001). The correlation analysis highlighted positive and negative correlations of different intensity levels between RGB parameters and calculated ratios (R/G, R/B, G/R, G/B, B/R, B/G). The variation of G in relation to R was described by a polynomial equation of degree 3 (R2=0.956), and the variation of B in relation to R was described by a polynomial equation of degree 2 (R2=0.736). High variability was recorded in the case of parameter B (CVB=23.44534), plant P3 (Origanum vulgare L.), and low variability was recorded in the case of color parameter G (CVG=2.66030), plant P2 (Hyssopus officinalis L.). Based on PCA, the distribution diagram of plant species in relation to RGB color parameters and calculated ratios, as biplot, was obtained. PC1 explained 66.037% of variance, and PC2 explained 33.095% of variance in relation to RGB, and PC1 explained 58.923% of variance, and PC2 explained 36.46% of variance in relation to the calculated ratios. The cluster analysis facilitated the grouping of plant species (P1 to P6) based on similarity in relation to the RGB color parameter values (Coph.corr. = 0.959). Origanum ; Salvia officinalis ; RGB color model ; Mathematics ; Horticulture ; Botany ; Officinalis ; Biology ; Artificial intelligence ; Essential oil Spectroscopy and Chemometric Analyses ; Phytochemistry and Biological Activities ; Essential Oils and Antimicrobial Activity
Authors: Xin Zhang | Hongbo Lou | Beatrice Ruta | Yuriy Chushkin | Federico Zontone | Shubin Li | Dazhe Xu | Tao Liang | Zhidan Zeng | Ho‐kwang Mao | Qiaoshi Zeng
Source: arXiv (Cornell University) (preprint, 2023-10-25)
Field: Materials Science — Materials Chemistry

Pressure-induced non-monotonic crossover of steady relaxation dynamics in a metallic glass Relaxation dynamics, as a key to understand glass formation and glassy properties, remains an elusive and challenging issue in condensed matter physics. In this work, in situ high-pressure synchrotron high-energy x-ray photon correlation spectroscopy has been developed to probe the atomic-scale relaxation dynamics of a cerium-based metallic glass during compression. Although the sample density continuously increases, the collective atomic motion initially slows down as generally expected and then counter-intuitively accelerates with further compression (density increase), showing an unusual non-monotonic pressure-induced steady relaxation dynamics crossover at ~3 GPa. Furthermore, by combining in situ high-pressure synchrotron x-ray diffraction, the relaxation dynamics anomaly is evidenced to closely correlate with the dramatic changes in local atomic structures during compression, rather than monotonically scaling with either sample density or overall stress level. These findings could provide new insight into relaxation dynamics and their relationship with local atomic structures of glasses. Relaxation (psychology) ; Synchrotron ; Amorphous metal ; Materials science ; Compression (physics) ; Dynamics (music) ; Scaling ; Atomic units ; Condensed matter physics ; Chemical physics ; Physics ; Optics ; Metallurgy ; Composite material Material Dynamics and Properties ; Metallic Glasses and Amorphous Alloys ; Glass properties and applications
Authors: F Cheng
Source: International Journal of Web Services Research (article, 2023-09-01)
Field: Materials Science — Surfaces, Coatings and Films

Research on a New Reconstruction Technology and Evaluation Method for 3D Digital Core Pore Structure This study analyses the main techniques for constructing a three-dimensional (3D) digital core, and summarizes the advantages and disadvantages of each reconstruction technique. The direction for the development of reconstruction technology for 3D digital cores is also proposed. The integration of multiscale, multicomponent, and nanoscale technology under different resolutions will play a significant role in future research efforts surrounding the physical properties of 3D digital cores. This study also introduces the main evaluation methods of digital cores, while analyzing and comparing the applicable scenarios of each method. The results of the pore statistics method, based on the seed filling algorithm, can be used as a new and effective evaluation method for the 3D reconstruction of digital cores. Computer science ; Core (optical fiber) ; 3D reconstruction ; Data mining ; Artificial intelligence ; Telecommunications Electron and X-Ray Spectroscopy Techniques ; Medical Image Segmentation Techniques
Authors: Jiwon Yu | Min-Ju Kim | Hae-Min Park
Source: KSBB Journal (article, 2023-03-31)
Field: Chemistry — Spectroscopy

Recent Advances in Top-Down Proteomics for Proteoform Analysis Over the past decade, mass spectrometry-based bottom-up proteomics (BUP) has been widely used to identify and to quantify complete proteomes from a biological system such as a cell, tissue, or organism.However, due to the protein inference problem, BUP approaches have intrinsic limitations for identifying and characterizing intact proteins that underlie complex traits and molecular mechanisms in biology.In contrast to BUP, which measures peptides produced from proteins by proteolytic digestion, top-down proteomics (TDP) is a powerful technology that allows for measuring intact proteins without proteolysis, thus identifying and quantifying proteoforms which provide new insights into molecular mechanisms.A proteoform is a defined form of a protein product from a single gene, including combinatorial coding polymorphisms, alternative RNA splicing events, and post-translational modifications (PTMs) on the same molecule.In this review, we outline some advances in separation, ionization, and fragmentation of intact proteins and data processing for TDP along with the growing power of proteoform-resolved measurements in clinical and translational research and biotechnology. Proteomics ; Computational biology ; Computer science ; Chemistry ; Biology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Glycosylation and Glycoproteins Research
Authors: Ade Usra Berli | Desmarita Leni | Helga Yermadona
Source: Jurnal Surya Teknika (article, 2023-12-25)
Field: Materials Science — Materials Chemistry

Analisis Pengaruh Komposisi Kimia dan Suhu Perlakuan Panas Terhadap Sifat Mekanik Baja Tahan Karat untuk Aplikasi Konstruksi A deep understanding of the mechanical properties of stainless steel is crucial for designing constructions that meet the requirements. However, to comprehensively understand the mechanical properties of stainless steel, sufficient testing is needed to gather data regarding its characteristics. In this research, an analysis was conducted on the Effect of Chemical Composition and Heat Treatment on the Mechanical Properties of Stainless Steel, using data from the Material Algorithm Project (MAP), which is a material database. The data was analyzed using descriptive statistics and Pearson correlation to observe the relationships between these variables. The research results indicate that chemical elements such as Cu and Ni have a positive correlation with elongation, indicating that higher concentrations of these elements lead to higher elongation of stainless steel. Furthermore, it was also found that temperature has a strong negative correlation with yield strength (YS) and ultimate tensile strength (UTS), with correlation values of -0.71 and -0.86, respectively. Further analysis revealed that water quenching resulted in better ultimate tensile strength compared to air quenching. This research demonstrates that experimental material testing datasets not only validate experiments but can also actively be used in the analysis and design of more effective materials. Ultimate tensile strength ; Elongation ; Quenching (fluorescence) ; Materials science ; Tensile testing ; Metallurgy ; Physics Material Selection and Properties
Authors: Oliver J. Hale | Helen J. Cooper | Michael T. Marty
Source: ChemRxiv (preprint, 2023-07-21)
Field: Chemistry — Spectroscopy

High-throughput deconvolution of native protein mass spectrometry imaging datasets for mass domain analysis. Protein mass spectrometry imaging (MSI) with electrospray-based ambient ionization techniques, such as nanospray-desorption electrospray ionization (nano-DESI), generates datasets in which each pixel corresponds to a mass spectrum populated by peaks corresponding to multiply-charged protein ions. Importantly, the signal associated with each protein is split among multiple charge states. These peaks can be transformed into the mass domain by spectral deconvolution. When proteins are imaged under native/non-denaturing conditions to retain non-covalent interactions, deconvolution is particularly valuable in helping interpret the data. To improve acquisition speed, signal-to-noise ratio, and sensitivity, native MSI is usually performed using mass resolving powers that do not provide isotopic resolution, and conventional algorithms for deconvolution of lower-resolution data are not suitable for these large data sets. UniDec was originally developed to enable rapid deconvolution of complex protein mass spectra. Here, we developed an updated feature set harnessing the high-throughput module, MetaUniDec, to deconvolve each pixel of native MSI datasets and transform m/z-domain image files to the mass domain. New tools enable reading, processing, and output of open format .imzML files for downstream analysis. Transformation of data into the mass domain also provides greater accessibility, with mass information readily interpretable by users of established protein biology tools such as SDS-PAGE. Deconvolution ; Mass spectrometry ; Electrospray ionization ; Chemistry ; Mass spectrum ; Mass spectrometry imaging ; Noise (video) ; Computer science ; Biological system ; Analytical Chemistry (journal) ; Artificial intelligence ; Algorithm ; Image (mathematics) ; Chromatography Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Proteomics Techniques and Applications