jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sheena Agarwal | Kavita Joshi
Source: ChemistrySelect (article, 2022-10-19)
Field: Materials Science — Materials Chemistry

Looking beyond Adsorption Energies to Understand Interactions at Surface using Machine Learning Abstract Identifying factors that influence interactions at the surface is still an active area of research. In this work, the importance of analyzing bond length activations (BL act ) along with adsorption energies (E a ) while interpreting Density Functional Theory (DFT) results is emphasized. Investigating adsorption of different small molecules, such as O 2 , N 2 , CO, and CO 2 , on commonly studied facets ((100), (110), and (111)) of seven fcc transition metal surfaces (M=Ag, Au, Cu, Ir, Rh, Pt, and Pd) demonstrates the missing linear correlation between E a and BL act . Further, tree based Machine Learning (ML) models reinforce the missing linear correlation between the two parameters and also highlight the importance of analyzing both to develop a better understanding of adsorption at surfaces. The best performing Random Forest models have a mean absolute error (MAE) of 0.19 eV for E a prediction, and even lower MAE of 0.012 Å for BL act prediction. While often d‐band center is correlated with E a , our observations show that infact the d‐band center has a better correlation with BL act . These observations emphasizes the role of BL act in gaining a fuller picture for catalysis. The fact that the factors responsible for BL act is a lesser‐explored subject adds to the novelty of the findings. Adsorption ; Novelty ; Density functional theory ; Random forest ; Molecule ; Chemistry ; Materials science ; Artificial intelligence ; Mathematics ; Computer science ; Computational chemistry ; Thermodynamics ; Physics ; Physical chemistry ; Psychology ; Social psychology Machine Learning in Materials Science ; CO2 Reduction Techniques and Catalysts ; Electrocatalysts for Energy Conversion
Authors: Zohreh Khoshraftar | Ahad Ghaemi
Source: SSRN Electronic Journal (article, 2022-01-01)
Field: Chemistry — Inorganic Chemistry

Evaluation of Pistachio Shells as Solid Wastes to Produce Activated Carbon for Co2 Capture: Isotherm, Response Surface Methodology (Rsm) and Artificial Neural Network (Ann) Modeling Response surface methodology ; Activated carbon ; Artificial neural network ; Materials science ; Process engineering ; Biological system ; Waste management ; Adsorption ; Chemical engineering ; Environmental science ; Biochemical engineering ; Computer science ; Engineering ; Chemistry ; Artificial intelligence ; Chromatography ; Biology ; Organic chemistry Zeolite Catalysis and Synthesis ; Extraction and Separation Processes ; Membrane Separation and Gas Transport
Authors: Jitendra Pal Singh | Subhajit Nandy | Keun Hwa Chae | Sangsul Lee
Source: Prabha Materials Science Letters (article, 2022-09-01)
Field: Materials Science — Materials Chemistry

X-ray Absorption Spectroscopy for Estimation of Oxidation State, Chemical Fraction and Local Atomic Structure of Materials This work discussed the role of X-ray absorption spectroscopy (XAS) in determining the oxidation state, chemical fraction, and local atomic structure of the materials. These aspects of XAS were discussed by taking LiNiO2 and Mn3O4 as prototype materials. The oxidation state of metal ions in these oxides was estimated with the help of XAS spectra of the reference oxides such as NiO (in the case of LiNiO2), MnO, Mn2O3, and MnO2 (in the case of Mn3O4). Analysis of the oxidation state was performed from the main absorption edge which was estimated from half of the step height. This showed that the Ni K-edge absorption edge of LiNiO2 is slightly above that of NiO. In the case of Mn ions, the main absorption edges show a linear variation with the oxidation states. This estimates the presence of a mixed oxidation state (2.6+) of Mn ions in Mn3O4. Linear combination fitting results exhibit that almost 35% of ions are in a 2+ oxidation state. The remaining ions are in a 3+ oxidation state. Thus, XAS can determine the fractions of each oxidation state of a particular ion in a given material. Quantitative information on coordination number and bond distance of nearest neighbor for a given element of a material is another important use of this technique. X-ray absorption spectroscopy ; Oxidation state ; Absorption spectroscopy ; Ion ; Absorption (acoustics) ; Extended X-ray absorption fine structure ; Chemical state ; Non-blocking I/O ; Coordination number ; Analytical Chemistry (journal) ; Spectroscopy ; Inorganic chemistry ; Chemistry ; XANES ; Absorption edge ; Bond length ; Atomic number ; Materials science ; X-ray photoelectron spectroscopy ; Metal ; Crystallography ; Atomic physics ; Crystal structure ; Optics ; Organic chemistry ; Physics ; Nuclear magnetic resonance ; Catalysis Catalytic Processes in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Jiaqi Dong | Brij M. Moudgil
Source: KONA Powder and Particle Journal (article, 2022-01-28)
Field: Materials Science — Surfaces, Coatings and Films

Interfacial Engineering of Particulate &amp; Surfactant Systems for Enhanced Performance in Industrial Applications Particulate and surfactant systems are an integral part either in processing or product lines in essentially every major industry, including Energy and Minerals, Pharmaceutical, Agriculture & Food, Microelectronics, Healthcare, Cosmetics, Consumer Products, and Analytical Instrumentation & Services. In most applications, product and process specifications depend on the synergistic or competitive interactions between the particles and reagent schemes. The primary goal of our research efforts has been to generate the structure-property-performance correlations-based knowledge and technology platforms for industry to develop more sustainable products and processes. Engineering the physicochemical/mechanical properties of surfaces, particles, and self-assembling surfactant systems enables their enhanced performance in industrial applications. Specifically, understanding and control of the nano and atomic-scale forces between particles and synthesis of functionalized particles form the foundation for targeted contributions in biomedical, advanced materials and minerals, sensor, and coating technologies. A synoptic overview of selected projects is presented in this review. Additional details can be found in the topic-specific references listed at the end of this manuscript. Microelectronics ; Nanotechnology ; Process engineering ; Coating ; Materials science ; Process (computing) ; Manufacturing engineering ; Systems engineering ; Computer science ; Engineering Surface Modification and Superhydrophobicity ; Pickering emulsions and particle stabilization ; Electrohydrodynamics and Fluid Dynamics
Authors: Viacheslav Shkirskiy | Frédéric Kanoufi
Source: ChemRxiv (preprint, 2022-12-13)
Field: Materials Science — Materials Chemistry

Reflective microscopy for mechanistic insights in corrosion research Reflective microscopy (RM) is a robust, label free optical imaging technique that allows fast operando measurements of structural changes on metal interfaces at nanoscale in a wide field. Based on the analysis of the reflected light, RM can be simply understood as “video camera” to produce optical photographs of studied interfaces and thus, it has been used for many years as a complementary tool for the visual inspection. However, recent developments in the optical models and refining the experimental design provided means for the quantitative conversion of reflected light intensities into the variations in roughness, thickness of surface films, chemical composition etc., all indispensable for the surface sciences. This review highlights recent advances and contemporary challenges in the methodological developments of RM specifically tailored for the corrosion research. Nanoscopic scale ; Materials science ; Microscopy ; Optical microscope ; Surface finish ; Optics ; Nanotechnology ; Surface roughness ; Corrosion ; Field (mathematics) ; Computer science ; Metallurgy ; Physics ; Composite material Anodic Oxide Films and Nanostructures ; Photoacoustic and Ultrasonic Imaging ; Force Microscopy Techniques and Applications
Authors: Omri Abarbanel | Julisa Rozon | Geoffrey Hutchison
Source: The Journal of Physical Chemistry Letters (article, 2022-02-28)
Field: Chemistry — Spectroscopy

Strategies for Computer-Aided Discovery of Novel Open-Shell Polymers Organic π-conjugated polymers with a triplet ground state have been the focus of recent research for their interesting and unique electronic properties, arising from the presence of the two unpaired electrons. These compounds are usually built from alternating electron-donating and electron-accepting monomer pairs which lower the HOMO-LUMO gap and yield a triplet state instead of the typical singlet ground state. In this paper, we use density functional theory calculations to explore the design rules that govern the creation of a ground-state triplet conjugated polymer and find that a small HOMO-LUMO gap in the singlet state is the best predictor for the existence of a triplet ground state, compared to previous use of a pro-quinoidal bonding character. This work can accelerate the discovery of new stable triplet materials by reducing the computational resources needed for electronic-state calculations and the number of potential candidates for synthesis. Shell (structure) ; Polymer ; Open shell ; Computer science ; Polymer science ; Materials science ; Engineering ; Chemistry ; Mechanical engineering ; Organic chemistry ; Composite material Analytical Chemistry and Chromatography ; Organic Electronics and Photovoltaics ; Machine Learning in Materials Science
Authors: Alon Ratner | Michael Wood | Maximilian Chowanietz | Nikhil Kumar | Rashik Patel | Paul Hadlum | Abhishek Das | Iain Masters
Source: Energies (article, 2022-06-15)
Field: Materials Science — Materials Chemistry

Laser Doppler Vibrometry for Evaluating the Quality of Welds in Lithium-Ion Supercells The inspection of the quality of welds in battery packs plays an important role in ensuring safety during the manufacturing and operation of energy-storage devices in automotive vehicles during service. This research investigated the novel application of laser Doppler vibrometry, a widely used non-destructive optical technique for modal analysis, to the post-weld evaluation of micro-TIG-welded interconnections in lithium-ion supercells. The experimental modal analysis showed features in the modal models of the supercells that were unique to their welding conditions. The comparisons between the supercells showed an absence of linear correlations between the modal parameters and the welding current, as well as differences in the welding parameters obtained from the negative and positive terminals of the cylindrical cells. These findings suggested that the modal parameters of the supercells were more strongly influenced by the rigidity of the structural materials than by the localized compliance of the welded interconnections. While this investigation demonstrated a method for using laser Doppler vibrometry to distinguish between different welding conditions in lithium-ion supercells at a structural level, further development is needed to identify the weld quality of individual interconnections. Welding ; Materials science ; Laser beam welding ; Modal ; Laser ; Modal analysis ; Acoustics ; Structural engineering ; Optics ; Composite material ; Vibration ; Engineering ; Physics Corrosion Behavior and Inhibition ; High voltage insulation and dielectric phenomena ; Advanced Battery Technologies Research
Authors: Ifeyinwa Ekeke | Steve Efe | Felix Nwadire
Source: Zastita materijala (review, 2022-09-03)
Field: Materials Science — Materials Chemistry

A review of amino acids used as corrosion inhibitors on iron metal/alloys in aggressive environments Research into the use of safe and environmentally friendly corrosion inhibitors can pave the way for an understanding of their inhibition mechanisms in metallic alloy materials. This review seeks to present and discuss the research work reported in the literature on the use of amino acids and their derivatives as corrosion inhibitors for iron and its alloys in different aggressive solutions. This non-toxic, biodegradable and relatively cheap corrosion inhibitor has shown to be efficient as an inhibitor for metals/alloys in acidic, alkaline and neutral solutions depending on experimental conditions. Electrochemical and surface techniques were among the most often used techniques to evaluate the corrosion inhibition efficiency of amino acids. Highest values of inhibition efficiency can be obtained in the presence of ions as Iand Br. This review presents and discusses most of the contributions made in literature on the use of amino acids and their derivatives as corrosion inhibitors for iron and its alloys. Corrosion ; Amino acid ; Metal ; Electrochemistry ; Alloy ; Materials science ; Metal ions in aqueous solution ; Chemistry ; Environmentally friendly ; Metallurgy ; Biochemistry ; Electrode ; Biology Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Yi-Hong Lin | Chih-Ning Tsai | Po-Feng Chen | Yen-Tzu Lin | Sorour Darvishi | Hubert H. Girault | Tung‐Yi Lin | Mei‐Yi Liao | Tzu‐En Lin
Source: ChemRxiv (preprint, 2022-06-29)
Field: Chemistry — Electrochemistry

AI-Assisted Fusion of Scanning Electrochemical Microscopy Images Using Novel Soft Probe Scanning electrochemical microscopy (SECM) is one of the scanning probe techniques that has attracted considerable attention because of its ability to interrogate surface morphology or electrochemical reactivity. However, the quality of SECM images generally depends on the sizes of the electrodes and many uncontrollable factors. Furthermore, manipulating fragile glass ultramicroelectrodes and blurred images sometimes frustrate researchers. To overcome the challenges of modern SECM, we developed novel soft gold probes and then established the AI-assisted methodology for image fusion. A novel gold microelectrode probe with high softness was developed to scan fragile samples. The distribution of EGFR (protein biomarker) in oral cancer was investigated. Then, we fused the optical microscopic images and SECM images to enhance the image quality using Matlab software. However, by changing the parameters for image fusion, thousands of fused images were generated, which is annoying for researchers. Thus, a deep learning model was built to select the best-fused images according to the contrast and clarity of the fused images. Therefore, the quality of the SECM images was improved by using a novel soft probe followed by combining the image fusion technique. In the future, a new scanning probe with AI-assisted fused SECM image processing may be interpreted more preciously and contribute to the early detection of cancers. Scanning electrochemical microscopy ; Image fusion ; Artificial intelligence ; Materials science ; Fusion ; Microscopy ; Computer vision ; Microelectrode ; Computer science ; Nanotechnology ; Optics ; Electrode ; Chemistry ; Image (mathematics) ; Physics ; Electrochemistry Electrochemical Analysis and Applications ; Thermography and Photoacoustic Techniques ; Photoacoustic and Ultrasonic Imaging
Authors: Stefan Mebs | Jens Beckmann
Source: Physical Chemistry Chemical Physics (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

<i>In silico</i> activation of dinitrogen with a light atom molecule The NN triple bond can be cleaved <i>in silico</i> with a light atom molecule containing only the earth abundant elements C, H, Si, and P. Extensive density functional theory (DFT) computations on various classes of <i>peri</i>-substituted scaffolds containing Lewis acidic and basic sites in the framework of frustrated Lewis pairs (FLP) indicate that the presence of two silyl cations and two P atoms in a flexible but not too flexible arrangement is essential for energy efficient N<sub>2</sub>-activation. The non-bonding lone-pair electrons of the P atoms thereby serve as donors towards N<sub>2</sub>, whereas the lone-pairs of N<sub>2</sub> donate into the silyl cations. Newly formed lone-pair basins in the N<sub>2</sub>-adducts balance surplus charge. Thereby, the N-N bond distance is increased by astonishing 0.3 Å, from 1.1 Å in N<sub>2</sub> gas to 1.4 Å in the adduct, which makes this bond prone to subsequent addition of hydride ions and protonation, forming two secondary amine sites in the process and eventually breaking the NN triple bond. Potential formation of dead-end states, in which the dications ("active states") aversively form a Lewis acid (LA)-Lewis base (LB) bond, or in which the LA and LB sites are too far away from each other to be able to capture N<sub>2</sub>, are problematic but might be circumvented by proper choice of spacer molecules, such as acenaphthalene or biphenylene, and the ligands attached to the LA and LB atoms, such as phenyl or mesityl, and by purging the reaction solutions with gaseous N<sub>2</sub> in the initial reaction steps. Charge redistributions <i>via</i> N<sub>2</sub>-activation and splitting were monitored by a variety of real-space bonding indicators (RSBIs) derived from the calculated electron and electron pair densities, which provided valuable insight into the bonding situation within the different reaction steps. Lone pair ; Chemistry ; Lewis acids and bases ; Adduct ; Triple bond ; Protonation ; Hydride ; Molecule ; Atoms in molecules ; Crystallography ; Frustrated Lewis pair ; Density functional theory ; Atom (system on chip) ; Electron pair ; Stereochemistry ; Computational chemistry ; Ion ; Catalysis ; Double bond ; Electron ; Organic chemistry ; Metal Organoboron and organosilicon chemistry ; Crystallography and molecular interactions ; Synthesis and characterization of novel inorganic/organometallic compounds
Authors: Adam Yonge | Gabriel S. Gusmão | Rakesh Batchu | M. Ross Kunz | Zongtang Fang | Rebecca Fushimi | Andrew J. Medford
Source: AIChE Journal (article, 2022-05-25)
Field: Materials Science — Materials Chemistry

Quantifying the impact of temporal analysis of products reactor initial state uncertainties on kinetic parameters Abstract The temporal analysis of products (TAP) reactor provides a route to extract intrinsic kinetics from transient measurements. Current TAP uncertainty quantification only considers the experimental noise present in the outlet flow signal. Additional sources of uncertainty such as initial surface coverages, catalyst zone location, inert void fraction, gas pulse intensity, and pulse delay, are not included. For this reason, a framework for quantifying initial state uncertainties present in TAP experiments is presented and applied to a carbon monoxide oxidation case study. Two methods for quantifying these sources of uncertainty are introduced. The first utilizes initial state sensitivities to approximate the parameter variances and provide insights into the structural certainty of the model. The second generates parameter confidence distributions through an ensemble‐based sampling algorithm. The initial state covariance matrix can ultimately be merged with the experimental noise covariance matrix, providing a unified description of the parameter uncertainties for a TAP experiment. Covariance ; Sensitivity (control systems) ; Covariance matrix ; Mechanics ; Uncertainty quantification ; Control theory (sociology) ; Biological system ; Environmental science ; Statistics ; Mathematics ; Computer science ; Engineering ; Physics Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Catalysis and Hydrodesulfurization Studies
Authors: Yao Zhang | Zezhong Tian | Wenqiang Ma | Man Zhang | Liling Yang
Source: International journal of agricultural and biological engineering (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Hyperspectral detection of walnut protein contents based on improved whale optimized algorithm Nondestructive and accurate estimation of walnut kernel protein content is important for food quality grading and profitability improvement of walnut packinghouses. Hyperspectral image technology provides potential solutions for walnuts nutrients detection by obtaining both spectral and textural information. However, the redundancy and large computation of spectral data prevent the widespread application of hyperspectral technology for high throughput evaluation. For walnut kernel protein inversion from hyperspectral image, this study proposed a novel feature selection method, which is named as improved whale optimized algorithm (IWOA). In the IWOA, a comprehensive feature selection criterion was applied in the iterative process, which fully considered the relevance of spectra information with target variables, representative ability of the selected wavebands to entire spectra, and redundancy of the selected wavebands. Especially in the relevance with target variables, the amplitude and shape characteristics of the spectra were both taken into consideration. Eight wavelengths around 996, 1225, 1232, 1377, 1552, 1600, 1691 and 1700 nm were then selected as the sensitive wavelengths to walnut protein. These wavelengths showed good correlation with certain chemical compounds related to protein contents mechanistically. Then three protein prediction models were established. After analysis and comparison, the model based on the selected wavelengths got better results with the one based on the full spectrum. Compared to the models based on solely spectral information, the model that combine spectral and textural information outperformed and got the best prediction results. The R2 in the calibration group was 0.9047, and the root mean square errors (RMSE) was 11.1382 g/kg. In the validation group, the R2 was 0.8537, and the RMSE was 18.9288 g/kg. The results demonstrated that the combination of the selected wavelengths through the IWOA with the textural characteristics could effectively estimate walnut protein contents. And the proposed method can be extended to the detection and inversion of other nutritional variables of nuts. Keywords: walnut protein, hyperspectral image, whale optimized algorithm, feature selection, textural indicator DOI: 10.25165/j.ijabe.20221506.7179 Citation: Zhang Y, Tian Z Z, Ma W Q, Zhang M, Yang L L. Hyperspectral detection of walnut protein contents based on improved whale optimized algorithm. Int J Agric & Biol Eng, 2022; 15(6): 235–241. Hyperspectral imaging ; Mean squared error ; Feature selection ; Redundancy (engineering) ; Near-infrared spectroscopy ; Mathematics ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Remote Sensing and Land Use