jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Md Tohidul Islam | Qinrui Liu | Scott Broderick
Source: Applied Sciences (article, 2024-10-10)
Field: Materials Science — Materials Chemistry

Machine Learning Accelerated Design of High-Temperature Ternary and Quaternary Nitride Superconductors The recent advancements in the field of superconductivity have been significantly driven by the development of nitride superconductors, particularly niobium nitride (NbN). Multicomponent nitrides offer a promising platform for achieving high-temperature superconductivity. Beyond their high superconducting transition temperature (Tc), niobium-based compounds are notable for their superior superconducting and mechanical properties, making them suitable for a wide range of device applications. In this work, machine learning is used to identify ternary and quaternary nitrides, which can surpass the properties of binary NbN. Specifically, Nb0.35Ta0.23Ti0.42N shows an 84.95% improvement in Tc compared to base NbN, while the ternary composition Nb0.55Ti0.45N exhibits a 17.29% improvement. This research provides a valuable reference for the further exploration of high-temperature superconductors in diversified ternary and quaternary compositions. Ternary operation ; Materials science ; Quaternary ; Computer science ; Geology Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; Metal and Thin Film Mechanics
Authors: Zeyuan Chang | Qi Zhang | Yuanfeng Li | Xiangjun Xin | Ran Gao | Yun Teng | Lan Rao | Meng Sun
Source: Electronics (article, 2024-01-25)
Field: Chemistry — Analytical Chemistry

Identification Method for XRF Spectral Analysis Based on an AGA-BP-Attention Neural Network X-ray fluorescence (XRF) spectroscopy is a non-destructive differential measurement technique widely utilized in elemental analysis. However, due to its inherent high non-linearity and noise issues, it is challenging for XRF spectral analysis to achieve high levels of accuracy. In response to these challenges, this paper proposes a method for XRF spectral analysis that integrates an adaptive genetic algorithm with a backpropagation neural network, enhanced by an attention mechanism, termed as the AGA-BP-Attention method. By leveraging the robust feature extraction capabilities of the neural network and the ability of the attention mechanism to focus on significant features, spectral features are extracted for elemental identification. The adaptive genetic algorithm is subsequently employed to optimize the parameters of the BP neural network, such as weights and thresholds, which enhances the model’s accuracy and stability. The experimental results demonstrate that, compared to traditional BP neural networks, the AGA-BP-Attention network can more effectively address the non-linearity and noise issues of XRF spectral signals. In XRF spectral analysis of air pollutant samples, it achieved superior prediction accuracy, effectively suppressing the impact of background noise on spectral element recognition. Identification (biology) ; Artificial neural network ; Spectral analysis ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Physics ; Biology ; Spectroscopy Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Mykola Isaiev | Nataliia Mykolaivna Kyrychenko | Vasyl Kuryliuk | David Lacroix
Source: Applied Physics Letters (article, 2024-04-01)
Field: Materials Science — Materials Chemistry

Features of phonon scattering by a spherical pore: Molecular dynamics insight There is still a gap in understanding phonon scattering by geometrical defects at the nanoscale, and it remains a significant challenge for heat transfer management in nanoscale devices and systems. In this study, we aim to explore the characteristics of phonon scattering by a single pore to gain insights into thermal transport in nanostructures. The paper outlines a methodology for assessing the spatial distribution of the magnitude of the radial, azimuthal, and polar components of the velocity of scattered phonons by a spherical pore. We demonstrated that the size parameter, commonly employed in electromagnetic wave scattering theory, is vital in determining the scattering regime. Specifically, we show that the calculated scattering efficiency has the same pattern as that commonly obtained in classical wave scattering theory. However, we found that crystallographic directions are pivotal in shaping the scattering patterns, especially in the regions where scattering patterns are defined by the Mie resonances. This observation holds significance in understanding the influence of phonon coherence on thermal transport in nanostructured materials. Scattering ; Phonon scattering ; Phonon ; Scattering theory ; Physics ; Condensed matter physics ; Materials science ; Coherence (philosophical gambling strategy) ; Light scattering ; Computational physics ; Optics ; Quantum mechanics Thermal properties of materials ; Thermal Radiation and Cooling Technologies ; Thermography and Photoacoustic Techniques
Authors: Xinyi Xu | Marco Bertani | Rajan Saini | Saeed Kamali | Daniel R. Neuville | Randall E. Youngman | Alfonso Pedone | Ashutosh Goel
Source: The Journal of Physical Chemistry C (article, 2024-07-02)
Field: Materials Science — Ceramics and Composites

Iron-Induced Structural Rearrangements and Their Impact on Sulfur Solubility in Borosilicate-Based Nuclear Waste Glasses The work presented in this review combines the strength of experimental and computational materials science to understand the iron-induced structural rearrangements in peralkaline aluminoborosilicate glasses and their impact on the solubility of sulfur (as SO42–) in model nuclear waste glasses. The majority (≥96%) of iron exists as tetrahedrally coordinated Fe3+ (both isolated and clustered) in the investigated glasses, thus acting as a network former being charge-compensated by Na+, while the remaining iron exists as tetrahedrally (distorted) coordinated Fe2+. Increasing Fe2O3 concentration (from 0 to 3 mol %) leads to glass network repolymerization through two mechanisms: (1) scavenging of Na+ by FeO4– units for charge compensation, likely from the nonbridging oxygen (NBO) sites, and (2) formation of Fe–O–(Si, B) linkages. Due to the decreased availability of NBO-associated Na+ in the glassy matrix with increasing Fe2O3 content, sulfur solubility diminishes as SO42– struggles to compete effectively with AlO4–, BO4–, and FeO4– for preferential charge compensation by Na+. Mössbauer spectroscopy reveals an insignificant impact of sulfur on the redox behavior or environment of iron in the glass structure, and SO42– prefers to be charge-compensated by Na+ over Fe2+. Borosilicate glass ; Solubility ; Sulfur ; Radioactive waste ; Chemistry ; Materials science ; Inorganic chemistry ; Nuclear chemistry ; Metallurgy ; Physical chemistry Glass properties and applications ; Recycling and utilization of industrial and municipal waste in materials production ; Nuclear materials and radiation effects
Authors: Yiyi Xiong | Cheryl McCarthy | Jacob Humpal | Cassandra Percy
Source: Agronomy Journal (article, 2024-07-30)
Field: Chemistry — Analytical Chemistry

Near‐infrared spectroscopy and deep neural networks for early common root rot detection in wheat from multi‐season trials Abstract In Australia, the soil‐borne disease common root rot ( Bipolaris sorokiniana ) (CRR) in wheat ( Triticum aestivum L.) leads to substantial yield losses, yet has limited visible aboveground symptoms, making detection and identification labor intensive. Near‐infrared (NIR) spectroscopy offers an early potential identification solution for CRR in wheat and has previously been reported with success for crop disease detection. This study investigated the ability of nondestructive NIR spectroscopy in combination with deep neural networks (DNN), logistic regression (LR), and principal component analysis combined with support vector machines (PCA‐SVM) for early‐stage CRR detection in wheat. NIR spectra of five different wheat varieties with varying resistance to CRR were collected in two seasons of glasshouse and three seasons of field trials using a portable spectrometer. Results demonstrated that DNN outperformed LR and PCA‐SVM, achieving 66%–91% average classification accuracy in glasshouse trials and an average accuracy of 73% with up to 87% in field trials, effectively distinguishing inoculated and non‐inoculated wheat plants from seedling to anthesis stages. Validation with a third season of field data achieved an average of 77% accuracy for the most susceptible variety during the stem elongation stage. NIR reflectance within 1600–1700 nm was identified as most important for estimating CRR presence, with initial detection occurring 35 days after sowing (DAS) in the glasshouse and 46 DAS in the field. In conclusion, a NIR spectrometer with a DNN model successfully performed disease classification, with the potential as a portable early disease detection tool to assist farm management decisions. Sowing ; Growing season ; Principal component analysis ; Agronomy ; Crop ; Field trial ; Anthesis ; Greenhouse ; Mathematics ; Biology ; Cultivar ; Statistics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Plant Disease Management Techniques
Authors: Agus Setiawan | Johny Wahyuadi Soedarsono | Moch. Syaiful Anwar | Wahyu Mayangsari | Ahmad Maksum | Aga Ridhova | Rini Riastuti | Dedy Iskandar | Ayende Ayende
Source: Heliyon (article, 2024-05-01)
Field: Materials Science — Materials Chemistry

Exploration of rice husk ash as a green corrosion inhibitor immersed in NH4Cl 7.5 % solution The study reports the development of a liquid smoke solution of rice husk ash (RHA) as a green corrosion inhibitor in NH<sub>4</sub>Cl solution in approaching corrosion protection for refinery facilities. The recent utilization of RHA has a partial solution to address the possible chemical to form a filming layer to disconnect bare metal and their environment. This work prepared the RHA solution by condensing the RHA vapor before adding it to various concentrations. The corrosion test of potentiodynamic and electrochemicals intends to discover the inhibitor's corrosion resistance before examining the electronic transition corresponding to the contribution of several functional groups using Ultraviolet Visible (UV-Vis) and Fourier-Transform Infrared Spectroscopy (FTIR). Surface evaluation intends to unveil the nature of the corrosion by utilizing the Scanning Electronic and Atomic Force Microscope. The corrosion test result shows the depression of corrosion rate to 0.120 mmpy with high efficiency beyond 96 % in the addition of 7.5 ppm RHA inhibitor. The greater Nyquist semicircle diameter at high concentrations increases the adsorption of the RHA on the surface of C1018. The electronic transition of n-π* and π -π* shows an extensive contribution of C[bond, double bond]C, C[bond, double bond]O, and -OH based on the UV-Vis and FTIR test. The formation of a complex compound of Fe-(NH<sub>4</sub>Cl-RHA)<sub>n</sub> blocks the corrosion active sites to reduce the corrosion. This study paves the way for using RHA as an organic compound under NH<sub>4</sub>Cl conditions, such as in a refinery process facility. Corrosion ; Materials science ; Fourier transform infrared spectroscopy ; Corrosion inhibitor ; Adsorption ; Husk ; Metallurgy ; Chemical engineering ; Nuclear chemistry ; Chemistry ; Organic chemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Etify A. Bakhite | Shaaban K. Mohamed | Chin‐Hung Lai | S. Karthikeyan | Islam S. Marae | Suzan Abuelhassan | Abdelhamid A. E. Soliman | Mohamed Salah K. Youssef | Hatem A. Abuelizz | Joel T. Mague | Rashad Al‐Salahi | Youness El Bakri
Source: ACS Omega (article, 2024-07-01)
Field: Chemistry — Organic Chemistry

Synthesis, Crystal Structure, Hirshfeld Surface Analysis, and Computational Approach of a New Pyrazolo[3,4-<i>g</i>]isoquinoline Derivative as Potent against Leucine-Rich Repeat Kinase 2 (LRRK2) Ethyl-2-((8-cyano-3,5,9a-trimethyl-1-(4-oxo-4,5-dihydrothiazol-2-yl)-4-phenyl-3a,4,9,9a-tetrahydro-1<i>H</i>-pyrazolo[3,4-<i>g</i>]isoquinolin-7-yl)thio)acetate (<b>5</b>) was synthesized, and its structure was characterized by IR, MS, and NMR (<sup>1</sup>H and <sup>13</sup>C) and verified by a single-crystal X-ray structure determination. Compound <b>5</b> adopts a "pincer" conformation. In the crystal, the hydrogen bonds of -H···O, C-H···O, and O-H···S form thick layers of molecules that are parallel to (101). The layers are linked by C-H···π(ring) interactions. The Hirshfeld surface analysis shows that intermolecular hydrogen bonding plays a more important role than both intramolecular hydrogen bonding and π···π stacking in the crystal. The intramolecular noncovalent interactions in <b>5</b> were studied by QTAIM, NCI, and DFT-NBO calculations. Based on structural activity relationship studies, leucine-rich repeat kinase 2 (LRRK2) was found to bind <b>5</b> and was further subjected to molecular docking studies, molecular dynamics, and ADMET analysis to probe potential drug candidacy. Intramolecular force ; Hydrogen bond ; Chemistry ; Crystal structure ; Intermolecular force ; Crystallography ; Natural bond orbital ; Molecule ; Stacking ; Isoquinoline ; Thio- ; Non-covalent interactions ; Stereochemistry ; Organic chemistry Synthesis and biological activity ; Metal complexes synthesis and properties ; Computational Drug Discovery Methods
Authors: Qingsi Lai | Xu, Fanjie | Lin Yao | Zhifeng Gao | Siyuan Liu | Hongshuai Wang | Shuqi Lu | Di He | Liwei Wang | Cheng Wang | Guolin Ke
Source: arXiv (Cornell University) (preprint, 2024-01-08)
Field: Materials Science — Materials Chemistry

End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most automated method only achieved at coarse-grained level. The more difficult and important task of fine-grained crystal structure prediction from PXRD remains unaddressed. This study introduces XtalNet, the first equivariant deep generative model for end-to-end crystal structure prediction from PXRD. Unlike previous crystal structure prediction methods that rely solely on composition, XtalNet leverages PXRD as an additional condition, eliminating ambiguity and enabling the generation of complex organic structures with up to 400 atoms in the unit cell. XtalNet comprises two modules: a Contrastive PXRD-Crystal Pretraining (CPCP) module that aligns PXRD space with crystal structure space, and a Conditional Crystal Structure Generation (CCSG) module that generates candidate crystal structures conditioned on PXRD patterns. Evaluation on two MOF datasets (hMOF-100 and hMOF-400) demonstrates XtalNet's effectiveness. XtalNet achieves a top-10 Match Rate of 90.2% and 79% for hMOF-100 and hMOF-400 in conditional crystal structure prediction task, respectively. XtalNet enables the direct prediction of crystal structures from experimental measurements, eliminating the need for manual intervention and external databases. This opens up new possibilities for automated crystal structure determination and the accelerated discovery of novel materials. Powder diffraction ; Crystallography ; Diffraction ; Materials science ; Crystal structure ; X-ray ; X-ray crystallography ; Chemistry ; Optics ; Physics X-ray Diffraction in Crystallography ; Crystallization and Solubility Studies ; Powder Metallurgy Techniques and Materials
Authors: Abrar Amin Khan | Sazid Noor Rabi | Tousif Jamee | Musanna Galib | Fazle Elahi | Md. Ashiqur Rahman
Source: The Journal of Physical Chemistry B (article, 2024-09-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Effects of Crumpling Stage and Porosity of Graphene Electrode on the Performance of Electrochemical Supercapacitor The performance characteristics of supercapacitors composed of crumpled graphene electrodes and aqueous NaCl electrolytes are investigated through Molecular Dynamics (MD) simulations using a newly developed crumpled graphene-based supercapacitor model. Results suggest that the three-dimensional configuration of crumpled graphene boosts electrolyte-electrode interaction. This improved interaction, which includes a larger ion-accessible zone, increases the specific capacitance of the supercapacitor by roughly 400% (16.4 μF/cm<sup>2</sup>) compared to planar graphene electrodes. Examining the effect of different stages of crumpling and the inclusion of pores on the electrode surface shows that the stages of crumpling substantially influence the supercapacitor performance. A smaller crumpling radius, meaning fully crumpled stage, improves the performance as increased crumpling leads to better packing efficiency, which aids in more ion separation. Furthermore, adding pores on the surface of crumpled graphene improves the ion accessibility by creating additional adsorption sites. An exceptional capacitance of 19.8 μF/cm<sup>2</sup> is obtained for a porosity of 20%. However, the results suggest that the in-plane-porosity of the electrode needs to be optimized as there is a decline in specific capacitance after that point (20% porosity), indicating a suboptimal relationship between the charge distribution, specific surface area (SSA) and the porosity of the electrode. Supercapacitor ; Materials science ; Porosity ; Graphene ; Electrode ; Electrochemistry ; Stage (stratigraphy) ; Composite material ; Nanotechnology ; Chemistry ; Geology Supercapacitor Materials and Fabrication ; Conducting polymers and applications ; Advancements in Battery Materials
Authors: Jithu Joseph | Sreekala Kunchi Kannan | Krishnendu K Surendran | Haritha Hareendrakrishnakumar | Mary Gladis Joseph
Source: Energy Technology (article, 2024-06-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Improved Capacitive Performance of High‐Voltage Electric Double‐Layer Capacitors by Electrolyte Optimization Using Hierarchically Porous Carbon Electrodes Advancement of the voltage window with stringent safety concerns is an imperative strategy to enhance the energy densities and output power delivery of electrical double‐layer capacitors (EDLCs). Solid‐state, water‐in‐salt (WIS), and ionic liquid‐based electrolytes are attractive and ideal choices for high‐voltage EDLCs due to their superior voltage window, electrochemical performance, and predominant safety aspects. Mindful of this, the current report demonstrates the electrochemical performance of new nanoporous carbon electrodes derived from waste dry leaves of Swietenia macrophylla with a high specific surface area (SSA) (1834 m 2 g −1 ) in polymer–gel, WIS, and ionic liquids‐based electrolytes. Symmetric EDLC devices are fabricated using polymer gel solid‐state (PVA–Na 2 SO 4 ), ionic liquids (EMIMBF 4 ), and WIS (21 m LiTFSI) electrolytes with the electrochemical stability windows of (ESW) 2, 2.5, and 2 V, respectively. The assembled devices with Na 2 SO 4 /PVA, EMIMBF 4 , and 21 m LiTFSI (WIS) electrolytes‐based devices exhibit high energy densities of 40, 31, and 25 Wh kg −1 at 0.5 A g −1 and good output power delivery of 5, 6.23, and 3 kW kg −1 at 5 A g −1 with better cyclability features. Self‐discharging studies and systematic evaluation of high‐voltage EDLCs offer a sustainable method to develop high‐performance aqueous and diverse electrolyte‐based supercapacitors. Electrolyte ; Materials science ; Supercapacitor ; Electrochemical window ; Ionic liquid ; Chemical engineering ; Electrochemistry ; Ionic conductivity ; Electrode ; Capacitor ; Nanoporous ; Nanotechnology ; Voltage ; Electrical engineering ; Chemistry ; Organic chemistry Supercapacitor Materials and Fabrication ; Advanced battery technologies research ; Conducting polymers and applications
Authors: Allison M. Hawks | Lillian M. Daniel | Valentino S. Sorto | J. Matthew Mauro | Perry Skiouris | Graham S. Collier
Source: ACS Applied Optical Materials (article, 2024-06-12)
Field: Materials Science — Polymers and Plastics

Expanding Color Control of Anodically Coloring Electrochromes Based on Electron-Rich 1,4-Dihydropyrrolo[3,2-<i>b</i>]pyrroles Anodically coloring electrochromes have received attention in recent years as high-contrast alternatives to cathodically coloring electrochromes due to their superior optical contrast during electrochemical switching. While current systems represent significant progress for organic electrochromics, it is necessary to expand the structural diversity of these materials while simultaneously reducing the hazards associated with synthetic protocols. With these considerations in mind, a family of 1,4-dihydropyrrolo[3,2-<i>b</i>]pyrrole (DHPP) chromophores with varying functionalities along the 2,5-axis was envisioned to accomplish these goals. After predicting different absorbance traits as oxidized molecules with time-dependent density functional theory, DHPP chromophores with varying peripheral functionalities were synthesized in a single aerobic synthetic step via an iron-catalyzed multicomponent reaction and characterized as high-contrast chromophores. In solution, the DHPP chromophores absorb in the ultraviolet region of the electromagnetic spectrum, resulting in color-neutral <i>L</i>*<i>a</i>*<i>b</i>* color coordinates of ∼100, 0, 0. Upon chemical oxidation, each molecule transitions to absorb at various points across the visible spectrum based on the extent of electron-donating ability and can display five distinct colors. Importantly, the chromophores are redox-active and display switching capabilities with an applied electrochemical potential. In conjunction with building fundamental insights into molecular design of DHPP chromophores, the results and synthetic simplicity of DHPPs make them compelling materials for color-controlled high-contrast electrochromes. Control (management) ; Electron ; Chemistry ; Materials science ; Computer science ; Physics ; Artificial intelligence ; Quantum mechanics Conducting polymers and applications ; Electrochemical Analysis and Applications ; Analytical Chemistry and Sensors
Authors: Sidra Altaf 1 | Tasawar Iqbal 2* | Ume Salma 3 | Muhammad Sajid 4 | Iman Basit 5 | Muhammad Zohaib Sabir 6 | Khadija Riaz 7 | Rasheeka Rasheed 8 | Muhammad Umair 9 and Rohma Talha 10
Source: Agrobiological Records (article, 2024-01-01)
Field: Chemistry — Electrochemistry

GOLD NANOPARTICLES FOR THE DETECTION OF ORGANOPHOSPHATE Organophosphate ; Colloidal gold ; Nanoparticle ; Nanotechnology ; Materials science ; Pesticide ; Biology Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Molecular Sensors and Ion Detection