jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yu‐Chun Chiang | Wei-Ting Chin | I‐Wei Chu
Source: Applied Sciences (article, 2025-05-21)
Field: Chemistry — Inorganic Chemistry

Zinc-Decorated and Nitrogen-Functionalized Hierarchical Porous Carbons for Carbon Dioxide Capture This study developed a highly facile method to synthesize Zn-decorated and nitrogen-doped hierarchical porous carbons for carbon dioxide (CO2) adsorption. Zeolitic imidazolate framework-8 (ZIF-8) was used as the raw material, which was subjected to a thermal treatment to obtain ZIF-8-derived carbons (ZDCs) in order to develop nanocarbons with a stable framework structure, a high CO2 adsorption capacity, and high selectivity under normal pressure. The crystallinity evolution of the samples changed from the typical ZIF-8 structure to having features of graphite carbons upon heating. The average particle sizes of the products were between 34 and 105 nm, and the specific surface areas ranged from 618 to 1862 m2/g. The nitrogen and zinc contents gradually decreased with increasing carbonization temperatures, but the changes in the distributions of the functional groups were different. The interactions between CO2 and the ZDCs were significantly enhanced, resulting in a higher isosteric heat of adsorption. The ZIF-8 carbonized at 1123 K exhibited the highest CO2 uptake, i.e., 3.57 mmol/g at 298 K and 101.3 kPa, while higher CO2 uptakes at 15 kPa occurred on the ZIF-8 carbonized at 923 and 1023 K due to their high isosteric heat of adsorption of CO2. The higher adsorption selectivity of Z8-650 for CO2 over N2 may be due to its higher V&lt;0.7nm/Vmi ratio and nitrogen and zinc contents. Consequently, the micropore area ratio and surface functional groups primarily determined the CO2 adsorption capacity at 15 kPa. In addition, an appropriate metal Zn to Zn2+ ratio may have a positive effect on CO2 adsorption. On the other hand, the ultramicropore volume ratio, micropore volume ratio, micropore area, and SSA played more significant roles at 101.3 kPa of pressure. Carbon dioxide ; Porosity ; Zinc ; Materials science ; Chemical engineering ; Chemistry ; Organic chemistry ; Metallurgy ; Composite material ; Engineering Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Membrane Separation and Gas Transport
Authors: Sudheesh Kumar Ethirajan | Ambarish Kulkarni
Source: Journal of Chemical Theory and Computation (article, 2025-10-30)
Field: Chemistry — Inorganic Chemistry

Modeling Diffusion in Metal–Organic Frameworks Using On-the-fly Probability Enhanced Sampling-Based Machine Learning Potentials Machine learning potentials (MLPs) can help bridge the length- and time-scale gaps required to study diverse physicochemical phenomena in nanoporous materials with ab initio accuracy. These MLPs are typically trained on quantum chemical data obtained from traditional molecular dynamics (MD) simulations that predominantly sample near-equilibrium configurations. This often limits the model's ability to describe high-energy, off-equilibrium states required to study rare events. To address this capability gap, we introduce a novel active learning curriculum using the On-the-fly Probability Enhanced Sampling (OPES) method. Using imidazole diffusion in the SALEM-2 metal-organic framework (MOF) as a prototypical example, we apply time-dependent OPES biases with temperature- and distance-based collective variables to systematically sample the most relevant regions of the potential energy surface. This strategy enables nanosecond-scale MD simulations with near-DFT accuracy, capturing both the expected diffusion pathway across the 6-membered window and a previously unreported ring-opening mechanism through the more constrained 4-membered window. The latter process, which involves the transient dissociation of a Zn-N bond, cannot be captured using classical force fields and is prohibitively expensive with DFT. Thus, this study highlights how enhanced sampling methods can overcome data scarcity challenges associated with training MLPs for studying rare events in nanoporous materials. Nanoporous ; Sampling (signal processing) ; Ab initio ; Molecular dynamics ; A priori and a posteriori ; Sample (material) ; Quantum ; Ensemble learning Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Nanopore and Nanochannel Transport Studies
Authors: Miikka Sipilä | Farrokh Mehryary | Sampo Pyysalo | Filip Ginter | Milica Todorović
Source: Communications Materials (article, 2025-11-20)
Field: Materials Science — Materials Chemistry

Question Answering models for information extraction from perovskite materials science literature Abstract Scientific text is a promising source of data in materials science, with ongoing research into utilising textual data for materials discovery. In this study, we developed and tested a Question Answering (QA) approach to extract material-property relationships from scientific publications. QA performance was evaluated for information extraction of perovskite bandgaps based on a human query. We observed considerable variation in results with five different large language models fine-tuned for the QA task. Best extraction accuracy was achieved with the QA MatSciBERT and F1-scores improved on the current state-of-the-art. QA also outperformed three latest generative large language models on the information extraction task, except the GPT-4 model. This work demonstrates the QA workflow and paves the way towards further applications. The simplicity and versatility of the QA approach all point to its considerable potential for text-driven discoveries in materials research. Workflow ; Question answering ; Information extraction ; Point (geometry) ; Data extraction ; Extraction (chemistry) ; Generative grammar ; Matching (statistics) ; Natural language Machine Learning in Materials Science ; Topic Modeling ; Text Readability and Simplification
Authors: N. D. Zhigadlo
Source: Journal of Crystal Growth (article, 2025-11-06)
Field: Materials Science — Materials Chemistry

Discovery of a new magnesium iron boride Mg4Fe1.1B13.9 in the Mg-Fe-B-N system Orthorhombic crystal system ; Boride ; Boron ; Ternary operation ; Crystal structure ; Magnesium ; Phase (matter) ; Lattice (music) Boron and Carbon Nanomaterials Research ; Superconductivity in MgB2 and Alloys ; Rare-earth and actinide compounds
Authors: Viviane de Oliveira Campos | Felipe Fernandes Barbosa | Ellen Kadja Lima de Morais | Dulce Maria de Araújo Melo | Jildimara de Jesus Santana | Gregory S. Patience
Source: The Canadian Journal of Chemical Engineering (article, 2025-04-23)
Field: Materials Science — Surfaces, Coatings and Films

Experimental methods in chemical engineering: Electron probe micro‐analysis— <scp>EPMA</scp> ABSTRACT Electron probe microanalysis (EPMA) is a non‐destructive spectroscopic technique to map the chemical composition—quantitative elemental distribution and layer thickness—with a micro‐scale resolution. An electron beam illuminates the surface of a sample and produces backscattered electrons (BSE), secondary electrons (SE), characteristic X‐rays, and light known as cathodoluminescence (CL). Combining energy dispersive spectrometry with wavelength‐dispersive spectrometry improves trace analysis and differentiates overlapping X‐ray lines, but the detection threshold is not much better than 100 ppm (parts per million). Implementing Monte Carlo simulation with better electronics and software are ongoing research areas to improve the method's precision, sensitivity, and spatial resolution. To detect Li, Be, and B ( 11) requires wavelength‐dispersive X‐ray spectroscopy (WDS), or soft X‐ray emission spectroscopy (SXES), or a combination of BSE/EDS method. Researchers in metallurgy &amp; metallurgical engineering, mineralogy, geochemistry &amp; geophysics, and mining &amp; mineral processing apply the method most. Chemical engineering is ranked 21st among the 250 scientific categories that use the technique. It is also applied to reconstitute works of art and the antiquities. A bibliometric map identified four clusters of research and for each cluster the major nodes were: (1) geochemistry, (2) mechanical properties, microstructure, and alloys, (3) Fe, Cu, and Cr, and (4) phase equilibria. Electron microprobe ; Analytical Chemistry (journal) ; Materials science ; Electron ; Chemistry ; Metallurgy ; Physics ; Environmental chemistry ; Nuclear physics Electron and X-Ray Spectroscopy Techniques ; Corrosion Behavior and Inhibition ; Surface and Thin Film Phenomena
Authors: Prashant Dubey
Source: RSC Advances (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

A comprehensive review on the capability of graphene quantum dots-based/involved platforms for the detection of inorganic ions Substantial contamination in the ecosystem (particularly, in waterbodies) due to the disposal of hazardous substances from superfluous industrial byproducts and other human activities is one of the most serious environmental issues. Although water is among the five basic elements required for all the living beings, it is continuously becoming unsafe and unhygienic for the purpose of drinking and household activities. The presence of heavy metal ions and many toxic anions (beyond their permissible concentration) significantly contributes to water pollution. Therefore, it is judicious to detect inorganic ions in order to avoid adverse situations related to the human health and ecological imbalance. Owing to the easy affordability and unique properties of zero-dimensional graphene quantum dots (GQDs), particularly, high/tunable fluorescence, electronic conductivity, electrocatalytic activity, chemiluminescence (CL) and electrochemiluminescence (ECL), GQDs-based/involved platforms are potentially deployed for the detection of inorganic ions with reasonable selectivity and sensitivity. The versatility of these sensing probes includes the possibility of detection through fluorimetric, colorimetric, electrochemical, CL, and ECL techniques. This review aims to comprehensively inspect the deployment of GQDs-based/involved sensors for the recognition of inorganic ions, highlighting different sensing approaches with the development of performance metrics and providing insights into their underlying mechanisms. Furthermore, this collective outlook on GQDs-based/involved sensors for inorganic ions may help to identify shortcomings in the existing knowledge and influence/inspire new research with better prospects. Graphene ; Human health ; Hazardous waste ; Metal ions in aqueous solution ; Software deployment ; Chemiluminescence ; Electrochemiluminescence ; Ion Carbon and Quantum Dots Applications ; Advanced biosensing and bioanalysis techniques ; Molecular Sensors and Ion Detection
Authors: Marija Iloska | J. Anibal Boscoboinik | Qin Wu | Mónica F. Bugallo
Source: Journal of Chemical Theory and Computation (article, 2025-01-02)
Field: Materials Science — Materials Chemistry

Particle Markov Chain Monte Carlo Approach to Inference in Transient Surface Kinetics In this work, we develop a novel Bayesian approach to study the adsorption and desorption of CO onto a Pd(111) surface, a process of great importance in natural sciences. The motivation for this work comes from the recent availability of time-resolved infrared spectroscopy data and the need for model interpretability and uncertainty quantification in chemical processes. The objective is to learn the relevant parameters that characterize the process: coverage with time, rate constants, activation energies, and pre-exponential factors. Our approach consists of three main schemes: (i) a problem design and probabilistic model for the whole system, (ii) a particle Markov chain Monte Carlo sampler to learn the hidden coverages and rate constant parameters, and (iii) two Bayesian formulations to infer the activation energies and pre-exponential factors. The flexibility of the Bayesian framework allows for uncertainty quantification where possible and integration of mathematical constraints in the model to reflect the system physically. We found that our results for the activation energies and pre-exponential factor are in agreement with those reported in the experimental literature, independently, and we provide discussions on the advantages and disadvantages as well as applicability to other systems. Markov chain Monte Carlo ; Monte Carlo method ; Bayesian inference ; Statistical physics ; Computer science ; Particle filter ; Exponential function ; Probabilistic logic ; Interpretability ; Bayesian probability ; Physics ; Machine learning ; Mathematics ; Artificial intelligence ; Statistics Catalytic Processes in Materials Science ; Air Quality Monitoring and Forecasting ; Machine Learning in Materials Science
Authors: Liang Chen | Diptesh Das | Jiang Guo | Ryo Tamura | Zetian Mao | Koji Tsuda
Source: Communications Physics (article, 2025-11-26)
Field: Materials Science — Materials Chemistry

Predicting symmetric structures of large crystals with GPU-based Ising machines Solving black-box optimization problems with Ising machines is increasingly common in materials science. However, their application to crystal structure prediction (CSP) is still ineffective due to symmetry agnostic encoding of atomic coordinates. We introduce CRYSIM, an algorithm that encodes the space group, the Wyckoff positions combination, and coordinates of independent atomic sites as separate variables. This encoding reduces the search space substantially by exploiting the symmetry in space groups. When CRYSIM is interfaced to Fixstars Amplify, a GPU-based Ising machine, its prediction performance is competitive with CALYPSO and Bayesian optimization for crystals containing more than 150 atoms in a unit cell. Although it is not realistic to interface CRYSIM to current small-scale quantum devices, it has the potential to become the standard CSP algorithm in the coming quantum age. Predicting stable structures of large crystals, unit cells containing tens or even hundreds of atoms, has been a long-standing challenge. In this article, the authors present a combinatorial optimization-based algorithm that leverages the inherent symmetry of crystals, making it potentially achievable, especially with future implementation on quantum hardware. Ising model ; Symmetry (geometry) ; Quantum ; Encoding (memory) ; Space (punctuation) ; Bayesian optimization ; Unit (ring theory) ; Quantum computer ; Crystal (programming language) Machine Learning in Materials Science ; Quantum Computing Algorithms and Architecture ; Quantum many-body systems
Authors: Khazaal Hameed Khazaal | Omar A. Alwash | Abbas Mezaal Karafe
Source: Annales de Chimie Science des Matériaux (article, 2025-04-30)
Field: Materials Science — Materials Chemistry

Environmentally Sustainable Alkyd-Based SiO₂–CuO Nanocoatings for Industrial Corrosion Protection: Synergistic, Structural, and Electrochemical Evaluation This study investigates the development of anticorrosion alkyd coatings enhanced with a hybrid nanofiller system comprising silicon dioxide (SiO) and copper oxide (CuO) nanoparticles.The primary objective was to determine the optimal nanoparticle ratio and loading concentration to improve the protective performance on mild steel substrates.Electrochemical impedance spectroscopy (EIS) revealed that a SiO: CuO weight ratio of 0.61:0.39 at a total concentration of 0.84 wt.% exhibited the highest corrosion resistance, achieving an impedance of 8.79 10 cm.Scanning electron microscopy (SEM) confirmed a uniform nanofiller distribution with no microstructural defects.Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses verified the successful chemical incorporation and crystallinity of the nanocomposite.Thermogravimetric analysis (TGA) indicated enhanced thermal stability, while adhesion testing following ASTM D3359 Method A demonstrated improved bonding with the substrate.Compared to a commercial epoxy-phenolic coating (TK-34), the developed coating retained 69% of its initial impedance after 72 hours of salt spray exposure, indicating superior durability.The synergistic interaction between hydrophobic CuO and insulating SiO significantly contributed to enhanced barrier and electrochemical properties.These findings highlight the practical viability of SiO-CuO nanocomposite coatings in extending the service life of steel infrastructures, offering a cost-effective and sustainable alternative to conventional protective systems. Alkyd ; Materials science ; Corrosion ; Electrochemistry ; Nanotechnology ; Chemical engineering ; Metallurgy ; Chemistry ; Electrode ; Engineering ; Coating Corrosion Behavior and Inhibition ; Anodic Oxide Films and Nanostructures ; Electrophoretic Deposition in Materials Science
Authors: Hummaira Khan | Yujun Song
Source: Coatings (article, 2025-12-18)
Field: Materials Science — Materials Chemistry

Progress and Perspectives in Nanostructured Thin Films The field of nanostructured thin films is experiencing rapid development, with materials scientists creating ever more fascinating structures at the nanoscale or even subnanoscale [...] Thin film ; Nanoscopic scale ; Nanostructure ; Field (mathematics) ; Scale (ratio) Copper-based nanomaterials and applications ; Chemical and Physical Properties of Materials ; 2D Materials and Applications
Authors: Evgenii Strugovshchikov | Viktor Mandrolko | Dominika Lesnicki | Mariachiara Pastore | Laurent Chaput | Mykola Isaiev
Source: Journal of Colloid and Interface Science (article, 2025-09-12)
Field: Materials Science — Materials Chemistry

Interfacial behavior from the atomic blueprint: Machine learning-guided design of spatially functionalized α-SiO2 surfaces Surface modification ; Density functional theory ; Colloid ; Surface energy ; Molecular dynamics ; Hydrogen bond ; Surface (topology) ; Ab initio Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Catalytic Processes in Materials Science
Authors: E. Grigorova | Gülhan Çakmak | Hakan H. Yuce | П. В. Марков
Source: Inorganics (article, 2025-09-04)
Field: Materials Science — Materials Chemistry

Electrochemical and Gas-Solid Hydrogen Storage Properties of a Multi-Metal Magnesium-Based Alloy Obtained by Ball Milling The hydrogen sorption and electrochemical properties of the alloy Mg50Ni12.5Al12.5V12.5Fe12.5 synthesized by ball milling under the protected atmosphere of argon for 50 h in a planetary ball mill are investigated. The significantly fast rate of absorption reaction is observed along with the hydrogen absorption capacity of 2.04 wt.% H2 at temperatures 200 and 300 °C and at a pressure of 1 MPa. Even at room temperature, the absorption capacity is relatively high, and it is about 1.6 wt.% H2. The alloy ball milled for 50 h and the alloy after cycling and hydrogenation were characterized by X-ray diffraction analyses, SEM, and TEM. The prepared alloy was tested as an anode in a Ni/MH battery in a 6 M KOH electrolyte. Galvanostatic and potentiostatic discharge modes were employed, revealing activation after the third cycle and giving a discharge capacity of 257 mAh/g. Hydrogen storage ; Magnesium ; Materials science ; Magnesium alloy ; Alloy ; Electrochemistry ; Ball mill ; Hydrogen ; Metallurgy ; Metal ; Chemistry ; Electrode ; Physical chemistry Hydrogen Storage and Materials ; Hybrid Renewable Energy Systems ; Ammonia Synthesis and Nitrogen Reduction
Authors: Siwasit Pitjamit | Norrapon Vichiansan | Komgrit Leksakul
Source: Journal of Engineering and Technological Sciences (article, 2025-01-30)
Field: Materials Science — Materials Chemistry

Innovative Approach to Graphene Film Synthesis: Factorial Design in PECVD Experiments Graphene, a two-dimensional carbon allotrope, has garnered significant interest due to its exceptional properties and diverse applications. This study investigates the optimization of graphene synthesis parameters using plasma-enhanced chemical vapor deposition (PECVD) to enhance film properties and broaden their application potentials. Using a comprehensive factorial design approach, factors including electric power (ranging from 60 to 100 W), the acetylene-to-hydrogen ratio (ranging from 30:70 to 50:50), and discharge time (ranging from 10 to 30 minutes) were systematically varied, and film thickness and the D/G ratio served as response variables. The experimental results revealed the significant effects of these parameters on film thickness, with optimal conditions identified as an electric power of 100 W, an acetylene-to-hydrogen ratio of 50:50, and a discharge time of 10 min. The average film thickness ranged from 41.51 to 253.80 nm. Morphological and structural analyses using atomic force microscopy and Raman spectroscopy elucidated the impact of synthesis parameters on film characteristics, with the D/G ratio varying from 0.75 to 1.8, indicating the degree of graphitization and defect density. Furthermore, surface properties and wettability were assessed using contact angle measurements, providing insights into surface interactions crucial for various applications. This study culminates in discussions on the implications for graphene synthesis optimization and its potential applications across diverse fields. Overall, this research contributes to advancing the understanding of graphene synthesis methodologies and underscores its significance in driving technological innovations. Graphene ; Factorial experiment ; Plasma-enhanced chemical vapor deposition ; Fractional factorial design ; Materials science ; Mathematics ; Composite material ; Engineering drawing ; Nanotechnology ; Engineering ; Statistics ; Chemical vapor deposition Graphene research and applications ; Molecular Junctions and Nanostructures
Authors: Noor W. Saleh Rabee | Tagreed N-A Omar
Source: Iraqi Journal of Pharmaceutical Sciences ( P-ISSN 1683 - 3597 E-ISSN 2521 - 3512) (article, 2025-02-15)
Field: Materials Science — Polymers and Plastics

Molecular Docking, ADMET Study, Synthesis, Anti-inflammatory, and Antimicrobial Screening of New NSAIDs Conjugated with Gabapentin The free –COOH of NSAIDs is thought to be one of the causes that responsible for the GI irritation associated ,in this study NSAIDs were conjugated with gabapentin through ester bond using chloroacetyl chloride as a spacer. The methodology of this work consist three steps: Gabapentin was reacted with para substituted benzaldehyde to protect the free amine group via converting it to imine (Schiff base) II(1a-b) , Esterification by the reaction of NSAID with chloroacetyl chloride to give the corresponding ester III , The reaction of III with II(1a-b) to give the final product III(1a-h). The structures of these compounds were confirmed and characterized by attenuated total reflectance -Fourier transform infrared spectroscopy (ATR-FTIR ) ,1HNMR and physicochemical properties . In silico evaluation methods were done before synthesis through molecular docking via genetic optimization for ligand docking (Schrödinger) Suite software with COX-1 enzyme, the prepared compounds showed good activity against standard compounds, theoretically and experimentally. An ADMET analysis was performed to anticipate the pharmacokinetic properties of the final synthesized drugs and indicate that the final compounds contain drug-like features.Also the preliminary pharmacological Evaluation . Synthesized compounds were screened for their antimicrobial activity, and show moderate to high inhibition against both gram-positive and gram-negative bacteria, and a high antifungal activity. The anti-inflammatory activity was also tested for the final compounds and it showed a good activity . Antimicrobial ; Docking (animal) ; Conjugated system ; Gabapentin ; Anti-inflammatory ; Pharmacology ; Chemistry ; Combinatorial chemistry ; Medicine ; Organic chemistry Synthesis and properties of polymers ; Analytical Methods in Pharmaceuticals ; Synthesis of heterocyclic compounds