jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mutairu O. Ajiboye | A.A. Daniyan | Paul C. Okonkwo | Lukman A. Aminu | Lukman O. Olasunkanmi | Ibrahim Waziri | L.E. Umoru | Oludolapo Akanni Olanrewaju | O.O. Ige
Source: Discover Electrochemistry. (article, 2025-11-06)
Field: Materials Science — Materials Chemistry

Gravimetric and microstructural assessment of Schiff base inhibitors in Nigerian tar sand processing Abstract This study presents the first investigation of halogen-substituted aniline-derived Schiff bases (SB1, SB2, SB3) as corrosion inhibitors for mild steel in Nigerian tar sand environments. Key novelty includes introducing inhibition power as a new gravimetric-based performance metric for alkaline conditions where electrochemical methods are limited. Tar sand from Ilubirin was processed with 0.58 M NaOH at 90 °C for 24 h with inhibitors at concentrations of 25–150 ppm. Gravimetric analysis, SEM–EDS, and Langmuir isotherm modelling revealed a significant corrosion rate with effectiveness order SB3 &gt; SB2 &gt; SB1. SB3 achieved 94.4% inhibition efficiency at 150 ppm due to a favourable molecular structure promoting enhanced adsorption. Langmuir analysis confirmed chemisorption (ΔG°ads &gt; − 20 kJ mol −1 ), while microstructural evaluation demonstrated excellent surface protection. This research demonstrates the effectiveness of inhibition power in assessing corrosion inhibitors using gravimetric data due to the limitations of electrochemical measurement in tar sand environments. The study concludes that Schiff-based compounds offer promising solutions for corrosion control in a harsh alkaline tar sand processing environment. Gravimetric analysis ; Corrosion ; tar (computing) ; Chemisorption ; Thermogravimetric analysis ; Schiff base Corrosion Behavior and Inhibition ; Petroleum Processing and Analysis ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Aniza Ibrahim | Juman A. Naser | Emad S. Taiyh | Z. Hassan | J Mohammed
Source: Analytical Methods in Environmental Chemistry Journal (article, 2025-06-01)
Field: Chemistry — Analytical Chemistry

Removal and determination of Malachite Green dye using nanofiber membranes and UV-Vis spectrophotometer The removal of malachite green (MG) dye on nanofiber membranes, which were prepared by the electrospinning technique, was studied after preparing a suitable resin to act as an efficient adsorbent. A UV-Vis spectrophotometer determined the MG concentration. The morphology of nanofiber membranes with an average diameter of 550 nm was studied by SEM, EDX, and XPS techniques. The batch approach was used to study the factors affecting the adsorption, which included the effect of equilibrium time, the adsorbent dose, the initial dye concentration, and temperature. The adsorption isotherms were also studied according to the Freundlich and Langmuir models and the thermodynamic functions. The results showed that the maximum adsorption efficiency was 92.946% at 318 K, and the adsorption capacity of the adsorbent was 18.4 mg g-1. Analytical chemistry features such as the limit of detection (LOD: 0.3 mg L-1), limit of quantification (LOQ: 0.9 mg L-1), and linear range (1-50 mg L-1) were obtained. From the correlation coefficient values, it was found that the Langmuir model is more suitable than the Freundlich model for describing the general adsorption isotherm. Also, the amount of dye molecule adsorption increases with increasing temperature (Endothermic Process), and there is more random movement on the nanofiber membrane than in the aqueous solution. The process occurs spontaneously as indicated by the positive values of ΔH° and ΔS° and the negative value of ΔG°. Malachite green ; Nanofiber ; Membrane ; Materials science ; Chemistry ; Chromatography ; Nanotechnology ; Adsorption ; Biochemistry ; Organic chemistry Dye analysis and toxicity ; Identification and Quantification in Food
Authors: Pemika Hirankittiwong | Sirikanjana Thongmee | Sougata Ghosh | Praphat Kawicha
Source: E3S Web of Conferences (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Nematic liquid crystal alignment based biosensor for plant pathogen detection The orientational mechanism of liquid crystal (LC) molecules in biosensors, optical equipment and other applications relies on its sensitivity, real-time detection and response at a specific location. In our study, we used nematic LC (5CB) for the rapid detection of specific DNA from plant pathogenic bacteria; Pectobacterium carotovorum , Xanthomonas citri subsp. citri , and Ralstonia solanacearum . Optical images of genomic DNA mixed with 5CB exhibited a changing anchoring transition. The speed of the planar-homeotropic configuration for R. solanacearum is faster perfect dynamic than X. citri subsp. citri . Conversely, in the case of P. carotovorum , an unchanged mechanism was observed. It can detect the DNA from plant pathogenic bacteria. Moreover, voltage can drive the reorientation of molecules into ITO glass cells. We found distinct responses at different voltages. The charge transfer was measured in an ITO glass cell between 5CB and DNA. We successfully identified the presence of the plant pathogenic bacteria by analyzing the genomic DNA and PCR products, partial 16S rRNA gene, of the pathogenic sensing. These results affirm that the LC based biosensor presents a simple, reliable, and accurate detection method. Liquid crystal ; Biosensor ; Materials science ; Nanotechnology ; Pathogen ; Chromatography ; Optoelectronics ; Chemistry ; Biology ; Microbiology Liquid Crystal Research Advancements ; Photonic Crystals and Applications ; Electrowetting and Microfluidic Technologies
Authors: Qian Liu | Xinxi Huang | Yihao Xiao | Y.S. Feng | Wanbin Li
Source: Small (article, 2025-12-22)
Field: Chemistry — Inorganic Chemistry

Rapid and Scalable Channel‐End‐Sealing Assembly of Flexible 20‐nm Co‐Continuous MOF Membranes for Ultrafast Gas Separation Metal-organic framework (MOF) membranes with sub-nanometer pore systems hold great potential for efficient gas separations. However, the rational designing and scalable manufacturing of MOF membranes face critical challenges, including stringent synthesis conditions, prolonged processing times, excessive reagent consumption, limited scalability, poor reproducibility, uncontrollable thickness, and mechanical fragility. In this study, we report a bioinspired channel-end-sealing assembly strategy for facile, rapid, and scalable production of flexible, ultrathin (≈20 nm), large-area (>1000 cm<sup>2</sup>) co-continuous MOF membranes. Inspired by capping the unit cells of honeycombs, we present sealing the channel ends of polymer substrates to form defect-free membranes, through establishing controllable and self-terminating crystallization at the nanoconfined interfaces between biphasic precursor systems via stoichiometric modulation. This strategy enables reproducible manufacturing of MOF membranes within 5 min at room temperature with low precursor consumption of 1.0 mL cm<sup>-2</sup>. Moreover, the resulting MOF membranes exhibit ultrafast and stable sieving properties with H<sub>2</sub> permeance as high as 13900 gas permeation units and H<sub>2</sub>/CO<sub>2</sub> selectivity up to 40.6 at 150 °C, outperforming state-of-the-art membranes. Crucially, the membranes can maintain their performance after bending with a curvature of 200 m<sup>-1</sup>. These findings pave the way for industrial-scale production and application of MOF membranes. Permeance ; Membrane ; Gas separation ; Permeation ; Polymer ; Scalability ; Ultrashort pulse Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Covalent Organic Framework Applications
Authors: I. N. Klyukin | Anastasia V. Kolbunova | Alexander S. Novikov | Alexandra A. Klyukina | К. Yu. Zhizhin | Nikolay T. Kuznetsov
Source: Computation (article, 2025-12-05)
Field: Chemistry — Physical and Theoretical Chemistry

Theoretical Insight into Non-Covalent Complexes of Closo-Borate Anions [BnHn−1X]y− with Glycine Non-covalent contacts play a significant role in binding between fragments in supramolecular assemblies. Understanding the non-covalent binding capabilities of closo-borate anions and their derivatives is a significant research challenge, due to their ability to interact with biomolecules. The present work was focused on the theoretical study of non-covalent complexes between glycine and closo-borate anions [BnHn−1X]y− (X = H, NH3, OH, SH, F; n = 10, 12; y = 1, 2). The main binding patterns between glycine and cluster systems were defined, and the effect of the exo-polyhedral substituent on the stability of non-covalent complexes was analysed. Complexes based on ammonium and hydroxy derivatives of closo-borate anions [BnHn−1X]y− (X = NH3, OH; n = 10, 12; y = 1, 2) were the most stable among all the derivatives considered. The findings of this work can be applied to the design of non-covalent complexes of closo-borate systems with biomolecules. Glycine ; Substituent ; Supramolecular chemistry ; Cluster (spacecraft) ; Ammonium ; Density functional theory Crystallography and molecular interactions ; Boron Compounds in Chemistry ; Hydrogen Storage and Materials
Authors: Moses Adondua Abah
Source:  (article, 2025-12-08)
Field: Materials Science — Biomaterials

Biodegradable Polymers: Synthesis and Applications Biodegradable polymers have gained significant attention as eco-friendly alternatives to traditional plastics. Derived from renewable resources like plants, animals, and microorganisms, these polymers can degrade naturally, reducing environmental pollution. Common biodegradable polymers include Poly Lactic Acid (PLA), Poly Hydroxyalk Anoates (PHA), and starch-based polymers. Applications range from packaging and textiles to medical devices and tissue engineering. The shift towards biodegradable polymers aims to mitigate plastic waste, decrease greenhouse gas emissions, and promote sustainable development. This review explores biodegradable polymers with emphasis on their synthesis and applications. Research has led to significant advancements in biodegradable polymer synthesis and applications. Findings from this study revealed that PLA, for instance, has shown excellent biodegradability and biocompatibility, making it suitable for food packaging, disposable cutlery, and medical implants. PHAs, produced by microorganisms, exhibit similar properties to conventional plastics and are used in medical devices, tissue engineering, and packaging. Starch-based polymers have been developed for biodegradable plastics, offering a costeffective and renewable alternative. Studies have also explored blending biodegradable polymers with other materials to enhance mechanical properties and degradation rates. For example, PLA-PHA blends have shown improved toughness and crystallinity. Furthermore, biodegradable polymers have been used in controlled release systems, delivering drugs, pesticides, and fertilizers in a targeted and sustainable manner. Biodegradable polymers offer a promising solution to environmental pollution and sustainable development. With advancements in synthesis and applications, these materials can replace traditional plastics in various industries, reducing plastic waste and promoting eco-friendly practices. Continued research and development are essential to improve performance, scalability, and affordability, ensuring a greener future for generations to come. Biodegradable polymer ; Biodegradation ; Polymer ; Renewable resource ; Biodegradable plastic ; Bioplastic ; Environmental pollution ; Renewable energy biodegradable polymer synthesis and properties ; Nanocomposite Films for Food Packaging ; Polymer Science and PVC
Authors: Jiacheng Xiong | Yuqi Shi | Wei Zhang | Runze Zhang | Zhiyi Chen | Chun Zeng | Xun Jiang | Duanhua Cao | Zhaoping Xiong | Mingyue Zheng
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-05-12)
Field: Materials Science — Materials Chemistry

Bridging 3D Molecular Structures and Artificial Intelligence by a Conformation Description Language Abstract Artificial intelligence, particularly language models (LMs), is reshaping research paradigms across scientific domains. In the fields of chemistry and pharmacy, chemical language models (CLMs) have achieved remarkable success in two-dimensional (2D) molecular modeling tasks by leveraging one-dimensional (1D) representations of molecules, such as SMILES and SELFIES. However, extending these successes to three-dimensional (3D) molecular modeling remains a significant challenge, largely due to the absence of effective 1D representations for capturing 3D molecular structures. To address this gap, we introduce ConfSeq, a novel molecular conformation description language that integrates SMILES with internal coordinates including dihedral angles, bond angles, and pseudo-chirality. This design naturally ensures SE(3) invariance, while preserving the human readability and conciseness characteristic of SMILES. ConfSeq enables the reformulation of a range of 3D molecular modeling tasks, such as molecular conformation prediction, 3D molecular generation, and 3D molecular representation, into sequence modeling problems. Then, by simply employing a standard Transformer architecture, we achieve state-of-the-art performance on various benchmark sets. Furthermore, compared to widely used diffusion-based approaches in 3D molecular modeling, the ConfSeq-based method offers unique advantages in inference efficiency, generation controllability, and enables scoring of generated molecules. We believe that ConfSeq can serve as a foundational tool, advancing the development of sequence-based 3D molecular modeling methods. Bridging (networking) ; Computer science ; Natural language processing ; Artificial intelligence ; Cognitive science ; Psychology Machine Learning in Materials Science ; Catalysis and Oxidation Reactions
Authors: Axel Forslund | Jong Hyun Jung | Yuji Ikeda | Blazej Grabowski
Source: npj Computational Materials (article, 2025-12-20)
Field: Materials Science — Materials Chemistry

Free-energy perturbation in the exchange-correlation space accelerated by machine learning: application to silica polymorphs We propose a free-energy-perturbation approach accelerated by machine-learning potentials to efficiently compute transition temperatures and entropies for all rungs of Jacob's ladder. We apply the approach to the dynamically stabilized phases of SiO<sub>2</sub>, which are characterized by challengingly small transition entropies. All investigated functionals from rungs 1-4 fail to predict an accurate transition temperature by 25-200%. Only by ascending to the fifth rung, within the random phase approximation, an accurate prediction is possible, giving a relative error of 5%. We provide a clear-cut procedure and relevant data to the community for, e.g., developing and evaluating new functionals. Perturbation (astronomy) ; Phase transition ; Space (punctuation) ; Phase space ; Perturbation theory (quantum mechanics) ; Random error Machine Learning in Materials Science ; Material Dynamics and Properties ; Phase Equilibria and Thermodynamics
Authors: Atanu Roy | Arup Chakraborty | Geetha Valurouthu | Yuan Zhang | Gil Bergman | Netanel Shpigel | M. Saiful Islam | Daniel Mandler | Yury Gogotsi
Source: ChemRxiv (preprint, 2025-01-31)
Field: Materials Science — Materials Chemistry

Suppression of Halide Ions Crossover in Zn-halide Batteries by 2D MXene Membranes A significant challenge in the practical application of Zn-halide batteries is their rapid self-discharge caused by the migration of halide species from the positive electrode to the metallic Zn. These highly oxidizing anions react with the deposited Zn, leading to its dissolution and the consequent loss of capacity. To address this issue, selective membranes such as Nafion or polyolefin separators are commonly used to mitigate anion crossover. However, aside from their high costs, these membranes often fail to prevent the transport of corrosive halides. Recently, there has been growing interest in utilizing Ti3C2Tx (MXene) for membrane applications. The negatively charged surface of MXene sheets and their ability to form free-standing films stable in halide electrolytes make them promising candidates for selective membranes. This study demonstrates the effective use of MXene membranes to mitigate the crossover of halide ions (Cl−, Br−, and I−). The ion transport mechanism was elucidated through a systematic electrochemical analysis combined with measurements of the physical properties of the electrolyte solutions and atomistic insights from ab-initio molecular dynamics simulations. Compared to Nafion, the developed MXene membrane exhibits a significantly improved anion selectivity, highlighting its potential as a compelling choice for use in batteries utilizing halide-ion based electrolytes. Halide ; Membrane ; Electrolyte ; Nafion ; Inorganic chemistry ; Electrochemistry ; Chemistry ; Materials science ; Chemical engineering ; Polyolefin ; Dissolution ; Electrode ; Nanotechnology ; Organic chemistry ; Physical chemistry MXene and MAX Phase Materials ; Covalent Organic Framework Applications ; Advanced Battery Materials and Technologies
Authors: Atinafu Bergene Bassa | Shemelis Hailu Adula | Muluken Bergene Bassa | Taame Abraha Berhe
Source:  (article, 2025-11-05)
Field: Chemistry — Organic Chemistry

Croton macrostachyus Bark Extract-Assisted Sustainable Synthesis of CuO Nanomaterials for 4-Nitrophenol Catalytic Reduction and Antibacterial Applications Environmental pollution and sustainability issues require environmentally friendly solutions. In this study, we synthesized copper oxide nanoparticles (CuO NPs) using a sol––gel method with Croton macrostachyus bark extract for application in environmental remediation and as an antimicrobial agent. The uncalcined CuO NPs (200 mg/mL) demonstrated strong antimicrobial activity, with inhibition zones of 22 ± 1.3 mm against Staphylococcus aureus and 11 ± 0.7 mm against Escherichia coli. Moreover, the nanoparticles efficiently catalyzed the reduction of 4-nitrophenol, achieving 98.79% degradation within 8 min (Kapp = 0.507 min−1). These findings show that CuO NPs synthesized from the extract of Croton macrostachyus provide a sustainable and efficient approach for addressing both environmental pollution and antibacterial resistance. Antimicrobial ; Nanomaterials ; Bark (sound) ; Environmentally friendly ; Environmental pollution ; Environmental remediation ; Antibacterial activity ; Catalysis Nanomaterials for catalytic reactions ; Copper-based nanomaterials and applications ; Nanoparticles: synthesis and applications
Authors: Marvin Scherlo | Dominic Phillips | Ricarda Künne | Emiliano Ippoliti | Klaus Gerwert | Carsten Kötting | Paolo Carloni | Antonia S. J. S. Mey | Till Rudack
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-07-26)
Field: Chemistry — Analytical Chemistry

IR spectroscopy: from experimental spectra to high-resolution structural analysis by integrating simulations and machine learning Abstract Understanding biomolecular function at the atomic scale requires detailed insight into the structural changes underlying dynamic processes. Vibrational infrared (IR) spectroscopy—when paired with biomolecular simulations and quantum-chemical calculations—determines bond length variations on the order of 0.01 Å, providing insights into these structutral changes. Here, we address the forward problem in IR spectroscopy: predicting high-accuracy vibrational spectra from known molecular structures identified by biomolecular simulations. Solving this problem lays the groundwork for the inverse problem: inferring structural ensembles directly from experimental IR spectra. We evaluate two computational approaches, normal mode analysis and Fourier-transformed dipole autocorrelation, against experimental IR spectra of N-Methylacetamide, a prototypical model for peptide bond vibrations. Spectra are derived from simulation models at multiple levels of theory, including hybrid quantum mechanics/molecular mechanics, machine-learned and classical molecular mechanics approaches. Our results highlight the capabilities and limitations of current theoretical biophysical approaches to decode structural information from experimental vibrational spectroscopy data. These insights underscore the potential of future artificial intelligence (AI)-enhanced models to enable direct IR-based structure determination. For example, resolving the so far experimentally inaccessible structures of toxic oligomers involved in neurodegenerative diseases, enabling improved disease diagnostics and targeted therapies. TOC Graphic Spectroscopy ; Resolution (logic) ; Spectral line ; Infrared spectroscopy ; High resolution ; Low resolution ; Materials science ; Computer science ; Computational physics ; Analytical Chemistry (journal) ; Artificial intelligence ; Physics ; Chemistry ; Remote sensing ; Geology ; Chromatography ; Quantum mechanics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Karol Skiba | Roman Kinasz
Source: Budownictwo i Architektura (article, 2025-06-25)
Field: Materials Science — Materials Chemistry

An overview of radiation exposure effects on concrete in nuclear power plants This review summarizes the effects of radiation exposure on the properties of concrete, with a focus on the impacts on compressive and tensile strength, elastic modulus, weight loss, and dimensional changes. Ionising radiation, including neutron exposure, can significantly alter the mechanical and physical properties of concrete used in nuclear energy facilities. Recent advancements in developing ultra-high-performance concrete (UHPC) and radiation shielding concrete with heavy natural aggregates offer promising alternatives for radiation shielding. AI-driven models can support this by predicting material performance under irradiation. Nuclear power ; Radiation ; Radiation exposure ; Environmental science ; Nuclear engineering ; Engineering ; Nuclear physics ; Nuclear medicine ; Physics ; Medicine Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies ; Radiation Shielding Materials Analysis
Authors: S. Richter | Thomas D. Kühne
Source: Research Square (preprint, 2025-04-22)
Field: Materials Science — Materials Chemistry

Regressing the self-consistent Hamiltonian and density from the non-self-consistent Hamiltonian Self consistent ; Hamiltonian (control theory) ; Covariant Hamiltonian field theory ; Mathematical physics ; Physics ; Statistical physics ; Classical mechanics ; Mathematics ; Hamiltonian system ; Quantum electrodynamics ; Mathematical optimization Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Protein Structure and Dynamics
Authors: Hagen Eckert | Sebastian A. Kube | Simon Divilov | Anthony Gordon Guest | Adam C. Zettel | David Hicks | Sean D. Griesemer | Nico Hotz | Xiomara Campilongo | Siya Zhu | Axel van de Walle | Jan Schroers | Stefano Curtarolo
Source: ArXiv.org (preprint, 2025-01-29)
Field: Chemistry — Physical and Theoretical Chemistry

Soliquidy: a descriptor for atomic geometrical confusion Tailoring material properties often requires understanding the solidification process. Herein, we introduce the geometric descriptor Soliquidy, which numerically captures the Euclidean transport cost between the translationally disordered versus ordered states of a materials. As a testbed, we apply Soliquidy to the classification of glass-forming metal alloys. By extending and combining an experimental library of metallic thin-films (glass/no-glass) with the aflow.org computational database (geometrical and energetic information of mixtures) we found that the combination of Soliquity and formation enthalpies generates an effective classifier for glass formation. Such classifier is then used to tackle a public dataset of metallic glasses showing that the glass-agnostic assumptions of Soliquity can be useful for understanding kinetically-controlled phase transitions. Confusion ; Geometry ; Theoretical physics ; Physics ; Computer science ; Mathematics ; Psychology ; Psychoanalysis History and advancements in chemistry