jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: T. Mohammed Faheem | Vinod Kumar Sharma | A. Shaija | Bhaskar Das | Ranjith Krishna Pai
Source: Asia-Pacific Journal of Chemical Engineering (review, 2025-11-26)
Field: Materials Science — Materials Chemistry

Innovative Approach to Hydrogen Purification: A Review on the Role of Metal Hydrides ABSTRACT Metal hydrides, renowned for their unique hydrogen bonding capabilities, have emerged as pivotal materials in the energy sector, particularly for hydrogen storage and purification applications. Their ability to store hydrogen reversibly under moderate conditions has positioned them at the forefront in hydrogen‐based energy systems. This review systematically examines metal hydride–based hydrogen purification technology, addressing a significant gap in the literature where focused reviews on this specific application remain relatively scarce. The review provides a critical analysis of diverse hydrogen production methods, including steam methane reforming, gasification and pyrolysis and their subsequent purification requirements to meet stringent ISO 14687:2019 standards. Various industrial purification techniques including cryogenic separation, pressure swing adsorption and membrane‐based methods are critically evaluated. Special emphasis is placed on metal hydride systems, which demonstrate lower initial capital costs, reduced operational expenditures and operation at near‐ambient conditions. By consolidating scattered research findings from experimental, computational and numerical studies spanning four decades, this review systematically organises fundamental principles, materials selection criteria, thermodynamic considerations, kinetic modelling approaches, reactor design strategies, impurity tolerance mechanisms and current research trends, thereby advancing the practical implementation of this sustainable purification technology for the emerging hydrogen economy. Hydrogen ; Hydrogen production ; Steam reforming ; Pressure swing adsorption ; Hydrogen fuel ; Hydride ; Hydrogen storage ; Hydrogen purifier ; Energy carrier Hydrogen Storage and Materials ; Catalysts for Methane Reforming ; Hybrid Renewable Energy Systems
Authors: Khushal P. Mudholkar | Madhu G. Kottad | Shivanand V. Angadi | L. D. Horakeri | Sushant S. Kakati | Shridhar N. Mathad | Chidanandayya S. Hiremath | R. B. Pujar | M.S. Bannur
Source: Characterization and Application of Nanomaterials (article, 2025-05-18)
Field: Materials Science — Materials Chemistry

Role of aluminium doping in tailoring the structural, electrical, and magnetic characteristics of Li-Co ferrites using sol-gel auto-combustion synthesis This study examined the impact of aluminium doping on the structural, electrical, and magnetic properties of Li(0.5)Co(0.75)AlxFe(2−x)O4spinel ferrites (x= 0.15 to 0.60). The samples were synthesised using the sol-gel auto-combustion technique, and they were examined using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fouriertransform infrared spectroscopy (FTIR), dielectric measurements, and vibrating sample magnetometry (VSM). All samples possessed a single-phase cubic spinel structure with Fd-3m space group, according to XRD analyses. SEM images showed the creation of homogeneous particles with an average size of about 21 nm. All samples had spinel ferrite phases, confirmed from FTIR spectra. DC electrical conductivity studies showed that the conductivity increased with increasing aluminium content up tox= 0.45 before dropping atx= 0.60. The maximum saturation magnetization value was found atx= 0.45, according to VSM measurements, which demonstrated that the magnetic characteristics were strongly correlated with the amount of aluminium. Aluminium ; Doping ; Combustion ; Materials science ; Sol-gel ; Chemical engineering ; Nanotechnology ; Composite material ; Chemistry ; Optoelectronics ; Organic chemistry Magnetic Properties and Synthesis of Ferrites ; Advancements in Battery Materials ; Semiconductor materials and interfaces
Authors: Wenkai Ning | Musen Li | Jeffrey R. Reimers | Rika Kobayashi
Source: Digital Discovery (article, 2025-12-10)
Field: Materials Science — Materials Chemistry

Optimizing data extraction from materials science literature: a study of tools using large language models Benchmarking five AI tools on materials science literature shows promising capabilities, but performance remains inadequate for large-scale data extraction. Our analysis offers detailed insight and guidance for future methodological improvements. Data extraction ; Data collection ; Information extraction ; Data modeling ; Data analysis Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Advanced Electron Microscopy Techniques and Applications
Authors: Shoshana C. Williams | Gabriel Greenstein | Xinyu Liu | Alessio Fragasso | Noah Eckman | Alexander N. Prossnitz | Changxin Dong | Anna Makar-Limanov | Christine Jacobs‐Wagner | Lynette Cegelski | Hector Lopez Hernandez | Eric A. Appel
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-11-07)
Field: Chemistry — Organic Chemistry

Cross-Molecular Active Learning for the Discovery of Antimicrobial Polyacrylamides Antimicrobial resistance poses an urgent and increasing threat to global health. The development of new antimicrobials is crucial. Synthetic copolymers are attractive as a potential solution, because they can be produced at scale and designed to mimic antimicrobial peptides and act as broad-spectrum antimicrobials capable of evading resistance mechanisms. This work leverages a cross-molecular machine learning pipeline, trained on antimicrobial peptides, to develop potent antimicrobial polymers to combat <i>Escherichia coli</i> , which were then synthesized and validated experimentally. One candidate copolymer was further characterized and shown to permeabilize the bacterial membrane, which is associated with decreased resistance. Furthermore, this copolymer demonstrated remarkable synergy in eradicating biofilm-associated <i>E. coli</i> when combined with a first-line clinical drug regimen, reducing the amount needed to eradicate bacteria in biofilms by three orders of magnitude. These results demonstrate promise for potentiating antibacterial activity of currently available antibiotics, treating serious and complicated infections, and combatting antimicrobial resistance. Antimicrobial ; Drug ; Bacteria ; Antibiotic resistance ; Antimicrobial peptides ; Anti-Infective Agents ; Antimicrobial drug ; Copolymer Antimicrobial agents and applications ; Antimicrobial Peptides and Activities ; Orthopedic Infections and Treatments
Authors: Subrata Biswas | Pathik Kumbhakar
Source: Multidisciplinary Research Journal (article, 2025-04-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Technique of Synthesis of Anisotropic Shaped Plasmonic Nanoparticles Anisotropic nanoparticles have attracted considerable attention for their distinctive shape-dependent optical, electronic, and catalytic properties, making them valuable across diverse applications, including medicine and nanotechnology. This abstract presents an overview of synthesis techniques used to produce anisotropic nanoparticles with controlled shapes, sizes, and compositions. Various methods, including chemical reduction, seed-mediated growth, and template-assisted approaches, are discussed in terms of their efficiency, reproducibility, and scalability. Emphasis is placed on understanding the role of surfactants, reducing agents, and reaction conditions in driving anisotropic growth. Additionally, recent advancements in green synthesis methods highlight the shift towards environmentally friendly procedures. The review provides insights into how precise control over nanoparticle anisotropy enhances their functional properties and enables their targeted applications in photonics, biomedicine, and catalysis. The findings underscore the potential of these techniques to advance the design and fabrication of next-generation anisotropic nanomaterials. Plasmon ; Nanoparticle ; Anisotropy ; Materials science ; Plasmonic nanoparticles ; Nanotechnology ; Optics ; Optoelectronics ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Nanoparticles: synthesis and applications ; Laser-Ablation Synthesis of Nanoparticles
Authors: Yinan Wang | Xiaoyang Wang | Zhenyu Wang | Jing Wu | Jian Lv | E Weinan | Han Wang
Source: Research Square (preprint, 2025-10-09)
Field: Materials Science — Materials Chemistry

OpenCSP: A Deep Learning Framework for Crystal Structure Prediction from Ambient to High Pressure Suite ; Benchmark (surveying) ; Scalability ; Stability (learning theory) ; Ranking (information retrieval) ; Deep learning ; Crystal structure prediction ; Sampling (signal processing) Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Crystallization and Solubility Studies
Authors: Arti Hadap | V. R. Panse | Serhii Tereshchuk
Source: Research Square (preprint, 2025-02-21)
Field: Materials Science — Materials Chemistry

Investigation of Aloe Vera Mediated ZnO-β-CD Nanoparticles for Photocatalysis &amp;amp; Antimicrobial Applications Aloe vera ; Photocatalysis ; Antimicrobial ; Nanoparticle ; Chemistry ; Nuclear chemistry ; Nanotechnology ; Materials science ; Microbiology ; Biochemistry ; Biology ; Catalysis ; Organic chemistry Nanoparticles: synthesis and applications ; TiO2 Photocatalysis and Solar Cells ; Chemistry and Chemical Engineering
Authors: Nichika Ozawa | Nahoko Kuroki | Hirotoshi Mori
Source: Advanced Science (article, 2025-12-22)
Field: Materials Science — Materials Chemistry

Ligand‐Induced Electronic Response Enables Predictive QM/MM Simulations Predictive modeling of large molecular systems demands methods that combine quantum accuracy with scalability. Although hybrid quantum mechanics/molecular mechanics (QM/MM) simulations offer such a framework, their predictive power has been limited by the subjective and system-specific definition of the QM region. Here, we present an electronically informed protocol that objectively defines QM regions from ligand-induced orbital shifts and charge-redistribution, extracted in a single semiempirical fragment molecular orbital (FMO) calculation. Validated on both zeolite-guest and enzyme-inhibitor complexes, the method achieves chemical accuracy (within ∼1-2 kcal/mol on binding energies) while substantially reducing computational cost at the DFTB level. This cross-domain strategy reframes QM/MM as a transferable design principle, bridging solid-state catalysis and quantum biochemistry, and thereby providing a practical platform for predictive molecular engineering across diverse disciplines. Fragment molecular orbital ; Bridging (networking) ; Quantum ; Quantum chemical ; Molecular dynamics ; Predictive power ; Power (physics) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Metal-Catalyzed Oxygenation Mechanisms
Authors: Ziyi Zhang | Derui Wang | Maciej P. Polak | Corey Carlos | Yutao Dong | Dane Morgan | Xudong Wang
Source: Small Methods (article, 2025-11-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tartrate‐Assisted Ionic Layer Epitaxy for General Synthesis of 2D Nanostructures The synthesis of ultrathin 2D nanomaterials with regular shapes and uniform thickness remains a challenge despite their intriguing properties. In this paper, a facile and generic strategy for the growth of versatile ultrathin nanosheets using tartrate-assisted ionic layer epitaxy (ILE) at the air-water interface is presented. Metal ions, stabilized by tartrate coordination, nucleate within the electrical double layer beneath a self-assembled monolayer. This method facilitates the growth of micro-sized hexagonal to wafer-scale continuous nanosheets from 26 metal elements, including single and multi-element compositions, with high precursor utilization via solution recycling. Furthermore, recognizing the need for efficient quality assessment, the successful application of a multimodal Large Language Model (LLM) for rapid and consistent evaluation of nanosheet quality from microscopy images, achieving performance comparable to human experts is demonstrated. This combined approach demonstrates a sustainable and high-throughput path for both 2D nanomaterial synthesis and automated quality assessment, accelerating materials discovery. Nanomaterials ; Nanosheet ; Epitaxy ; Layer (electronics) ; Nanostructure ; Nucleation ; Ionic bonding Gold and Silver Nanoparticles Synthesis and Applications ; Nanopore and Nanochannel Transport Studies ; Anodic Oxide Films and Nanostructures
Authors: Lakshminarayana Satham | Anand Podilapu | Renuka Khatik
Source: Journal of Molecular Chemistry. (article, 2025-06-20)
Field: Chemistry — Organic Chemistry

Synergistic catalysis: Unlocking site-selective functionalization of carbohydrate hydroxyl groups for advanced glycoscience Selective functionalization of carbohydrate hydroxyl groups is challenging due to their abundance and similar reactivity. Synergistic catalysis—using multiple catalysts to activate different substrates—offers a promising solution, outperforming traditional single-catalyst approaches. This review presents recent advances in synergistic systems employing transition metals, chiral ligands, and organoboron compounds to achieve regio-, stereo-, and enantioselective transformations. These methods enable the construction of glycosidic linkages and carbohydrate mimics with potential biological activity. The role of non-covalent interactions, dynamic kinetic resolution, and computational tools in guiding selectivity is also discussed. Emphasis is placed on reaction efficiency, sustainability, and scalability, alongside persistent challenges such as hydroxyl differentiation, catalyst compatibility, and system optimization. Future directions include developing novel catalytic platforms, integrating computational design, and adopting greener methodologies to expand access to carbohydrate-based molecules with valuable functional properties. Glycosidic bond ; Catalysis ; Enantioselective synthesis ; Surface modification ; Carbohydrate chemistry ; Carbohydrate Carbohydrate Chemistry and Synthesis ; Glycosylation and Glycoproteins Research ; Cyclopropane Reaction Mechanisms
Authors: S.Z. Ismayilova | M.H. Osmanli | R.H. Ismayilov | D.B. Тagiyev | Mansura Huseynova | Konul Gahramanova | Ajdar Medjidov | Bahattin Yalçın | Fuad Famil Valiyev | M.A. Bayramov | Lala Guliyeva | Onur Şahi̇n | Shie‐Ming Peng
Source: Azerbaijan Chemical Journal (article, 2025-10-27)
Field: Chemistry — Organic Chemistry

COPPER(II) COMPLEX WITH PYRAZINE- AND TRIAZINE-MODULATED TRIPYRIDYLDIAMINE LIGAND: SYNTHESIS, CRYSTAL STRUCTURE, MAGNETIC, AND ANTIMICROBIAL PROPERTIES Using the pyrazine- and triazine-modulated tripyridyldiamine ligand 6-phenyl-N2,N4-di(pyrazin-2-il)-1,3,5-triazine-2,4-diamine (H2dpztzda), a new mononuclear copper(II) complex [Cu(H2dpztzda)(NO3)2]∙2C3H7NO 1 has been synthesized, structurally characterized, and its antimicrobial properties studied. According to the single crystal X-ray analysis of complex 1, Cu(II) exhibits five coordination with a distorted trigonal bipyramidal geometry. The "inverted type" of EPR spectra (g┴ &gt; g||~ ge), alongside results from magnetic moment susceptibility and electronic spectrum studies, collectively support this observation. The calculated Addison value for 1 is τ5 = 0.54, indicating also that the Cu(II) center possesses distorted trigonal bipyramidal geometry. The H2dpztzda molecule coordinates with the Cu(II) as a tridentate ligand. Complex 1 exhibits two types of hydrogen bonding: classical and non-classical. It has been shown that the interactions involving C-H‧‧‧π, π-π, and hydrogen bonding significantly influence the crystal packing of synthesised complex 1 and play a crucial role in the formation of supramolecular motifs. The antimicrobial activity of the compounds was evaluated using the traditional well diffusion method. Both compounds (complex 1 and H2dpztzda ligand) analyzed for antimicrobial activity showed highly effective results against the bacteria Pseudomonas aeruginosa, Mycobacterium phlei, and the fungi Aspergillus niger and Penicillium chrysogenum in lubricants and coolants Supramolecular chemistry ; Electron paramagnetic resonance ; Hydrogen bond ; Antimicrobial ; Trigonal bipyramidal molecular geometry ; Molecule ; Crystal (programming language) ; Ligand (biochemistry) ; Crystal structure Synthesis and Characterization of Heterocyclic Compounds ; Metal complexes synthesis and properties ; Enzyme function and inhibition
Authors: Arman Ter-Petrosyan | Michael Holden | Jenna A. Bilbrey | Sarah Akers | Christina Doty | Kayla Yano | Le Wang | Rajendra Paudel | Eric Lang | Khalid Hattar | R. Comès | Yingge Du | Bethany E. Matthews | Steven R. Spurgeon
Source: npj Computational Materials (article, 2025-11-21)
Field: Materials Science — Materials Chemistry

Revealing the evolution of order in materials microstructures using multi-modal computer vision The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microstructural order. Our present understanding is typically derived from laborious manual analysis of imaging and spectroscopy data, which is difficult to scale, challenging to reproduce, and lacks the ability to reveal latent associations needed for mechanistic models. Here, we demonstrate a multi-modal machine learning (ML) approach to describe order from electron microscopy analysis of the complex oxide La1−xSrxFeO3. We construct a hybrid pipeline based on fully and semi-supervised classification, allowing us to evaluate both the characteristics of each data modality and the value each modality adds to the ensemble. We observe distinct differences in the performance of uni- and multi-modal models, from which we draw general lessons in describing crystal order using computer vision. Pipeline (software) ; Construct (python library) ; Energy (signal processing) ; Modality (human–computer interaction) ; Order (exchange) ; Value (mathematics) Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Advanced Electron Microscopy Techniques and Applications
Authors: Tri Nguyen | Thanh N. Truong
Source: npj Computational Materials (article, 2025-12-12)
Field: Materials Science — Materials Chemistry

Inverse Design Using Goal-Conditioned Reinforcement Learning for Organic Semiconductor Materials from Benzene and Thiophene-based Polycyclic Aromatic Compounds We present a machine learning approach for the inverse design of organic semiconductor materials from benzene and thiophene-based polycyclic aromatic compounds (PACs). Inverse design is an efficient approach to materials discovery that aims to design materials with preset properties. However, it is complex due to the non-uniqueness and nonlinearity of property-to-structure relationships. We demonstrate the potential of this approach through the inverse design of PACs to achieve target HOMO-LUMO gaps, a key property for organic semiconductors, ranging from 1.36 eV to 4.37 eV with an error of 0.15 eV within Density Functional Theory uncertainty. The model uses goal-conditioned reinforcement learning with chemical domain knowledge, allowing addressing design goals directly. To incorporate practical aspects such as chemical accessibility, the model can include soft constraints, such as minimizing ring count to favor smaller structures. Thus, our framework addresses key inverse design challenges while allowing prioritization of more optimal or diverse candidates. Inverse ; Benzene ; Inverse problem ; Material Design ; Nonlinear system ; Key (lock) ; Property (philosophy) Machine Learning in Materials Science ; Organic Electronics and Photovoltaics ; Synthesis and Properties of Aromatic Compounds
Authors: J.W. Yang | Y.S. Yang | H. Wu | Seemab Hussnain | X.J. Wang | H.B. Zeng | W.J. Li
Source: Functional Thin Films and Energy Materials (article, 2025-12-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

State-of-the-Art of Polymer-Based Conductive Adhesives for Electromagnetic Protection Manufacturing Polymer-based conductive adhesives (PbCAs) have emerged as key materials for electromagnetic wave interference (EMI) protection. They are increasingly replacing traditional metals due to their environmental friendliness, low-temperature processing, and flexibility. This review systematically elaborates on the conductive mechanisms of PbCAs, which are dominated by percolation theory and quantum tunneling effects. Furthermore, recent advances in the encapsulation of PbCAs within polymer matrices (e.g., epoxy, polyurethane) and/or with conductive fillers (e.g., metals, carbon-based materials, MXenes) have been highlighted. These innovations facilitate their expanded applications in EMI protection, including both EMI shielding and electromagnetic wave absorption. Despite significant advancements, challenges persist in balancing high conductivity with favorable mechanical properties and long-term stability under harsh service conditions. Future development is expected to focus on fillers with a low percolation threshold, optimized structural designs, and multifunctional applications in flexible and wearable electronics. These advancements aim to meet the requirements of miniaturized, high-performance electronic devices. Electrical conductor ; EMI ; Electromagnetic interference ; Electromagnetic shielding ; Conductive polymer ; Adhesive ; Electrically conductive ; Quantum tunnelling Electromagnetic wave absorption materials ; Smart Materials for Construction ; Advanced Sensor and Energy Harvesting Materials
Authors: Asmaa R. Alsayeh | E.M. Abdelrazek | A. H. Oraby | Ahmed A. Shokeir | Raghda Abo Gabal
Source: Scientific Reports (article, 2025-11-27)
Field: Materials Science — Materials Chemistry

Red single wavelength emitting up-conversion nanoparticles modulate cellular dynamics and gene expression in T24 bladder cancer cells Bladder cancer persists in posing a significant global health challenge, highlighting the need for the development of advanced therapeutic strategies. This study investigates the effects of red single-wavelength upconversion nanoparticles (UCNPs), co-doped with Sm<sup>3</sup>⁺ and Nd<sup>3</sup>⁺ in a NaYbF<sub>4</sub> matrix, on T24 bladder cancer cells. The UCNPs were synthesized using a thermal decomposition method and characterized for their optical, structural, and morphological properties. The nanoparticles exhibited strong red emission under 980 nm near-infrared (NIR) excitation. Cytotoxicity assays revealed concentration-dependent cell death, with enhanced effects under radiation. Wound healing assays demonstrated that UCNPs reduced cellular repair mechanisms, with radiation further enhancing this effect. Gene expression analysis revealed significant modulation of key genes involved in cancer progression, including upregulation of IL-6, and downregulation of anti-apoptotic genes such as BCL2, HIF, and Survivin. Additionally, UCNPs raised the levels of reactive oxygen species (ROS), indicating oxidative stress. These findings highlight the therapeutic potential of UCNPs in bladder cancer treatment. Downregulation and upregulation ; Bladder cancer ; Cancer cell ; Cytotoxicity ; Gene expression ; Reactive oxygen species ; Cancer ; Gene Luminescence Properties of Advanced Materials ; Nanoplatforms for cancer theranostics ; Photodynamic Therapy Research Studies