jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Magdalena Laskowska
Source: International Journal of Molecular Sciences (article, 2026-03-20)
Field: Materials Science — Materials Chemistry

Special Issue “Functional Nanomaterials: Structures, Compositions and Various Applications” Research into functional nanomaterials lies at the heart of many technological breakthroughs because it connects fundamental structure-property relationships with real-world performance in devices and processes [...]. Composition (language) Chemical and Physical Properties of Materials ; Magnesium Oxide Properties and Applications ; Carbon and Quantum Dots Applications
Authors: Hidemasa Bessho | Takeshi Kawasaki | Hayato Shiba
Source: arXiv (Cornell University) (article, 2026-03-14)
Field: Materials Science — Materials Chemistry

Inferring the dynamics of glass-forming liquids from static structure across thermal states In this study, we demonstrate the generalizability of graph neural networks in predicting the dynamic heterogeneity of model glass-forming liquids across different temperatures. While previous approaches have often been limited to making predictions at the specific temperatures used during training, we find that our proposed framework - T-BOTAN - enables interpolation to temperatures not included in the training set. We show that the dynamical behavior, the associated four-point correlations, and even the macroscopic temperature can be estimated with sufficient accuracy solely from static particle configurations at untrained temperatures. These results suggest that static configurations encode not only local structural features driving dynamic heterogeneity but also fundamental thermodynamic information. Interpolation (computer graphics) ; Thermal ; Dynamics (music) ; Dynamical heterogeneity ; Graph ; Particle (ecology) ; Generalizability theory ; ENCODE Material Dynamics and Properties ; Machine Learning in Materials Science ; Advanced Physical and Chemical Molecular Interactions
Authors: Sam Daniel Fenny A | Prasanth Samykkannu | Yokesvaran Kalidasan | Ajithkumar S | S. Balaguru
Source: EPJ Web of Conferences (article, 2026-01-01)
Field: Materials Science — Polymers and Plastics

A Lightweight Advanced Composite System: Polypropylene Fabric Reinforced Expandable Polystyrene Polymer matrix composite (PMCs) have the primary strengths of high specific strength, low density, and corrosion and abrasion resistance. Their performance is largely determined by the effectiveness of the transfer of loads between fiber reinforcement and polymer matrix. To produce a lightweight composite material, a polypropylene (PP) fabric was reinforced into an expandable polystyrene (EPS) matrix with gaseous softening and processing ingredient of gasoline. A composite was developed using the reinforcement in order to determine the effect of polypropylene reinforcement on the mechanical and physical behavior of an EPS-based matrix. The mechanical characterization tests such as tensile , flammability and hardness tests were performed in this research. It is found that besides increasing the surface hardness, the presence of polypropylene textiles also enhances the structural integrity, tensile responsiveness, as well as flame- resistance characteristics in the EPS matrix. The suggested work recognizes the potential of the PP-fabric-reinforced EPS composites as an example of a low-density material that can be used in the lightweight structural and insulating areas. Polypropylene ; Ultimate tensile strength ; Composite number ; Reinforcement ; Polystyrene ; Softening ; Tensile testing ; Abrasion (mechanical) Flame retardant materials and properties ; Natural Fiber Reinforced Composites ; Mechanical Behavior of Composites
Authors: Domenic Kratzer | Martina Plank | Meike Koenig | Tahereh Mohammadi Hafshejani | Joerg Lahann
Source: Repository KITopen (Karlsruhe Institute of Technology) (article, 2026-01-01)
Field: Materials Science — Surfaces, Coatings and Films

A Tandem Chemical Vapor Deposition Platform for the Solvent‐Free Synthesis of Polypeptide Architectures The precise engineering of surfaces decorated with polypeptides is critical for advanced diagnostics, biomedical coatings, and cellular interfaces. However, conventional methods are plagued by the need for solvents, multistep procedures, substrate limitations, and the abundance of side reactions. Here, we report that two-step chemical vapor polymerization can result in the fast, efficient, and substrate-independent synthesis of polypeptide films without the use of solvents or excipients. The first step involves deposition of an initiator layer, i.e., poly(4-amino-p-xylylene), via chemical vapor deposition (CVD) polymerization of 4,16-diamino[2.2]paracyclophane. The second step involves evaporation and ring-opening polymerization of N-carboxy anhydrides. This fully integrated CVD approach ensures substrate-independent, conformal growth of poly(propargyl-(S)-glycine) and poly(O-propargyl-(S)-tyrosine) films of up to 198 nm thickness. The use of CVD processes eliminates the concern of side reactions, such as transfer and termination reactions, and is a prerequisite for the successful peptide micropatterning, demonstrated in this study. Successful peptide growth and post-polymerization modifications via click chemistry were confirmed by time-of-flight secondary mass spectrometry, x-ray photoelectron spectroscopy, and infrared spectroscopy. The application of entirely solvent-free workflows to develop biomacromolecular coatings, such as the polypeptide films demonstrated in this study, addresses a critical gap in the pursuit of advanced and scalable biologization methods. Chemical vapor deposition ; Polymerization ; Evaporation ; Substrate (aquarium) ; Polymer ; Deposition (geology) ; Tandem ; Click chemistry Polymer Surface Interaction Studies ; Nanofabrication and Lithography Techniques ; Diatoms and Algae Research
Authors: Ioannis Pispas | Aristeidis Papagiannopoulos
Source: Macromol—A Journal of Macromolecular Research (article, 2026-03-18)
Field: Materials Science — Surfaces, Coatings and Films

Next-Generation Polysaccharide-Based Nanocarriers for Precision Medicine: Structure–Property Principles, Responsiveness, and Therapeutic Translation Among the most structurally diverse biomacromolecules, polysaccharides have attracted increased attention as nanocarriers for precision medicine due to their inherent biocompatibility and versatility in functionalization. Molecular features, such as monomer composition, glycosidic linkages, charge density, and chemical modification, essentially determine the nanoscale assembly process of these biopolymers, as well as their biological compatibility. This review highlights the role of these properties in the assembly process of polysaccharide-based nanocarriers leading to a variety of self-assembled nanostructures, such as polyelectrolyte complexes, protein–polysaccharide complexes, amphiphilic micelles, vesicles, hybrid systems, and nanogels, which are extensively discussed throughout the review. This review also focuses on the structure–property–function relationships of nanocarriers as applied to the rapidly developing area of precision medicine, emphasizing the problems of sustainability and reproducibility. By combining the principles of molecular engineering, supramolecular assembly, and measurable properties, this work aims to present a unified view of the molecular engineering of polysaccharide-based nanocarriers for enhanced translation potential, as well as to outline a coherent framework for the rational development of next-generation polysaccharide-based nanocarriers with improved clinical relevance. Nanocarriers ; Rational design ; Biocompatibility ; Translation (biology) ; Process (computing) ; Amphiphile Polymer Surface Interaction Studies ; Supramolecular Self-Assembly in Materials ; Hemoglobin structure and function
Authors: Miaolan Zhen | Mingyang Li | Jialei Xu | Rui Shi | Hujun Qian | Youliang Zhu | Zhongyuan Lu
Source: Chinese Journal of Chemical Physics (article, 2026-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

A Multi-Scale Molecular Dynamics Scheme/Toolkit for Polymer Modeling Multi-scale modeling of polymer systems remains a fundamental challenge in materials science due to the strongly coupled structures and dynamics across atomic, mesoscopic, and macroscopic scales. Here, we present PyGAMD-ChemFAST (Python GPU-accelerated molecular dynamics-chemical-friendly automated simulation toolkit), an integrated modeling and simulation framework that combines a molecular simulation platform with an automated modeling and processing toolkit. The framework supports bidirectional cross-scale modeling, integrating the mapping from all-atom (AA) to coarse-grained (CG) models in coarse-graining and from CG back to AA in fine-graining, while automating the entire workflow from model parameterization through dynamics simulation to property analysis. It accommodates complex polymer topologies and ensures cross-scale force field compatibility. By unifying modeling and simulation in a programmable environment, PyGAMD-ChemFAST enhances computational efficiency and ensures parameter consistency, especially in studying phase separation, glass transition, crystallization, and mechanical behavior. This integrated framework provides an efficient and reliable platform for high-throughput, multi-scale polymer research. Molecular dynamics ; Polymer ; Dynamics (music) ; Molecular model ; Work (physics) Advanced Physical and Chemical Molecular Interactions ; Block Copolymer Self-Assembly ; Rheology and Fluid Dynamics Studies
Authors: M Zahirul Alam | Robert Fickler | Yiyu Zhou | Enno Giese | Jeremy Upham | R. N. Boyd
Source: Nanophotonics (article, 2026-01-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

An Epsilon‐Near‐Zero‐Based Nonlinear Platform for Ultrafast Re‐Writable Holography We re-examine real-time holography for all-optical structuring of light and optical computation using a contemporary material: a subwavelength-thick, spatially unstructured film of indium tin oxide (ITO). When excited by spatially structured light at epsilon-near-zero frequencies, the film acts as an efficient and reconfigurable diffractive optical platform for all-optical modulation of light such as spatial structuring and optical computations. We demonstrate a few percent of absolute diffraction efficiency over greater than 300-nm-bandwidth around telecom wavelengths using a film four orders of magnitude thinner than and up to six orders of magnitude faster than standard holographic materials. Our findings highlight the potential of using epsilon-near-zero-based nanostructures for efficient modulation of spatially structured light and rapid prototyping without complex nanofabrication processes. Ultrashort pulse ; Holography ; Nonlinear system ; Nonlinear optics ; Laser ; Computer-generated holography Metamaterials and Metasurfaces Applications ; Photorefractive and Nonlinear Optics ; Advanced Optical Imaging Technologies
Authors: Yunlong Jia | Long Guo | Wei Li | Shuai Zhang | Xiaojie Shi | Shengming Yin
Source: Journal of Nuclear Engineering (article, 2026-01-28)
Field: Materials Science — Materials Chemistry

Recent Development of Oxide Dispersion-Strengthened Copper Alloys for Application in Nuclear Fusion The performance of conventional precipitation-strengthened copper alloys drastically degrades at temperatures exceeding 500 °C, hindering their application under extreme conditions like those in nuclear fusion reactors. Oxide dispersion–strengthened copper (ODS–Cu) alloy surmounts these constraints by incorporating thermally stable, nanoscale oxide dispersoids that simultaneously confer strengthening, microstructural stabilization, and enhanced irradiation tolerance, while preserving high thermal conductivity. This review comprehensively examines the state of the art in ODS–Cu alloy from a “processing–microstructure–property” perspective. We critically assess established and emerging fabrication routes, including internal oxidation, mechanical alloying, wet chemical synthesis, reactive spray deposition, and additive manufacturing, to evaluate their efficacy in achieving uniform dispersions of coherent/semi-coherent nano-oxides at engineering-relevant scales. The underlying strengthening mechanisms and performance trade-offs are quantitatively analyzed. The review also outlines strategies for joining and manufacturing complex components, highlights key gaps in metrology and reproducibility, and proposes a roadmap for research and standardization to accelerate industrial deployment in plasma-facing components. Oxide ; Copper ; Alloy ; Fabrication ; Fusion ; Metrology ; Nanoscopic scale ; Copper oxide Fusion materials and technologies ; Copper Interconnects and Reliability ; Microstructure and mechanical properties
Authors: F. E. Abeng | Nse N. Oji | Kayode A. Osuwa | Daniel Ofem | Ayei I. Ettah | Ese L. Ekanem | Oru Ogar Njor | Nkinkwa I. Ntonia | Emmanuel Edet | Ubong U. Udoka | Madaki A. Amidu | David A. Ephraim
Source: Discover Chemistry. (article, 2026-02-19)
Field: Materials Science — Materials Chemistry

Thermodynamic study and adsorption characteristics of mild steel corrosion inhibition in 0.1 M $$H_{2}SO_{4}$$ solution by orange peels (Citrus sinensis) The development of efficient and eco-friendly corrosion inhibitor is necessary because mild steel corrosion in acidic conditions present serious industrial issues. The potential of orange peel (Citrus sinensis) extract as a green corrosion inhibitor for mild steel in 0.1 M H2SO4 solution is investigated in this study. The hydrogen evolution method was used to assess the inhibition efficiency, corrosion rate, as well as adsorption and thermodynamic models. Thermodynamic parameters such as activation energy, enthalpy change, and entropy change were computed. Langmuir, Freundlich and Temkin adsorption isotherms were used to examine the extract’s adsorption behavior on the mild steel surface. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) were also used for surface characterization. Effective corrosion inhibition is confirmed by the results, which shows an increase in inhibition efficiency (IE) and decrease in corrosion rate with increasing inhibitor concentration. With increase in temperature, the inhibition efficiency drops and corrosion rate increases. At 303 K and 4.0 g/L concentration of the orange peels extract recoreded maximum IE% of (92.9%), (65.1%), and (69.0%) for hydrogen evolution, electrochemical impedance spectroscopy, and potentiodynamic polarization techniques, respectively. The result also revealed the inhibited system’s activation energy to be higher than the unrestrained systems. An endothermic reaction is suggested by the positive enthalpy change with values less than 100 kJ/mol. The Langmuir isotherm offered the best fit, implying monolayer adsorption on a homogeneous surface, with negligible lateral interaction, thereby strengthening the proposed adsorption mechanistic pathway. The adsorption process is spontaneous and primarily physical when the negative Gibbs free energy of adsorption is smaller than − 20 kJ/mol. When the inhibitor was present, protective barrier layers formed on the mild steel surface, according to SEM and AFM investigations. Citrus sinensis extract effectively inhibits mild steel corrosion in 0.1 M H2SO4 solution by physical adsorption and surface barrier development, indicating its potential as a sustainable and ecofriendly corrosion inhibitor. All the methods used in this study agreed. Adsorption ; Corrosion ; Gibbs free energy ; Enthalpy ; Endothermic process ; Freundlich equation ; Langmuir adsorption model ; Langmuir ; Corrosion inhibitor Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Electrodeposition and Electroless Coatings
Authors: Weitao Li | Yi Yang | Yutong You | Cuijuan Xing | Aiqing Xia | Jin Guo | Pengbo Gao | Lili Dong
Source: Journal of Separation Science (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Hydroxyl‐Mediated Adsorption Site Distribution on Titanium Dioxide@Covalent Organic Framework and Enhanced Selective Separation and Detection of Lead Ions This work designs a titanium dioxide@covalent organic framework composite material (TiO<sub>2</sub>-COF), which optimizes the distribution of lead adsorption sites by adjusting the position of hydroxyl groups in the COF, thereby enhancing the separation efficiency of trace Pb<sup>2+</sup> ions. The composite material integrates the advantages of metal oxides and porous materials, optimizing the separation performance of Pb<sup>2+</sup> ions through a synergistic enhancement effect. Additionally, its multi-interface structural characteristics provide the material with multidimensional selectivity, resulting in a highly selective separation material. In selectivity experiments, the material demonstrated high adsorption selectivity for Pb<sup>2+</sup> ions compared to several other metal ions. Thermodynamic and kinetic simulation results prove that the adsorption of Pb<sup>2+</sup> ions by TiO<sub>2</sub>-COF conforms to the pseudo-second-order kinetics and the Langmuir adsorption model. After multiple cycles of use, the material still maintains high adsorption efficiency, demonstrating its potential clean and green application value in the highly selective separation of metal pollutants. The constructed material was used for the separation and preconcentration of Pb<sup>2+</sup> ions, establishing a detection system for trace Pb<sup>2+</sup> ions. The detection limit of the method is 0.073 µg L<sup>-1</sup> (3σ/K, n = 9), with precision ranging from 0.55% to 11.7% (n = 11), and a linear range of 0.2-5 µg L<sup>-1</sup>, exhibiting strong anti-interference capability. The constructed method achieves the determination of lead ions in real samples, with recoveries ranging from 95% to 103%. Moreover, the standard material GBW08607 was analyzed through the constructed system, and the t-test shows that the calculated t-value is 2.01, which is less than the tabulated t-value of 2.57 (n = 6), proving the reliability of the method. It provides a potential alternative material for the separation and analysis of other environmental pollutants. Adsorption ; Selectivity ; Detection limit ; Titanium ; Metal ions in aqueous solution ; Selective adsorption ; Metal-organic framework ; Ion Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal ; Extraction and Separation Processes
Authors: Daniel Willimetz | Joaquín Martínez-Ortigosa | Deborah Anima Brako-Amoafo | Lukáš Grajciar | J. Alejandro Vidal-Moya | Carlos Bornes | Vincent Sarou-Kanian | Fernando Rey | Teresa Blasco | Christopher J. Heard
Source: Journal of Materials Chemistry A (article, 2026-01-01)
Field: Chemistry — Inorganic Chemistry

Aluminium siting in zeolite RTH from a combined machine learning – NMR approach Combining NMR with machine learning opens new opportunities to address the still‑challenging elucidation of aluminum siting in zeolite frameworks. Aluminium ; Zeolite Zeolite Catalysis and Synthesis ; Advanced NMR Techniques and Applications ; NMR spectroscopy and applications
Authors: Ambre Brachfeld | Giorgio Mattana | Agathe Laës | Vincent Noël | Lylian Challier
Source: Electrochimica Acta (article, 2026-03-12)
Field: Chemistry — Electrochemistry

Turning metals cations into catalytic nanoparticles on modified electrode: a general strategy for their electrochemical quantification • Cu and Fe pre-accumulated on modified graphite electrodes form a nanoelectrode array by electrochemical reduction. • Cu and Fe nanoelectrode array dimensions tune the catalytic HER peak potential in cyclic voltammetry. • Peak shifts in electrocatalytic HER voltammetric curves enable accurate nanomolar Cu and Fe quantification with higher sensitivity than pulsed voltammetry. • Conceptual advance from conventional current-based to potential-based sensing, enabled by nanometric-scale diffusion regime shifts in cyclic voltammetry. • New detection concept easily added in the workflow of electrochemical metal sensor development. An innovative electrochemical sensing method has been presented in the present study. Instead of designing a specific high-affinity or highly selective surface, a generalizable approach is proposed, that complements conventional electrochemical stripping methods and can be readily integrated into existing sensor development workflows without additional cost or complex fabrication steps. Diazonium-modified graphite electrode were used as a robust platform to demonstrate that sparsely pre-accumulated copper and iron cations can be reduced into nanodeposits, which behave as a nanoelectrode array. For the first time, it is shown that the macroscopic electrochemical response of this array towards the hydrogen evolution reaction depends on the size of the nanoelectrodes: higher metal concentrations in the incubation solution lead to more extensive metal deposition and larger nanostructures, which shift the hydrogen evolution reaction catalytic peak potential positively in cyclic voltammetry. This shift continues until the metal becomes detectable by standard pulsed analytical methods. Importantly, the proposed approach achieves enhanced sensitivity up to ten times greater compared to standard pulsed reference methods. Moreover, this gain in sensitivity does not rely on a specific surface chemistry. Therefore, the more affine a given accumulation layer is for its target metal, the lower the detection limits that can be achieved with this method. This study points towards a promising route for next-generation electrochemical sensors for trace metal detection, offering sensitivity beyond that of traditional faradaic detection schemes while remaining simple, scalable, and broadly adaptable. Electrochemistry ; Electrode ; Catalysis ; Cyclic voltammetry ; Graphite ; Metal ; Transition metal ; Electrochemical gas sensor ; Hydrogen Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors ; Electrocatalysts for Energy Conversion
Authors: Timo Reents | Arianna Cantarella | M. Bercx | Pietro Bonfà | Giovanni Pizzi
Source: ArXiv.org (article, 2026-01-05)
Field: Materials Science — Materials Chemistry

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions Generative AI models, such as score-based diffusion models, have recently advanced the field of computational materials science by enabling the generation of new materials with desired properties. In addition, these models could also be leveraged to reconstruct crystal structures for which partial information is available. One relevant example is the reliable determination of atomic positions occupied by hydrogen atoms in hydrogen-containing crystalline materials. While crucial to the analysis and prediction of many materials properties, the identification of hydrogen positions can however be difficult and expensive, as it is challenging in X-ray scattering experiments and often requires dedicated neutron scattering measurements. As a consequence, inorganic crystallographic databases frequently report lattice structures where hydrogen atoms have been either omitted or inserted with heuristics or by chemical intuition. Here, we combine diffusion models from the field of materials science with techniques originally developed in computer vision for image inpainting. We present how this knowledge transfer across domains enables a much faster and more accurate completion of host structures, compared to unconditioned diffusion models or previous approaches solely based on DFT. Overall, our approach exceeds a success rate of 97% in terms of finding a structural match or predicting a more stable configuration than the initial reference, when starting both from structures that were already relaxed with DFT, or directly from the experimentally determined host structures. Heuristics ; Diffusion ; Neutron scattering ; Scattering ; Field (mathematics) ; Hydrogen Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Block Copolymer Self-Assembly