jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jie Miao | W. H. Long | Jiayi Yan | Chengjia Xiong
Source: Journal of Materials Chemistry C (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Adjustment and detection of the topology freezing transition temperature of vitrimers based on vitrimers doped with nanoparticles and photonic crystals A physical method is proposed to adjust and detect T v of vitrimers based on vitrimers doped with SiO 2 nanoparticles and photonic crystals from SiO 2 nanoparticles. T v is decreased as the doping amount of SiO 2 nanoparticles is increased. Materials science ; Topology (electrical circuits) ; Nanoparticle ; Photonics ; Photonic crystal ; Nanotechnology ; Chemical engineering ; Optoelectronics ; Engineering ; Electrical engineering Photochromic and Fluorescence Chemistry ; Porphyrin and Phthalocyanine Chemistry ; Photochemistry and Electron Transfer Studies
Authors: S. Shyam Sunder | Maria Jauregui Rozo | Hari A. Deshpande | A. Neyer | Vinay Papaiya | Dietmar Meinel | Bernhard Schartel | Holger Ruckdäschel
Source: Journal of Polymer Science (article, 2025-08-03)
Field: Materials Science — Polymers and Plastics

Char to the Rescue: Processing and Transfer of Flame‐Retardant Epoxy Resins, Adjusting the Fire Behavior and Post‐Fire Structural Integrity of Glass Fiber Composites ABSTRACT Epoxy (EP) glass fiber reinforced composites (GFRCs) are extensively used in structural applications due to their excellent thermal and mechanical properties, but their inherent flammability limits fire‐safe deployment. While numerous studies examine the flame retardancy of resins or individual composite systems, comprehensive studies evaluating simultaneous improvements in flame retardancy and post‐fire mechanical integrity, specifically through prepreg processing, remain challenging. This study investigates the effectiveness and transferability of phosphorus‐based flame retardant (FR) systems to diglycidyl ether of bisphenol A (DGEBA) and EP novolac resin matrices and their corresponding bidirectional glass fiber composites via prepregs. The FRs are chosen based on varying modes of action: ammonium polyphosphate with inorganic silicate (APP/InSi) primarily acts in the condensed phase (CP), and aluminum diethyl phosphinate with zinc hydroxystannate (AldietPO2/ZHS) is known to demonstrate both gas‐phase (GP) and CP activity. Fire residues are tailored to compensate for structural defects from fire exposure. EP novolac, with higher aromaticity and cross‐linking, possesses better inherent flame resistance compared to DGEBA. The novolac composites containing AldietPO2/ZHS simultaneously showed the highest retention of flexural properties after fire exposure and the best fire safety index. The experimental values of the post‐fire flexural properties in the composites calibrated damage parameters in two theoretical models. Fire retardant ; Char ; Epoxy ; Composite material ; Materials science ; Glass fiber ; Fiber ; Waste management ; Pyrolysis ; Engineering Flame retardant materials and properties ; Fire dynamics and safety research ; Fiber-reinforced polymer composites
Authors: Wenqi Liu | Shihua Zhong
Source: Photonics (article, 2025-07-19)
Field: Chemistry — Analytical Chemistry

Non-Destructive Discrimination and Traceability of Exocarpium Citrus grandis Aging Years via Feature-Optimized Hyperspectral Imaging and Broad Learning System Exocarpium Citrus grandis is a traditional Chinese medicinal and edible herb whose pharmacological efficacy is closely tied to its aging duration. The accurate discrimination of aging years is essential for quality control but remains challenging due to limitations in current analytical techniques. This study proposes a novel feature-optimized classification framework that integrates hyperspectral imaging (HSI) with a Broad Learning System (BLS). Bilateral spectral data (side A and side B) were collected to capture more comprehensive sample information. A combination of normalization (NOR) preprocessing and the Iterative Variable Importance for Spectral Subset Selection Algorithm (iVISSA) was found to be optimal. The NOR–iVISSA–BLS model achieved classification accuracies of 94.09 ± 1.01% (side A) and 95.10 ± 0.82% (side B). Furthermore, cross-validation between the two sides (A→B: 94.92%, B→A: 94.11%) confirmed the model’s robustness and generalizability. This dual-side spectral validation strategy offers a rapid, nondestructive, and reliable solution for the vintage authentication of Exocarpium Citrus grandis, contributing to the modernization of quality control in medicinal foodstuffs. Hyperspectral imaging ; Traceability ; Feature (linguistics) ; Computer science ; Remote sensing ; Artificial intelligence ; Materials science ; Pattern recognition (psychology) ; Optics ; Optoelectronics ; Physics ; Geology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Date Palm Research Studies
Authors: Buren Yang | Tengteng Zheng | Caiqi Zhao | Lihao Chen
Source: Buildings (article, 2025-12-25)
Field: Materials Science — Materials Chemistry

Mechanical, Physical, and Microstructural Performance of Road Base Materials Prepared with Magnesite Tailings Mixed with Cement Magnesite tailings are by-products of magnesite mining, yet their utilization rate remains extremely low. Although previous studies have explored their basic physical properties and potential use in cementitious or geotechnical materials, research on cement-stabilized magnesite tailings-particularly regarding their mechanical behavior, engineering applicability, and microstructural evolution-remains limited. Key scientific gaps include the lack of systematic evaluation of their compaction characteristics, strength development, stiffness evolution, and bearing capacity, as well as insufficient understanding of the stabilization mechanisms governing their performance. Addressing these gaps is essential for assessing their feasibility as road construction materials. In this study, magnesite tailings were selected as the primary raw material and mixed with ordinary Portland cement to prepare mixtures for evaluating their suitability as highway subgrade fillers. The compaction characteristics, unconfined compressive strength (UCS), ultrasonic pulse velocity (UPV), and California Bearing Ratio (CBR) of the mixtures were systematically examined. Furthermore, the evolution of composition and stabilization mechanisms of the mixtures was analyzed using X-ray diffraction, scanning electron microscopy, and thermogravimetric analysis. The results show that cement incorporation effectively improves the poor particle gradation of magnesite tailings, leading to a denser and more homogeneous structure. Adding 7% cement increases the maximum dry density and optimum moisture content by 3.7% and 5.1%, respectively. The unconfined compressive strength rises by 100.9–126.3% within 3–28 days, and the maximum uniaxial stress is 119.6% higher than that of the 1% cement mixture. These improvements demonstrate the potential of cement-stabilized magnesite tailings as a sustainable subgrade material and provide insight into their microstructural and mechanical behavior. Cementitious ; Magnesite ; Tailings ; Compressive strength ; Cement ; Portland cement ; Compaction Magnesium Oxide Properties and Applications ; Tailings Management and Properties ; Concrete and Cement Materials Research
Authors: Yu Liu | Hongtao Gu | Jincheng Zhang | Zhiyi Leng | Ziguang Wang | Shengfang Zhang
Source: Coatings (article, 2025-07-31)
Field: Materials Science — Metals and Alloys

Performance Optimization of Stacked Weld in Hydrogen Production Reactor Based on Response Surface Methodology–Genetic Algorithm To address the issues of hydrogen embrittlement, creep, and fatigue that commonly occur in the welds of hydrogen production reactor operating under hydrogen exposure, high temperature and high pressure, this study proposes adding Si and Mo as reinforcing elements to the welding materials to enhance weld performance. Given the varying performance requirements of different weld layers in the stacked weld, a gradient performance optimization method for the stacked weld of hydrogen production reactors based on the response surface methodology (RSM)–genetic algorithm (GA) is proposed. Using tensile strength, the hydrogen embrittlement sensitivity index, fatigue strain strength, creep rate and weld performance evaluation indices, a high-precision regression model for Si and Mo contents and weld performance indices was established through RSM and analysis of variance (ANOVA). A multi-objective optimization mathematical model for gradient improvement of the stacked weld was also established. This model was solved using a GA to obtain the optimal element content combination added to the welding wire and the optimal weld thickness for each weld layer. Finally, submerged arc welding experiments of the stacked weld were conducted according to the optimization results. The results show that the tensile strength of the base layer, filling layer and cover layer of the stacked weld increased by 5.60%, 6.16% and 4.53%, respectively. Hydrogen embrittlement resistance increased by 70.56%, 52.40% and 45.16%, respectively. The fatigue and creep resistance were also improved. The experimental results validate the feasibility and accuracy of the proposed optimization method. Welding ; Materials science ; Response surface methodology ; Creep ; Ultimate tensile strength ; Embrittlement ; Hydrogen ; Hydrogen embrittlement ; Composite material ; Structural engineering ; Metallurgy ; Computer science ; Corrosion ; Engineering Hydrogen embrittlement and corrosion behaviors in metals ; Welding Techniques and Residual Stresses ; Fatigue and fracture mechanics
Authors: Sartika Puspita | Sri Nabawiyati Nurul Makiyah | Masaki Kita | Ahmad Hafidul Ahkam
Source: Dental Journal (Majalah Kedokteran Gigi) (article, 2025-09-10)
Field: Materials Science — Biomaterials

Potential of Bombyx mori fibroin peptide as an inhibitor of BMP2 and TGFB1 in the treatment of pulp tissue damage Background: Silk from Bombyx mori, a species of silkworm, contains fibroin, which has good biocompatibility and is potentially suitable for medical applications, especially in the treatment of tissue damage. Purpose: This study evaluated the potential interaction of B. mori fibroin peptides with bone morphogenetic protein 2 (BMP2) and transforming growth factor beta 1 (TGFB1), which are protein markers for dentine reparative activity. Methods: The research was carried out in silico. The three-dimensional structure of the proteins was obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), and the antimicrobial potential of fibroin was evaluated using Antimicrobial Peptide Scanner v.1, the Collection of Anti-Microbial Peptides (CAMPR3), PeptideRanker, ToxinPred, AlgPred, and AllergenFP. Molecular modeling and analysis were performed with trRosetta, PrankWeb, the HDOCK server, and Discovery Studio. Results: The light chain 1 peptide (LC1), light chain 2 peptide (LC2), heavy chain 2 (HC2), and heavy chain 7 (HC7) showed high binding affinity to BMP2, while LC2, HC1, HC3, and HC6 showed high binding affinity to TGFB1 compared to silicic acid as a standard anti-inflammatory drug. Conclusion: These seven peptides can potentially interact with BMP2 or TGFB1 and might have anti-inflammatory capability. Fibroin ; Peptide ; Bone morphogenetic protein 2 ; Bombyx mori ; Biocompatibility ; Peptide sequence ; Oligopeptide Silk-based biomaterials and applications ; Insect Utilization and Effects
Authors: Sung-Hoon Kim | In Soo Joo | G. H. Kim | Kee-Choon Kwon | Ga-Ae Ryu | Sunhye Shin | Kwan‐Hee Yoo
Source: Proceedings of the AAAI Symposium Series (article, 2025-08-01)
Field: Materials Science — Materials Chemistry

Digital Twin-Driven Innovations in SOFC Electrode Virtual Engineering This study presents a digital twin-based virtual laboratory designed to optimize the manufacturing processes of electrode materials for Solid Oxide Fuel Cells (SOFC). Leveraging artificial intelligence models (R2=0.89, RMSE=0.03), the system accurately predicts critical material properties such as electrode thickness, dispersion stability, and polarization resistance. The virtual simulation of key processes—material selection, combining, coating, and sintering—significantly enhances process accuracy, efficiency, and product quality, effectively reducing experimental time and costs. Electrode ; Computer science ; Systems engineering ; Manufacturing engineering ; Engineering ; Chemistry Advancements in Solid Oxide Fuel Cells ; Digital Transformation in Industry ; Machine Learning in Materials Science
Authors: Nisreen A. Nusair | Mithun Bhowmick
Source: Preprints.org (preprint, 2025-12-16)
Field: Materials Science — Materials Chemistry

Carbon Dots and Biomimetic Membrane Systems: Mechanistic Interactions and Hybrid Nano-Lipid Platforms Carbon dots (CDs) have emerged as a distinct class of fluorescent nanomaterials distinguished by their tunable physicochemical properties, ultrasmall size, exceptional photoluminescence, versatile surface chemistry, high biocompatibility, and chemical stability, positioning them as promising candidates for biomedical applications ranging from sensing and imaging to drug delivery and theranostics. As CDs increasingly transition toward biological and clinical use, a fundamental understanding of their interactions with biological membranes becomes essential, as cellular membranes govern nanoparticle uptake, intracellular transport, and therapeutic performance. Model membrane systems, such as phospholipid vesicles and liposomes, offer controllable platforms to elucidate CD-membrane interactions by isolating key physicochemical variables otherwise obscured in complex biological environments. Recent studies demonstrate that CD surface chemistry, charge, heteroatom doping, size, and hydrophobicity, together with membrane composition, packing density, and phase behavior, dictate nanoparticle adsorption, insertion, diffusion, and membrane perturbation. In addition, CD-liposome hybrid systems have gained momentum as multifunctional nanoplatforms that couple the fluorescence and traceability of CDs with the encapsulation capacity and biocompatibility of lipid vesicles, enabling imaging-guided drug delivery and responsive theranostic systems. This review consolidates current insights into the mechanistic principles governing CD interactions with model membranes and highlights advances in CD-liposome hybrid nanostructures. By bridging fundamental nanoscale interactions with translational nanomedicine strategies, this work provides a framework for the rational design of next-generation CD-based biointerfaces with optimized structural, optical, and biological performance. Nanomedicine ; Drug delivery ; Membrane ; Biocompatibility ; Nanomaterials ; Membrane biophysics ; Biological membrane ; Nanocarriers Carbon and Quantum Dots Applications ; Polydiacetylene-based materials and applications ; Supramolecular Self-Assembly in Materials
Authors: Ning An | Bofeng Li | Yuexing Wang | Xiangyu Sun | Xu He
Source: Research Square (preprint, 2025-12-12)
Field: Materials Science — Materials Chemistry

An improved unified creep‐plasticity constitutive model for viscoplastic solder materials of electronic packaging subjected to high-strain-rate impact loadings Viscoplasticity ; Split-Hopkinson pressure bar ; Soldering ; Constitutive equation ; Reliability (semiconductor) ; Electronic packaging ; Deformation (meteorology) ; Joint (building) ; Finite element method High-Velocity Impact and Material Behavior ; Electronic Packaging and Soldering Technologies ; Energetic Materials and Combustion
Authors: A. Guler
Source: Processes (article, 2025-06-24)
Field: Materials Science — Biomaterials

Thermodynamic and Structural Signatures of Arginine Self-Assembly Across Concentration Regimes Arginine plays a critical role in biomolecular interactions due to its guanidinium side chain, which enables multivalent electrostatic and hydrogen bonding contacts. In this study, atomistic molecular dynamics simulations were conducted across a broad concentration range (26–605 mM) to investigate the thermodynamic and structural features of arginine self-assembly in aqueous solution. Key observables—including hydrogen bond count, radius of gyration, contact number, and isobaric heat capacity—were analyzed to characterize emergent behavior. A three-regime aggregation pattern (dilute, cooperative, and saturated) was identified and quantitatively modeled using the Hill equation, revealing a non-linear transition in clustering behavior. Spatial analyses were supplemented with trajectory-based clustering and radial distribution functions. The heat capacity peak observed near 360 mM was interpreted as a thermodynamic signature of hydration rearrangement. Trajectory analyses utilized both GROMACS tools and the MDAnalysis library. While force field limitations and single-replica sampling are acknowledged, the results offer mechanistic insight into how arginine concentration modulates molecular organization—informing the understanding of biomolecular condensates, protein–nucleic acid complexes, and the design of functional supramolecular systems. The findings are in strong agreement with experimental observations from small-angle X-ray scattering and differential scanning calorimetry. Overall, this work establishes a cohesive framework for understanding amino acid condensation and reveals arginine’s concentration-dependent behavior as a model for weak, reversible molecular association. Arginine ; Chemistry ; Self-assembly ; Thermodynamics ; Statistical physics ; Biophysics ; Materials science ; Nanotechnology ; Physics ; Biology ; Biochemistry ; Amino acid Supramolecular Self-Assembly in Materials ; Surfactants and Colloidal Systems ; Methane Hydrates and Related Phenomena
Authors: Wise Herowati | Muhamad Akrom
Source: Journal of Multiscale Materials Informatics (article, 2025-06-14)
Field: Materials Science — Materials Chemistry

Comparative Study of Classical, Quantum, and Hybrid Stacking Models for Predicting Corrosion Inhibition Efficiency Using QSAR Descriptors This study investigates the performance of classical, quantum, and hybrid classical-quantum stacking models in predicting Corrosion Inhibition Efficiency (IE%) using 14 QSAR descriptors. The hybrid model combines a Gradient Boosting Regressor (GBR) and a Quantum Support Vector Regressor (QSVR) through a meta-learner (Ridge Regression). Results show a significant improvement over traditional models. The hybrid stacking model achieved an R² of 0.834, an MSE of 8.123, an MAE of 2.371, and an RMSE of 2.850, outperforming both individual classical and quantum models. These results confirm the strength of hybrid models in capturing both complex nonlinear and quantum-interaction patterns in QSAR-based molecular prediction. Quantitative structure–activity relationship ; Stacking ; Quantum ; Boosting (machine learning) ; Computer science ; Nonlinear system ; Biological system ; Mathematics ; Artificial intelligence ; Machine learning ; Chemistry ; Physics ; Quantum mechanics Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Machine Learning in Materials Science
Authors: Svetlana V. Eliseeva
Source: Chemical Science (article, 2025-12-04)
Field: Materials Science — Materials Chemistry

A reflection on “Intriguing aspects of lanthanide luminescence” Lanthanide luminescence surrounds us in everyday life and is essential for cutting-edge technological and healthcare applications. In 2013, we published a minireview in <i>Chemical Science</i> (<i>Chem. Sci.</i>, 2013, <b>4</b>, 1939-1949, https://doi.org/10.1039/C3SC22126A) that was focused on the latest innovations and less-known aspects of lanthanide luminescence in applications such as biological imaging, sensing and therapy, security inks and anti-counterfeiting tags, luminescent probes and sensors, and solar energy conversion. Herein, a discussion of the progress of this field is provided with support of the most recent examples in the areas of circularly polarized luminescence, nanothermometry and multiplexed biological imaging in the extended second near-infrared window (NIR-II, 1000-3000 nm). Lanthanide ; Luminescence ; Reflection (computer programming) ; Rare earth ; Field (mathematics) ; Multiplexing Lanthanide and Transition Metal Complexes ; Luminescence Properties of Advanced Materials ; bioluminescence and chemiluminescence research
Authors: Dominika Koperová | Tadeáš Matěcha | Allen A. Espinosa | Martin Rusek
Source: Chemistry Teacher International (article, 2025-11-01)
Field: Chemistry — Physical and Theoretical Chemistry

Assessing experimental activities in chemistry instruction: a systematic review of available tools Abstract Experimental activities have historically been an integral part of chemistry education. However, researchers have highlighted the limited empirical evidence supporting their effectiveness. This study provides a systematic review of tools available for experimental activities’ assessment. A review of 68 studies indexed in the Web of Science database revealed several available tools which, however, may not comprehensively address all educational aspects satisfactorily. Most assessment tools target higher education, with limited focus on primary and secondary levels. Strong emphasis is placed on cognitive outcomes, while affective, psychomotor or other domains remain underrepresented or poorly integrated. The review also highlighted emerging trends, such as virtual labs and interdisciplinary approaches, emphasizing the need for specialized assessment tools to evaluate these innovations effectively. These findings resulted in the development of a comprehensive table that offers educators and researchers valuable insights into available assessment tools. This resource enables the selection of appropriate tools based on criteria such as activity type, chemistry subdiscipline, assessed domain, and tool type, with the option to apply filters for more targeted searches. The review also highlights a greater emphasis on comprehensive, validated tools is essential for enhancing experiment-based learning in chemistry education. Resource (disambiguation) ; Systematic review ; Table (database) ; Selection (genetic algorithm) ; Focus (optics) Various Chemistry Research Topics ; Science Education and Pedagogy ; Innovative Teaching Methods
Authors: Seong-Min Kim | Daihui Wu | Yilong Han
Source: Nature Communications (article, 2025-12-10)
Field: Materials Science — Materials Chemistry

Percolation transition in entangled granular networks Highly nonconvex granular particles, such as staples and metal shavings, can form solid-like cohesive structures through geometric entanglement (interlocking). However, the network structure formed by this entanglement remains largely unexplored. Here, we employ network science to investigate the entanglement networks of C-shaped granular particles under vibration in experiments and simulations. Analysis of key network properties reveals that these networks undergo a percolation transition as the number of links increases logarithmically over time; the entangled particles form a giant cluster when the number of links exceeds a critical threshold. We propose a continuum percolation model of rings that effectively describes this observed transition. Furthermore, we find that the particles' opening angle significantly affects mechanical bonding and, consequently, the network structure. This work demonstrates the promise of network-based approaches for studying entangled materials, with potential applications from mechanical metamaterials to entangled robot swarms. Quantum entanglement ; Percolation (cognitive psychology) ; Percolation threshold ; Metamaterial ; Cluster (spacecraft) ; Work (physics) ; Key (lock) ; Topology (electrical circuits) Material Dynamics and Properties ; Micro and Nano Robotics ; Granular flow and fluidized beds