jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ge Pan | Wei Deng | Ming Hu | Bo Peng | Miaomiao Zhang | Zongjia Li | Qian Duan | Jilin Tang | Dapeng Wang
Source: ACS Applied Materials & Interfaces (article, 2025-12-19)
Field: Materials Science — Materials Chemistry

Leveraging the Concentration-Gradient Diffusion within a Catalyst-Containing Hydrogel Bilayer Enables Safe and Effective Tooth Whitening and Caries Prevention Tooth whitening has attracted considerable attention as it can enhance appearance and improve oral health. Nanocatalysts with peroxidase-like activity can catalyze H<sub>2</sub>O<sub>2</sub> to generate reactive oxygen species (ROS), a process known as chemodynamic therapy (CDT). The ROS generation can achieve effective tooth whitening and caries prevention. Nonetheless, traditional CDT methods often struggle with controlling the reaction process by adjusting the concentrations of H<sub>2</sub>O<sub>2</sub> or nanocatalysts. An excessive ROS can harm oral tissues, whereas insufficient ROS may compromise therapeutic efficacy. To address this issue, this study designed a hydrogel bilayer that separately encapsulates H<sub>2</sub>O<sub>2</sub> and iron-based metal-organic frameworks (Fe-MOFs) nanoparticles (NPs) with peroxidase-like activity. The ROS generation was regulated by leveraging the concentration-gradient diffusion of H<sub>2</sub>O<sub>2</sub>. Through Monte Carlo simulations and machine learning algorithms, mathematical formulas were derived to elucidate how to harness concentration-gradient diffusion for near-independent modulation of the reaction half-life and rate. The experimental results demonstrated that being guided by the formulas could effectively avoid the initial burst of ROS and manipulate the ROS generation duration, thereby achieving safe and effective tooth whitening and caries prevention. We anticipate that this bilayer design strategy can be extended to other CDT systems, enabling precise control over therapeutic outcomes. Bilayer ; Tooth whitening ; Reactive oxygen species ; Process (computing) ; Diffusion ; Flexibility (engineering) Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Oral microbiology and periodontitis research
Authors: Katarína Skladanová | Tomáš Bučko
Source: The Journal of Chemical Physics (article, 2025-09-23)
Field: Materials Science — Materials Chemistry

Adsorption of benzene on graphene studied by ML-accelerated <i>ab initio</i> molecular dynamics simulations Periodic ab initio molecular dynamics simulations accelerated by machine learning were conducted to investigate the adsorption of benzene on graphene at a coverage of 0.11 ML and a temperature of 150 K. For this purpose, seven density functional approximations (DFAs) were used, differing in the exchange-correlation functional (PBE, SCAN, HSE06, and vdW-optB86b) and the long-range dispersion correction (D2, D3, D4, and MBD). Thermal effects on the structure, enthalpy (ΔadsH), and Gibbs free energy (ΔadsG) of adsorption were analyzed. The relatively fast surface diffusion of the adsorbate was identified as the dominant anharmonic effect causing an increase in ΔadsG of up to 50% compared to static harmonic calculations. In contrast, the anharmonic effect on ΔadsH was shown to be nearly negligible. The computed thermodynamic data were used to predict the desorption kinetics parameters, i.e., activation energy (Ea), Arrhenius pre-factor (ν), and position of desorption maximum (Tmax). Among the DFAs tested, the PBE + D4 method was found to provide the best overall agreement with the experimental data. The SCAN + MBD, PBE + D3, and PBE + D2 methods predict Ea values that agree with the experimentally determined value within the reported uncertainty but significantly underestimate Tmax. Anharmonicity ; Molecular dynamics ; Adsorption ; Diffusion ; Gibbs free energy ; Enthalpy ; Desorption ; Arrhenius equation Graphene research and applications ; Catalytic Processes in Materials Science ; Covalent Organic Framework Applications
Authors: Wenjie Xie | Qianfeng Xu | Zeheng Tan | Jundong Lin | Fen Zou | Muqi Chen | Jiaquan Xu | Guowei Zhong | Qiuling Du | Jinxiang Zhang | Jibiao Li | Minyao Jiang | Ming Xi | Hua Wei | Yangjia Zhuo | Yuting Zhang | Qi-Shan Dai | Weide Zhong
Source: ACS Omega (article, 2025-12-19)
Field: Materials Science — Materials Chemistry

Integrating Proteomics and Predictive Model: Elucidating the Role of Aminated Nanodiamonds in Suppressing Prostate Cancer Growth Prostate cancer (PCa) presents a formidable therapeutic challenge owing to the limited efficacy of existing treatments. In this study, a series of comparative experiments demonstrated that nanodiamonds (NDs) with different functional groups exhibit inhibitory effects on the growth, replication, and migration of prostate cancer cells without directly killing the cells. Among them, aminated nanodiamonds (aNDs) showed the most pronounced inhibitory activity. Subsequently, a combination of proteomics analysis and machine learning was employed to elucidate the molecular mechanisms by which these aNDs exerted their inhibitory effects on PCa progression. Data-independent acquisition proteomics identified the key proteins affected by the aNDs, and the Kyoto Encyclopedia of Genes and Genomes analysis revealed ribosome pathway enrichment. Bioinformatics analysis focused on ten crucial genes, thus incorporating a novel prognostic model that categorized patients based on gene expression and emphasized the significance of mitochondrial ribosomal protein L22 (MRPL22). In vivo experiments confirmed the antitumor effects and biocompatibility of the aNDs. In addition, an analysis of the response of MRPL22 to anticancer drugs in public databases revealed its relevance to a range of drugs and compounds. In summary, this study integrated diverse interdisciplinary methodologies, thereby offering insights into the mechanism of the inhibition of PCa by the aNDs and the regulatory role of MRPL22 in the ribosomal pathway. Proteomics ; Prostate cancer ; KEGG ; Ribosomal protein ; Ribosome ; Mechanism (biology) ; Cancer ; In vivo Diamond and Carbon-based Materials Research ; Cancer, Lipids, and Metabolism ; Prostate Cancer Treatment and Research
Authors: Ruizhao Liu | Zhiwu Chen | Zhenya Lu | Xin Wang
Source: Ceramics International (article, 2025-04-17)
Field: Materials Science — Materials Chemistry

Machine learning-assisted study of the effects of CaZrO3 and Y2O3 co-doping on the dielectric properties of X8R BaTiO3 based ceramics Materials science ; Dielectric ; Doping ; Ceramic ; Chemical engineering ; Engineering physics ; Composite material ; Optoelectronics Ferroelectric and Piezoelectric Materials ; Dielectric materials and actuators ; Microwave Dielectric Ceramics Synthesis
Authors: Qi Meng | Chuan‐Lu Yang | Xiaohu Li | Yuliang Liu | Wenkai Zhao | Feng Gao
Source: Physical Chemistry Chemical Physics (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Ultralow lattice thermal conductivity and enhanced thermoelectric performance in the AgKTe monolayer induced by four-phonon scattering The lattice thermal conductivity (<i>κ</i><sub>l</sub>) for the AgKTe monolayer is obtained using the second-, third-, and fourth-order interatomic force constants by machine learning methods. Remarkably, the inclusion of four-phonon (4ph) scattering processes leads to a significant reduction-by approximately 50-66%-in the <i>κ</i><sub>l</sub> value compared to calculations considering only three-phonon (3ph) processes. Consequently, an ultralow <i>κ</i><sub>l</sub> value of 0.03 W m<sup>-1</sup> K<sup>-1</sup> is achieved along the <i>x</i> and <i>y</i> directions, respectively, at 600 K, placing AgKTe among the 2D materials with the lowest known thermal conductivities. This highlights the pivotal role of 4ph scattering in suppressing phonon transport. Moreover, a highly degenerate valence band substantially boosts the power factor of p-type carriers. Benefiting from both the reduced <i>κ</i><sub>l</sub> and enhanced electronic transport, the AgKTe monolayer achieves a high thermoelectric figure of merit (<i>ZT</i>) of 3.87 at 600 K and intrinsic carrier concentrations. By revealing the dominance of 4ph scattering in <i>κ</i><sub>l</sub>, this work not only suggests AgKTe as a viable thermoelectric candidate but also deepens the understanding of thermal behavior in low-dimensional structures. Monolayer ; Phonon ; Thermal conductivity ; Condensed matter physics ; Thermoelectric effect ; Materials science ; Scattering ; Thermoelectric materials ; Phonon scattering ; Lattice (music) ; Lattice constant ; Nanotechnology ; Physics ; Thermodynamics ; Composite material ; Quantum mechanics Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Machine Learning in Materials Science
Authors: Xianghui Meng | Yanqing Shen | Xin Yang | Chun Wu | Qing Ai | Yong Shuai | ZhongXiang Zhou
Source: Physical review. B./Physical review. B (article, 2025-11-13)
Field: Materials Science — Materials Chemistry

Effects of anharmonic phonons on superconductivity in the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>NH</mml:mi> <mml:mn>4</mml:mn> </mml:msub> </mml:math> -intercalated boron-carbon clathrate <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>NH</mml:mi> <mml:mn>4</mml:mn> </mml:msub> <mml:msub> <mml:mi mathvariant="normal">B</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:msub> <mml:mi mathvariant="normal">C</mml:mi> <mml:mn>8</mml:mn> </mml:msub> </mml:mrow> </mml:math> Achieving structural stability and high critical temperature $({T}_{c})$ in hydrides under ambient conditions remains a major challenge. A feasible design strategy integrates the advantages of two material classes: (i) B-C--based clathrate superconductors, which exhibit excellent structural stability at ambient or relatively low pressures, and (ii) hydrogen-based unit, which possesses the potential for high ${T}_{c}$. Guided by this strategy, we theoretically predict a hypothetical compound ${\mathrm{NH}}_{4}{\mathrm{B}}_{2}{\mathrm{C}}_{8}$ by embedding hydrogenated units into a B-C clathrate framework. Using the stochastic self-consistent harmonic approximation combined with machine-learning-accelerated structural sampling, we assess the impact of anharmonicity on its superconducting properties. Anharmonic effects harden the dominant phonon modes 13--15, reducing the electron-phonon coupling constant $\ensuremath{\lambda}$ from 1.43 to 1.22 and lowering ${T}_{\text{c}}$ from 102 to 91 K. Furthermore, hole doping realized by ${\mathrm{NH}}_{4}$ vacancy engineering, which yields ${({\text{NH}}_{4})}_{3}{({\text{B}}_{2}{\text{C}}_{8})}_{4}$, is demonstrated to be ineffective in enhancing ${T}_{c}$ under anharmonic conditions. Our results highlight the synergistic role between hydrogen units and B-C frameworks in enhancing superconductivity, and underscore the importance of anharmonicity in the design of such superconductors. Anharmonicity ; Superconductivity ; Phonon ; Clathrate hydrate ; Coupling (piping) ; Stability (learning theory) ; Structural stability Boron and Carbon Nanomaterials Research ; Superconductivity in MgB2 and Alloys ; Inorganic Chemistry and Materials
Authors: Shiyang He | Yongxia Han | Zicai Zhao | Wentao Huang | Jiahao Shi | Yang Dong | Haojun Lin | Licheng Li
Source: IEEE Transactions on Instrumentation and Measurement (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Experimental Database and Prediction Model of Insulators Flashover Under Lightning Impulse Lightning flashover criteria of insulators and air gaps are the basis of the external insulation design for transmission lines. However, the mechanisms of long air gap discharges remain unclear. This paper aims to establish a comprehensive database of lightning impulse tests for insulators/air gaps based on extensive experiments conducted over the past twelve years, making it feasible to predict the flashover characteristics of insulators/air gaps accurately through machine learning algorithms. Firstly, a comparative analysis of experimental results from various institutions over the years reveals that the flashover characteristics are significantly influenced by many factors, including gap/insulator length, voltage waveform, insulator materials, and meteorological conditions. Subsequently, a publicly accessible insulator/air gap flashover test database is constructed to realize the real-time storage, management, and analysis of test data. Ultimately, the input features are selected by correlation analysis. The intelligent prediction models for the lightning flashover characteristics of 220kV insulators are developed by algorithms, including SVR (Support Vector Regression), ELM (Extreme Learning Machine), XGBoost (eXtreme Gradient Boosting), and RF (Random Forest). The results demonstrate that the SVR algorithm achieved a mean absolute percentage error (MAPE) of merely 2.19% in predicting U50% compared to the experimental results. Meanwhile, XGBoost achieved the lowest error of 18% in volt-time characteristics. It shows promising potential for more accurate criteria through the use of the test database and advanced algorithms. Arc flash ; Lightning (connector) ; Impulse (physics) ; Computer science ; Electrical engineering ; Engineering ; Physics ; Voltage ; Power (physics) High voltage insulation and dielectric phenomena
Authors: Changpeng Lin | Jian Han | Ben Xu | Nicola Marzari
Source: ArXiv.org (preprint, 2025-08-01)
Field: Materials Science — Materials Chemistry

First-principles phonon physics using the Pheasy code Parameter-free calculations of lattice dynamics from first principles have achieved significant progress in the past decades, with a wealth of applications in thermodynamics, phase transitions, and transport properties of materials. Current approaches to derive the interatomic force constants (IFCs) of lattice potential become challenging and sometimes infeasible when going beyond third-order anharmonicity, due to the combinatorial explosion in the number of higher-order IFCs. In this work, we present a robust and user-friendly program, Pheasy, which accurately reconstructs the potential energy surface of crystalline solids via a Taylor expansion of arbitrarily high order. Given force-displacement datasets, the program enables an efficient and accurate extraction of IFCs using advanced machine-learning algorithms, and further calculates a wide range of harmonic and anharmonic phonon related properties. We show in three prototypical examples how the obtained IFCs have been successfully applied to study anharmonic lattice dynamics and thermal transport. Through these detailed benchmarks, we have also identified the optimal approach for IFC extractions and offered general guidelines for high-fidelity lattice-dynamical simulations, addressing the large uncertainties in the IFCs extracted from existing various schemes. Overall, the Pheasy project aims to create a phonon code ecosystem that connects diverse phonon simulation platforms and offers access to the broad research community. Anharmonicity ; Phonon ; Lattice (music) ; Interatomic potential ; Code (set theory) ; Thermal ; Phase transition ; Range (aeronautics) Machine Learning in Materials Science ; Thermal properties of materials ; Thermal Expansion and Ionic Conductivity
Authors: Marios Spanakis | Evangelos Bakaros | Stella-Natalia Papadopoulou | Agapi Fournaraki | Emmanouil K. Symvoulakis
Source: Pharmacoepidemiology (article, 2025-10-09)
Field: Chemistry — Organic Chemistry

Pharmacoepidemiological Data on Drug–Herb Interactions: Serotonin Syndrome, Arrhythmias and the Emerging Role of Artificial Intelligence Herbal medicinal products are increasingly used alongside conventional medicines, raising the risk of potential interactions such as pharmacodynamic drug–herb interactions (PD-DHIs) that can cause serious adverse drug reactions (ADRs). This review aims to present available pharmacological, clinical and pharmacoepidemiological literature regarding potential DHIs associated with serotonin syndrome or cardiac arrhythmias. Furthermore, it assesses the current evidence using the Oxford Centre for Evidence-Based Medicine (CEBM) 2009 framework. Serotonin syndrome most often results from combining serotonergic herbs (e.g., St. John’s wort) with antidepressants like serotonin reuptake inhibitors (SSRIs), as supported by repeated case reports and mechanistic plausibility (CEBM Level 3, Grade C). Other herbs such as black cohosh, ginseng, Syrian rue, turmeric, rhodiola, ashwagandha, and L-tryptophan/5-HTP have been linked to serotonin syndrome when used with SSRIs, serotonin-norepinephrine reuptake inhibitors (SNRIs), or monoamine oxidase inhibitors (MAOIs), but evidence is limited (Levels 4–5, Grade D). For cardiac arrhythmias, PD-DHIs arise when herbs interact with drugs that alter cardiac electrophysiology—such as QT-prolonging agents, psychotropics, antiarrhythmics or digoxin—thereby amplifying arrhythmogenic risk. Ephedra with sympathomimetics is strongly associated with arrhythmias (Level 2–3, Grade B). Licorice may potentiate digoxin and QT-prolonging drugs via hypokalemia (Level 4, Grade C). Other related PD-DHIs include aconite with antiarrhythmics, bitter orange or caffeine with QT-prolonging psychotropics, yohimbine with cardiovascular agents, and aloe or senna with digoxin. Overall, the evidence for PD-DHIs varies from moderate to weak but large-scale pharmacoepidemiological data is scarce. Future approaches, including artificial intelligence with explainable machine learning and network pharmacology, may integrate mechanistic, clinical, and real-world data to improve early detection or prediction of PD-DHIs. However, several specific challenges must be addressed. Therefore, it is crucial for healthcare providers in both clinical and community settings to increase their awareness of these interactions and ADRs to ensure the safe use of herbal remedies alongside conventional therapies. Serotonergic ; Serotonin syndrome ; Serotonin ; Monoamine oxidase ; MDMA ; Pharmacovigilance ; Cardiac arrhythmia ; Drug Chemical synthesis and alkaloids ; Plant-based Medicinal Research ; Complementary and Alternative Medicine Studies
Authors: John Peter Kachira | Robinson Musembi | Francis Nyongesa | Mwende Mbilo | Martin Nyamunga | Ibrahim Musanyi
Source: Next Materials (article, 2025-05-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ab-Initio investigation of the structural, electronic, mechanical, thermophysical, and optical properties of the Zintl-phase K₂AgSb ternary compound for optoelectronic applications A Zintl-phase K₂AgSb ternary compound has been investigated using density functional theory (DFT) on its structural, electronic, mechanical, thermophysical, and optical properties. Various exchange-correlation functionals have been employed, including the local density approximation (LDA) and generalised gradient approximation (GGA). Regularised strongly constrained and appropriately normed (RSCAN) and Tran-Blaha modified Becke-Johnson (TB-mBJ) functionals were utilised to enhance the accuracy of electronic structure predictions. The computed band gap values were 1.1601 eV and 1.2559 eV using LDA and GGA approximations, respectively. In contrast, more refined estimates of 1.5274 eV and 1.8917 eV were obtained using the RSCAN and TB-mBJ functionals. Machine learning (ML) has been used to predict critical properties, such as band gaps and elastic moduli, and to guide the discovery of new materials with optimal performance. However, ML predicted the smallest band gap (0.94 eV), which may be due to limitations in the training data, systematic biases, or an inability to fully capture material-specific electronic structure corrections. The projected density of states (PDOS) analysis revealed that the K4 p , Ag2 p , and K2 s orbitals primarily contribute to the formation of the conduction band, whereas the Ag3d, Sb2p, and K1s orbitals dominate the valence band formation. Analysis of the mechanical properties confirmed that K₂AgSb is ductile with ionic bonding, which is a characteristic of Zintl-phase compounds. The optical properties demonstrated strong absorption within the ultraviolet - visible (1.0–15 eV) range, high refractive index, and a pronounced plasmonic response, highlighting its potential for optoelectronic and plasmonic technology applications. In addition, the reflectivity and energy loss spectra suggest the suitability of K₂AgSb for optical coatings and high-performance photonic devices. Ternary operation ; Materials science ; Ab initio ; Phase (matter) ; Ab initio quantum chemistry methods ; Crystallography ; Optoelectronics ; Chemistry ; Computer science ; Molecule Heusler alloys: electronic and magnetic properties ; Intermetallics and Advanced Alloy Properties ; Chalcogenide Semiconductor Thin Films
Authors: Shuying Lin | Linbing Jiang | Baoliang Zhang | Xi-Jun Wu | Siyi Shen | Yu Ma | Wenguan Liu
Source: Journal of Nuclear Materials (article, 2025-11-29)
Field: Materials Science — Materials Chemistry

Effects of vacancies and voids on hydrogen behavior in yttrium hydrides Yttrium ; Hydrogen ; Molecular dynamics ; Redistribution (election) ; Diffusion ; Hydride ; Molecule ; Hydrogen molecule Nuclear Materials and Properties ; Fusion materials and technologies ; Hydrogen Storage and Materials
Authors: Sachin Upadhye | Prafulla O. Bagde | Sanjay R. Sange | Achal Rokade | Mayuri A. Chandak | Tejas R. Patil | Niteen T. Kakade | Nilesh Shelke
Source: Asian Journal of Civil Engineering (article, 2025-03-15)
Field: Materials Science — Surfaces, Coatings and Films

Optimization and multi-functional predictive performance of advanced superhydrophobic cementitious materials for water-resistant infrastructure Cementitious ; Materials science ; Computer science ; Composite material Surface Modification and Superhydrophobicity ; Aerogels and thermal insulation ; Solar-Powered Water Purification Methods
Authors: Shuyan Zhao | Boyan Zhao | Yong Wang | Yanrong Li | Essy Kouadio Fodjo | Wei Deng | Dan Li
Source: ACS Applied Materials & Interfaces (article, 2025-12-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Utilizing a SHAP-Assisted Machine Learning Algorithm for Optimization of Plasmonic Properties of Gold Nanostructure Gold nanostructures (GNSs) have tunable optical absorption and catalytic properties and thus are increasingly used in molecular sensing and nanomanufacturing. However, the rapid design of GNSs with specific optical properties is limited by various factors, making it difficult to achieve efficient design by conventional trial-and-error methods. Here, we report a SHapley Additive exPlanations (SHAP)-assisted extreme gradient boosting (XG-Boost) model for conducting the preparation of GNSs with preferential plasmonic features using silver nitrate (AgNO<sub>3</sub>) and ascorbic acid in different surfactants at room temperature. The XG-Boost model achieves exceptional predictive accuracy (<i>R</i><sup>2</sup> > 0.98, RMSE < 0.03). Importantly, SHAP elucidates the underlying mechanism linking synthetic conditions to plasmonic properties of GNSs, particularly revealing the contribution of surfactants to predictions, which was previously underestimated. Guided by the XG-Boost-SHAP strategy, GNSs with tunable localized surface plasmon resonance peaks and high stability are designed and precisely synthesized in various shapes. The GNSs were successfully applied to thiourea detection, Hg<sup>2+</sup> recognition, glucose analysis, and fabrication of luminescent chips. The results demonstrate the remarkable potential of the machine-learning framework in tailoring GNSs with personalized features to realize various objectives. Nanostructure ; Plasmon ; Surface plasmon resonance ; GNSS applications ; Fabrication ; Surface plasmon ; Stability (learning theory) Gold and Silver Nanoparticles Synthesis and Applications ; Machine Learning in Materials Science ; Laser-Ablation Synthesis of Nanoparticles