jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nikolaos Patsalidis (13870231) | Mohsen Doust Mohammadi (22039421) | Somnath Bhowmick (2142640) | George Biskos (1435339) | Vagelis Harmandaris (1454050)
Source: Figshare (article, 2025-08-12)
Field: Materials Science — Materials Chemistry

Active Learningof Atomic Size Gas/Solid PotentialEnergy Surfaces via Physics Aware Models We propose an active learning (AL) framework to develop classical force fields (FFs) that accurately model the potential energy surfaces (PES) of gas/solid atomic-scale complexes. A central challenge is integrating AL with flexible, computationally efficient physics-aware potentials to achieve quantum-level accuracy for complex interfacial systems. Our approach trains physics-aware potentials, with incorporated flexibility and smoothness, on actively sampled density functional theory (DFT) data to describe interactions between undercoordinated atomic silver (Ag) clusters and gaseous pollutants (CO<sub>2</sub>, CO, SO<sub>2</sub>), relevant for environmental applications like sensing. The AL process follows three stages: (1) FFs are trained using adaptable physics aware potentials of semiempirical descriptors, optimized via a Pareto analysis scheme; (2) new candidate structures are generated through the use of the refined FFs in Metropolis Hastings Monte Carlo (MHMC) or stochastic molecular dynamics (sMD) simulations; (3) a subset of candidates is selected for DFT computations based on an outlier score (OS), which utilizes the existing data descriptor distributions, ensuring diverse PES exploration. This framework produces FFs capable of capturing cohesive, physisorption, and chemisorption interactions with admirable accuracy, close to ab initio methods, while retaining the efficiency of semiempirical potentials. To demonstrate, produced FFs are utilized in molecular dynamics (MD) simulations of single Ag clusters embedded in bulk gas phases, examining condensation characteristics. Our methodology is highly versatile, easily accommodating various choices of descriptors, model basis sets, and sampling techniques. Molecular dynamics ; Ab initio ; Flexibility (engineering) ; Computation ; Outlier ; Monte Carlo method ; Process (computing) ; Density functional theory ; Potential energy Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Quantum many-body systems
Authors: Daniil Poletaev | Artem Oganov
Source: arXiv (Cornell University) (preprint, 2025-12-31)
Field: Materials Science — Materials Chemistry

SSCHA-based evolutionary crystal structure prediction at finite temperatures with account for quantum nuclear motion Accurate crystal structure prediction (CSP) at finite temperatures with quantum anharmonic effects remains challenging but very prominent in systems with lightweight atoms such as superconducting hydrides. In this work, we integrate machine-learned interatomic potentials (MLIPs) with the stochastic self-consistent harmonic approximation (SSCHA) to enable evolutionary CSP on the quantum anharmonic free-energy landscape. Using LaH$_{10}$ at 150 GPa and 300 K as a test case, we compare two approaches for SSCHA-based CSP: using light-weight active-learning MLIPs (AL-MLIPs) trained on-the-fly from scratch, and foundation models or universal MLIPs (uMLIPs) from the Matbench project. We demonstrate that AL-MLIPs allow to correctly predict the experimentally known cubic Fm$\bar{3}$m phase as the most stable polymorph at 150 GPa but require corrections within the thermodynamic perturbation theory to get consistent results. The uMLIP Mattersim-5m allow to conduct SSCHA-based CSP without requiring per-structure training and even get correct structure ranking near the global minimum, though fine-tuning may be needed for higher accuracy. Our results show that including quantum anharmonicity simplifies the free-energy landscape and is essential for correct stability rankings, that is especially important for high-temperature phases that could be missed in classical 0 K CSP. The proposed approach extends the reach of CSP to systems where quantum nuclear motion and anharmonicity dominate. Anharmonicity ; Crystal structure prediction ; Quantum ; Stability (learning theory) ; Perturbation (astronomy) ; Perturbation theory (quantum mechanics) ; Harmonic Machine Learning in Materials Science ; Quantum many-body systems ; Quantum, superfluid, helium dynamics
Authors: Aleksandr I. Buglakov | Kristina A. Belkina | V. V. Vasilevskaya
Source: Journal of Molecular Liquids (article, 2025-10-27)
Field: Chemistry — Organic Chemistry

Structure, permeability and load capacity of vesicles from amphiphilic comb-coil diblock copolymers: Active learning assisted computer simulation Vesicle ; Amphiphile ; Solvophobic ; Copolymer ; Membrane ; Permeability (electromagnetism) ; Phase diagram Advanced Polymer Synthesis and Characterization ; Polymer Surface Interaction Studies ; Block Copolymer Self-Assembly
Authors: Wenze Song | Yi Li
Source:  (article, 2025-03-21)
Field: Materials Science — Polymers and Plastics

Deep Learning and Multi-Model Fusion for Analyzing Staircase Wear and Human Traffic Patterns This paper aims at providing scientific guideline for archaeological research by analyzing the relationship between stair wear and human activity patterns. The Archard Model is adopted to build staircase wear model to take account of human activities and natural influences. A Dynamic Wear Differential Equation is derived and the Numerical stability is ensured by spatial and temporal discretization, explicit Eulerian and CFL conditions. The maximum, minimum and average wear depth are 1.5568 mm, 0.0668 mm and 0.3452 mm, respectively, which is consistent with the assumptions of human activity habits and Gaussian distribution of pedestrian flow. A Multi-Source Information Fusion Model, which employs a simplified Archard wear equation, is constructed to predict human activity patterns. A Gradient Boosted Decision Tree (GBDT) was applied to fit the model, and 5-fold cross-validation and Bayesian optimization were used to improve the prediction accuracy. The usage frequency of the stair can be estimated as 493 persons/day. To predict the walk direction and pattern, the longitudinal and lateral features are defined, and the Gaussian Mixture Model (GMM) and Bayesian Classification Framework are applied. The obtained results show that the peak spacing: 0.39 m and the asymmetry index: 0.10. A Multi-Angle Analysis of Measurement Model is proposed to optimize the measurement data collection. The sampling density function, error evaluation model and time measurement model are established and solved iteratively. The results exhibit high accuracy with average measurement error of 0.003 mm and total measurement time of 421.55 hours, which indicates the data obtained by the proposed measurement scheme is reliable for the subsequent analysis. To realize the time series reconstruction of the staircase by the Markov Chain Monte Carlo (MCMC) method, the Bayesian Temporal Inference Model and Multi-information Historical Reconstruction Model are developed. The factors which have great influence on the staircase wear are considered including the intensity of use, environmental impacts, and maintenance activities. To validate the proposed model and method, and the given dataset is adopted. The age of the staircase is estimated to be about 219.2 years, with an error no more than 40 years. The model was also effective in analyzing the reliability of the renovation, material sources, and historical records with a reliability index of 0.8. The sensitivity analysis is performed to quantify the prediction error using Mean Absolute Error (MAE). Compared with the impact of human activity intensity and path distribution standard deviation, the diffusion coefficient has a greater impact on the accuracy of predicting the frequency of stair use. Fusion ; Computer science ; Deep learning ; Artificial intelligence ; Machine learning Textile materials and evaluations ; Industrial Vision Systems and Defect Detection
Authors: Sergio Fuentes Anton (22316776)
Source: Figshare (article, 2025-09-26)
Field: Chemistry — Physical and Theoretical Chemistry

From Childhoodto Classroom: Teaching the PeriodicTable of Elements through Collectible Sticker Cards Sticker cards are widely recognized as popular memorabilia and appealing to both children and adults. Their potential as an educational tool remains largely untapped despite their versatility in teaching a wide range of concepts and topics while simultaneously serving as an engaging and active learning methodology. This study details the creation of a collection of 130 stickers depicting chemical elements of the periodic table and explores their use as an innovative resource in science education. The product was tested with 64 third-year university students as well as 20 high school students. Participants were divided into two main groups: 4 university subgroups of 16 students each and 4 high school subgroups of 5 students each. Each subgroup was provided with an album and given 5 weeks to complete it under different sets of instructions. In the university context, the activity emphasized collaboration and teamwork while reinforcing the periodic table of studies in the previous academic year. For the high school students, the cards served as a pedagogical tool to enhance motivation and encourage task completion, both in class and as homework. After the five-week period, all four university subgroups successfully completed their albums within the allotted time. Among the high school participants, three of four subgroups achieved satisfactory results. One of these subgroups completed the album a week early, while two others came close to finishing their albums. The results demonstrate a high level of engagement among participants, who were motivated to earn cards through various activities. This suggests that collectible sticker cards represent a promising educational resource for prospective educators, offering an innovative and effective methodology to enhance learning outcomes. Collectable ; Table (database) ; Teamwork ; Class (philosophy) ; Product (mathematics) ; Task (project management) Various Chemistry Research Topics ; Science Education and Pedagogy ; History and advancements in chemistry
Authors: Hu Chen | Qiwu Luo | Mingrui Li | Chunhua Yang | Weihua Gui
Source: Measurement (article, 2025-11-29)
Field: Chemistry — Spectroscopy

Residual oxygen detection in pharmaceutical glass vials based on harmonic slope consistency Residual ; SIGNAL (programming language) ; Harmonic ; Repeatability ; Stability (learning theory) ; Consistency (knowledge bases) ; Computation ; Harmonic balance Spectroscopy and Laser Applications ; Laser-induced spectroscopy and plasma ; Spectroscopy and Chemometric Analyses
Authors: D Yue | Chaozhi Xiong | Zhen‐Wu Shao | Chong Liu
Source: Symmetry (article, 2025-06-06)
Field: Chemistry — Inorganic Chemistry

Construction of a Symmetrical Bi-Hydroxamate Metal–Organic Framework with Chemical Robustness Recently, the emerging class of hydroxamate-based metal–organic frameworks (MOFs) has demonstrated significant structural diversity and chemical robustness, both essential for potential applications. Combining the favorable hard–hard Bi-O interactions and chelating chemistry of hydroxamate groups, a rigid and symmetrical three-dimensional bismuth-hydroxamate metal–organic framework was successfully prepared via solvothermal synthesis and structurally elucidated via X-ray crystallography. The MOF, namely SUM-91 (SUM = Sichuan University Materials), features one-dimensional Bi-oxo secondary building blocks (SBUs), which are bridged by chelating 1,4-benzenedihydroxamate linkers. With the demonstrated permanent porosity and molecular sieving effect (CO2 vs. N2), SUM-91 was also found to be stable under harsh chemical conditions (aqueous solutions with pH = 2–12 and various organic solvents). As the structural robustness of SUM-91 could be attributed to the finetuning of the coordinative sphere of Bi centers, this work shed light on the further development of (ultra-)microporous materials with high stability and selective adsorption properties. Robustness (evolution) ; Metal ; Computer science ; Chemistry ; Organic chemistry ; Biochemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Zeolite Catalysis and Synthesis
Authors: Wladislaw Pisetsky | Thomas J. J. Müller
Source: Catalysts (article, 2025-01-08)
Field: Chemistry — Organic Chemistry

Recent Advances in the Synthesis of Substituted Polyacetylenes Recent developments in the synthesis of substituted polyacetylenes have considerably benefitted from advancements in organometallic catalysis; however, most important developments rely on the advent of Rh-catalyzed living polymerizations. The latter not only allow the tailoring of well-defined degrees of polymerization with low and narrow polydispersity but also enable access to stereochemical well-defined cis-transoidal polymers with a helical structure. These novel polymers open new avenues for application in photonics and electronics. Rh-catalyzed living polymerizations are mild and concise metal-catalyzed polymer syntheses that not only allow for the decoration of sidechains with multiple functionalities, including chiral units, but also enable enantioselective induction of helical chirality, memory of chirality, well-defined copolymerization, and end-group functionalization at both termini. This review summarizes recent developments in metal-catalyzed syntheses of substituted polyacetylenes, with a special focus on Rh-catalyzed living polymerizations. Chemistry Synthesis and Properties of Aromatic Compounds ; Synthesis of Indole Derivatives ; Organic Chemistry Cycloaddition Reactions
Authors: Zixuan Xue | Chaofan Yin | Yuechao YAO | Yanmin Wang | Yueyue Sun | Zhengrong Liu | Yinong Zhou | Jun Zhou | Kai Wu
Source: Journal of Inorganic Materials (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Research Progress on Proton-conducting Solid Oxide Fuel Cells with Hydrogen-containing Fuel Driven by global energy transition and carbon neutrality goals, Proton-conducting Solid Oxide Fuel Cells (P-SOFCs) have become a research hotspot in clean energy technology due to their advantages of efficient medium-to-low temperature power generation (400-600 ), excellent fuel compatibility, and high energy conversion efficiency.This review analyzes the development prospects of hydrogencontaining fuel P-SOFCs.Addressing key technological bottlenecks, this review focuses on three core dimensions including material design, reaction mechanisms, and characterization techniques to summarize research progress and technical challenges in hydrocarbon-fueled and ammonia-fueled P-SOFCs systems.For hydrocarbon-fueled P-SOFCs, the carbon deposition issue is thoroughly examined.The formation mechanisms, characterization methods, and influencing factors on carbon deposition are discussed in depth.Advanced improvement strategies are highlighted, including modification of reforming catalysts, optimization of proton-conducting electrolytes, and novel design of electrodes.Regarding direct ammonia fuel cells (DAFCs), challenges related to insufficient anode durability are addressed.Critical influencing factors are identified as catalyst activity, support types, nitridation corrosion mechanisms, hydrogen partial pressure, ammonia flow rate, and anode microstructure.Based on cutting-edge research, novel improvement strategies, such as anode modification, optimization of anode catalytic layers, and innovative cell structure designs, are summarized.This review outlines future development directions to advance the commercialization of hydrogen-containing fuel P-SOFCs. Materials science ; Fuel cells ; Hydrogen fuel ; Oxide ; Hydrogen ; Solid oxide fuel cell ; Proton ; Chemical engineering ; Metallurgy ; Physical chemistry ; Organic chemistry ; Nuclear physics ; Anode Advancements in Solid Oxide Fuel Cells
Authors: Keshav Basnet | Basanta Kumar Neupane
Source: Journal of Nepal Chemical Society (article, 2025-08-18)
Field: Materials Science — Materials Chemistry

Quantum Chemical Exploration of Carbonofluoridic Acid's Structural, Electronic, and Spectroscopic Properties The structural and electronic properties of the title molecule were investigated using Density Functional Theory (DFT) at the B3LYP/6-311G++(d,p) level in Gaussian G09 W and GaussView. Geometrical optimization was performed to determine the most stable configuration, with total energy computations revealing the minimized energy state. The electronic properties were analyzed through HOMO-LUMO gap calculations, yielding a band gap of 8.68708 eV, indicating high kinetic stability and low reactivity. Global reactivity indices, including electrophilicity, hardness, and electronegativity, were evaluated to ascertain the chemical behavior of the molecule. Molecular Electrostatic Potential (MEP) analysis identified reactive sites, with oxygen atoms showing a negative potential for electrophilic attack, while hydrogen atoms exhibited a positive potential, favoring nucleophilic interactions. Frontier molecular orbitals were further explored using the Total, Partial, and Overlap Density of States (TDOS, PDOS, and OPDOS) to elucidate the charge distribution and orbital contributions. Electron Localization Function (ELF) and Localized Orbital Locator (LOL) analyses revealed the electron density distribution, highlighting regions of strong covalent interactions and localized bonding characteristics. A Reduced Density Gradient (RDG) was employed to visualize non-covalent interactions, indicating van der Waals interactions and steric effects. Fukui functions and dual descriptors were calculated to predict reactive sites and charge-transfer tendencies. Spectroscopic characterization via FT-IR and FT-Raman spectroscopy confirmed the key functional group vibrations. These insights contribute to the understanding of the reactivity and stability of the title molecule and its potential applications in materials science and biochemistry. Quantum chemical ; Materials science ; Chemistry ; Organic chemistry ; Molecule Porphyrin and Phthalocyanine Chemistry ; Inorganic and Organometallic Chemistry ; Chemical Thermodynamics and Molecular Structure
Authors: M. Morad | Magdy S. Abo Ghazala | M.G. El-Shaarawy | M. E. Gouda | T. Y. Elrasasi
Source: Discover Nano (article, 2025-10-29)
Field: Materials Science — Polymers and Plastics

Study the characterization and thermoelectrical properties of the polyvinyl alcohol / Polyaniline polymer blend thick films This study investigated the impact of the introduction of Polyaniline (PANi) on the structural, thermal stability, electrical, and thermoelectric properties of polyvinyl alcohol (PVA)<sub>1-x</sub> Polyaniline (PANi)<sub>x</sub> blend composites, (where x = 0, 10, 20, and 30 wt.%). The prepared blends were synthesized via the casting technique. The process of polymerizing polyaniline (PANi) was executed in a methodical and ordered manner. The obtained films from these blends are analyzed to assess their surface characteristics and structural morphology through elemental analysis, scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR), as well as their thermal properties via thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The PVA hydrogen bonding facilitates the uniform dispersion of PANi among the chains of PVA, which increases the amorphous structure of the prepared films. The surface of the pure PVA film is characterized by a smooth surface. However, a mixture of nanofibers with slightly white porous spongy morphology patches appeared in the PANi-doped films. Furthermore, the incorporation of PANi into the PVA matrix improves the thermal stability of the prepared films. The impact of PANi on the electrical properties, Seebeck Coefficient, and thermal conductivity of the prepared composites is evaluated using the four-probe direct technique and laser flash measurements. SEM images reveal a heterogeneous distribution of conductive PANi particles within the continuous PVA matrix. A notable aspect of this investigation is the significant increment in the DC electrical conductivity of the blend films at room temperature, which increases from 2.08 × 10^<sup>-12</sup> S/m for the pure PVA film to 0.08 S/m for the film containing 30 wt.% PANi. The Seebeck Coefficient decreases with loading the PANi due to the increase in the charge carrier concentration. Concurrently, there was a slight enhancement in thermal conductivity, increasing from 0.1304 W m<sup>-1</sup> K<sup>-1</sup> to 0.362 W m⁻<sup>1</sup> K<sup>-1</sup> for the 0 wt.% and 30 wt.% films, respectively. The findings suggest a polymer blend with significant potential for thermoelectrical applications, exhibiting high electrical and low thermal conductivity, which is advantageous for thermoelectric applications. Polyaniline ; Thermogravimetric analysis ; Thermal stability ; Scanning electron microscope ; Differential scanning calorimetry ; Polyvinyl alcohol ; Polymer blend ; Conductive polymer Conducting polymers and applications ; Polymer Nanocomposite Synthesis and Irradiation ; Advanced Sensor and Energy Harvesting Materials
Authors: Juan Du | Kaiyin Xiao | Dongyu Li | Kaifan Du | Zebei Mao | Tong Li | Hao Peng
Source: Research Square (preprint, 2025-09-01)
Field: Materials Science — Materials Chemistry

Molecular mechanism of h-BN enhancing the thermal conductivity of PEEK Peek ; Mechanism (biology) ; Thermal conductivity ; Materials science ; Composite material ; Polymer ; Physics Thermal properties of materials ; Graphene research and applications ; Fuel Cells and Related Materials