jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Max W. Shen | Ewa Nowara | Michael Maser | Kyunghyun Cho
Source: ArXiv.org (preprint, 2025-12-02)
Field: Materials Science — Materials Chemistry

Training Dynamics of Learning 3D-Rotational Equivariance While data augmentation is widely used to train symmetry-agnostic models, it remains unclear how quickly and effectively they learn to respect symmetries. We investigate this by deriving a principled measure of equivariance error that, for convex losses, calculates the percent of total loss attributable to imperfections in learned symmetry. We focus our empirical investigation to 3D-rotation equivariance on high-dimensional molecular tasks (flow matching, force field prediction, denoising voxels) and find that models reduce equivariance error quickly to $\leq$2\% held-out loss within 1k-10k training steps, a result robust to model and dataset size. This happens because learning 3D-rotational equivariance is an easier learning task, with a smoother and better-conditioned loss landscape, than the main prediction task. For 3D rotations, the loss penalty for non-equivariant models is small throughout training, so they may achieve lower test loss than equivariant models per GPU-hour unless the equivariant ``efficiency gap'' is narrowed. We also experimentally and theoretically investigate the relationships between relative equivariance error, learning gradients, and model parameters. Equivariant map ; Focus (optics) ; Training (meteorology) ; Measure (data warehouse) ; Field (mathematics) ; Mean squared prediction error ; Reduction (mathematics) ; Training set Machine Learning in Materials Science ; Generative Adversarial Networks and Image Synthesis ; Domain Adaptation and Few-Shot Learning
Authors: Luiz D. Silva Neto | Rodolfo J. Brandão | Thais Logetto Caetité Gomes | LUCAS MEILI | José Teixeira Freire
Source: ACS Omega (article, 2025-12-20)
Field: Materials Science — Materials Chemistry

Mathematical Modeling of LDH Nanoparticle Drying: Evaluating Effective Diffusivity and the Role of the Mass Biot Number Layered Double Hydroxides (LDH) are an important class of inorganic nanomaterials characterized by variable composition, high porosity, significant surface area, and notable ion-exchange capacity. Although coprecipitation is the most widely used synthesis method, the subsequent drying step is often critically overlooked, as it directly affects particle agglomeration and degradation of the porous colloidal structure. This study evaluated the influence of the drying process on MgAl-CO<sub>3</sub>/LDH synthesis by determining the effective diffusivity (<i>D</i> <sub>eff</sub>) and activation energy (<i>E</i> <sub>a</sub>). LDHs were synthesized via coprecipitation (Mg/Al ratio = 2:1). Drying kinetics were investigated at 75, 90, and 105 °C, both without and with forced-air convection (1.0 ± 0.1 m/s). Diffusivity coefficients were determined using Fick's second law. A two-parameter diffusion model, including the mass Biot number (<i>Bi</i> <sub>m</sub>), provided a superior fit to the experimental data compared with the one-parameter model, corroborating the strong influence of external drying conditions. <i>D</i> <sub>eff</sub> values ranged from a maximum of 4.00 × 10<sup>-7</sup> m<sup>2</sup>/s (at 105 °C with convection, <i>Bi</i> <sub>m</sub> = 0.01) to a minimum of 3.40 × 10<sup>-10</sup> m<sup>2</sup>/s (at 75 °C without convection). The average activation energy ranged from 12.55 to 26.80 kJ/mol, suggesting that the superficial diffusion of liquid molecules along capillary surfaces is the rate-limiting mass-transfer mechanism. These results establish a quantitative basis for optimizing LDH drying parameters. They can serve as a starting point for other drying systems, such as fluidized-bed, rotary, spray, and freeze-dryers. Thermal diffusivity ; Coprecipitation ; Biot number ; Diffusion ; Particle size ; Particle (ecology) ; Activation energy ; Nanoparticle Layered Double Hydroxides Synthesis and Applications ; Magnesium Oxide Properties and Applications ; Aerogels and thermal insulation
Authors: Xi Zhou | Nan Chao | Caishan Jiao | Yang Gao | Chunhui Li | Y. Zhang
Source: Nuclear Engineering and Design (article, 2025-07-31)
Field: Materials Science — Materials Chemistry

Diffusion of solid fission products in UO2 and UO2+x Diffusion ; Materials science ; Fission products ; Nuclear engineering ; Fission ; Nuclear physics ; Nuclear fission product ; Long-lived fission product ; Radiochemistry ; Fission product yield ; Thermodynamics ; Engineering ; Neutron ; Chemistry ; Physics Nuclear Materials and Properties ; Radioactive element chemistry and processing ; Nuclear reactor physics and engineering
Authors: Nian Ran | Yue Wang | Zhang, Xiaoyuan | Li, Zhongzheng | Ran, Qingsong | Li, Wenhao | Allmendinger, Richard
Source: ArXiv.org (preprint, 2025-02-18)
Field: Materials Science — Materials Chemistry

ExLLM: Experience-Enhanced LLM Optimization for Molecular Design and Beyond Molecular design involves an enormous and irregular search space, where traditional optimizers such as Bayesian optimization, genetic algorithms, and generative models struggle to leverage expert knowledge or handle complex feedback. Recently, LLMs have been used as optimizers, achieving promising results on benchmarks such as PMO. However, existing approaches rely only on prompting or extra training, without mechanisms to handle complex feedback or maintain scalable memory. In particular, the common practice of appending or summarizing experiences at every query leads to redundancy, degraded exploration, and ultimately poor final outcomes under large-scale iterative search. We introduce ExLLM (Experience-Enhanced LLM optimization), an LLM-as-optimizer framework with three components: (1) a compact, evolving experience snippet tailored to large discrete spaces that distills non-redundant cues and improves convergence at low cost; (2) a simple yet effective k-offspring scheme that widens exploration per call and reduces orchestration cost; and (3) a lightweight feedback adapter that normalizes objectives for selection while formatting constraints and expert hints for iteration. ExLLM sets new state-of-the-art results on PMO and generalizes strongly in our setup, it sets records on circle packing and stellarator design, and yields consistent gains across additional domains requiring only a task-description template and evaluation functions to transfer. Computer science ; Natural language processing Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Ziling Zhou (9521822) | Zhengzhe Qu (22196092) | Mengjie Wu (311329) | Yu Wang (12152) | Jianzhu Cao (22196095) | Jiejuan Tong (13926936) | Yanwei Wen (1567159) | Bin Shan (303309) | Feng Xie (149450)
Source: Figshare (article, 2025-09-08)
Field: Materials Science — Materials Chemistry

Strong Trapping Capabilityand Diffusion SuppressionEffect of Silicon Carbide Surface on Tritium: A First Principle Study Silicon carbide (SiC) has attracted considerable interest for use in electronics, aerospace, and nuclear energy applications owing to its excellent electrical and mechanical properties. In the nuclear industry, SiC serves as an effective tritium permeation barrier. However, a significant discrepancy remains between the experimentally measured diffusion coefficients and the theoretical predictions. In addition, a steep tritium concentration gradient exists near the surface, whereas the concentration remains nearly uniform through the bulk, a phenomenon that is not yet fully understood. In this study, first-principles calculations were performed to investigate the influences of vacancies, grain boundaries, and surfaces on tritium diffusion in 3C-SiC. Vacancies and grain boundaries were found to have a negligible impact on the effective diffusion coefficient. In contrast, the surface exhibited a high diffusion barrier, demonstrating a strong tritium-trapping behavior. Incorporation of the surface effect into a multilayer diffusion model resulted in good agreement between the theoretical predictions and the experimental results, while also explaining the observed steep concentration gradient near the surface. These findings enhance the fundamental understanding of the tritium behavior in SiC and provide theoretical guidance for the design of high-performance tritium permeation barrier materials. Silicon carbide ; Diffusion ; Trapping ; Permeation ; Tritium ; Silicon ; Grain boundary ; Carbide ; Surface diffusion Fusion materials and technologies ; Silicon Carbide Semiconductor Technologies ; Advanced ceramic materials synthesis
Authors: Manar B. Hasan | Suha Anwer Ibrahim | Nisreen Mizher Rahmah | Thekra Atta Ibrahim | Alaa H. Alminshid | Mohammed Nsaif Abbas
Source: Results in Engineering (article, 2025-06-18)
Field: Chemistry — Inorganic Chemistry

Vanadium remediation from polluted wastewater using a novel non-conventional adsorbent • A non-conventional low-cost adsorbent was synthesized, achieving 81% recovery of vanadium • The adsorption isotherm followed the Langmuir model with a correlation coefficient of 0.992. • The adsorption kinetics were best described by the intraparticle diffusion model with a correlation coefficient of 0.9907. • Morphological characterization of the adsorbent indicated that the buckthorn leaves contained multiple functional groups that contributed effectively to the capture of vanadium ions • The results indicate promising scalability This investigation studies the utilization of buckthorn leaves as a low-cost and environmentally friendly adsorbent to remove vanadium from simulated wastewater. Experiments were conducted using batches under various operating conditions. The obtained results indicated that the vanadium recovery efficiency reached 81% and was in direct proportion to the pH, agitation speed, and contact time, and inversely with other variables, while adsorption capacity reaching 0.1 mg/g. The optimum conditions for vanadium removal using this novel adsorbent are 150 min, 12 g, 8.0 mg/L, 350 rpm, and 6 for contact time, adsorbent dosage, initial vanadium concentration, agitation speed, and pH, respectively, and 25°C, while maintaining stable performance overall experiments. Morphological characterization of the material indicated that the buckthorn leaves contained multiple functional groups that contributed effectively to the capture of vanadium ions from the contaminated solution, according to Fourier transform infrared spectroscopy (FT-IR) analysis. Field Emission Scanning Electron Microscopy (FESEM) examination revealed that the adsorption medium underwent significant changes due to the accumulation of target metal particles, and that the surface area decreased from 13.3 to 1.275 m²/g as a result of adsorption, according to the results obtained from the Brunauer, Emmett and Teller (BET)test. The results showed that the adsorption was spontaneous in the temperature range studied, that it had a negative entropy of 438 J/mol.K, and that it was exothermic with an enthalpy of 142.7 kJ/mol, which means that the adsorption is chemisorption. Kinetically the closest model to describing the adsorption was the intra-particle diffusion model, while Langmuir was the best model for representative of the obtained data isothermally compared to the other models, according to the correlation coefficients, which were 0.9907, 0.992, respectively. Environmental remediation ; Wastewater ; Vanadium ; Adsorption ; Environmental science ; Waste management ; Chemistry ; Materials science ; Contamination ; Environmental engineering ; Metallurgy ; Engineering Vanadium and Halogenation Chemistry ; Fluoride Effects and Removal ; Mercury impact and mitigation studies
Authors: Ziling Zhou | Zhengzhe Qu | Mengjie Wu | Yu Wang | Jianzhu Cao | Jiejuan Tong | Yanwei Wen | Bin Shan | Feng Xie
Source: ACS Applied Materials & Interfaces (article, 2025-09-08)
Field: Materials Science — Materials Chemistry

Strong Trapping Capability and Diffusion Suppression Effect of Silicon Carbide Surface on Tritium: A First Principle Study Silicon carbide (SiC) has attracted considerable interest for use in electronics, aerospace, and nuclear energy applications owing to its excellent electrical and mechanical properties. In the nuclear industry, SiC serves as an effective tritium permeation barrier. However, a significant discrepancy remains between the experimentally measured diffusion coefficients and the theoretical predictions. In addition, a steep tritium concentration gradient exists near the surface, whereas the concentration remains nearly uniform through the bulk, a phenomenon that is not yet fully understood. In this study, first-principles calculations were performed to investigate the influences of vacancies, grain boundaries, and surfaces on tritium diffusion in 3C-SiC. Vacancies and grain boundaries were found to have a negligible impact on the effective diffusion coefficient. In contrast, the surface exhibited a high diffusion barrier, demonstrating a strong tritium-trapping behavior. Incorporation of the surface effect into a multilayer diffusion model resulted in good agreement between the theoretical predictions and the experimental results, while also explaining the observed steep concentration gradient near the surface. These findings enhance the fundamental understanding of the tritium behavior in SiC and provide theoretical guidance for the design of high-performance tritium permeation barrier materials. Silicon carbide ; Diffusion ; Permeation ; Trapping ; Tritium ; Silicon ; Carbide ; Grain boundary ; Potential gradient Fusion materials and technologies ; Muon and positron interactions and applications ; Plasma Diagnostics and Applications
Authors: Akihisa Miyagawa | Shinya Watanabe | Shigenori Nagatomo | Kiyoharu Nakatani
Source: Bulletin of the Chemical Society of Japan (article, 2025-04-30)
Field: Chemistry — Spectroscopy

Coumarin-derivatives diffusion in single octadecylsilyl-functionalized silica particle observed by fluorescence correlation spectroscopy Abstract The analysis of intraparticle diffusion mechanisms provides crucial insights into chromatographic separation. In the present study, we investigated the intraparticle diffusion mechanisms of coumarin derivatives within single octadecylsilyl-functionalized (ODS) silica particle in acetonitrile (ACN)/water solutions using fluorescence correlation spectroscopy (FCS). Intraparticle diffusion coefficients (D) were determined in solutions including 0, 30, 40, 50, and 100 vol% ACN. The obtained D values were analyzed based on the pore and surface diffusion model. Diffusion species with coefficients on the order of 10−7 cm2 s−1 at 30 to 100 vol% ACN were attributed to pore diffusion without adsorption/desorption processes. In contrast, slower diffusion species with coefficients on the order of 10−8 cm2 s−1 were attributed to surface diffusion. These results elucidate the intraparticle diffusion mechanisms of coumarin derivatives in ODS silica particle as observed by FCS. We anticipate that this method will become a standard approach for clarifying intraparticle diffusion phenomena and will provide valuable insights into chromatography, drug delivery, and catalysis. Chemistry ; Fluorescence correlation spectroscopy ; Fluorescence ; Particle (ecology) ; Coumarin ; Diffusion ; Fluorescence spectroscopy ; Spectroscopy ; Organic chemistry ; Analytical Chemistry (journal) ; Molecule ; Thermodynamics ; Optics Analytical Chemistry and Chromatography ; Mesoporous Materials and Catalysis ; Advanced Chemical Sensor Technologies
Authors: M. Xochitl Aguilar-Pujol | Isabel C. Arango | Eoin Dolan | You Ba | Marco Gobbi | Luis E. Hueso | Fèlix Casanova
Source: ArXiv.org (preprint, 2025-06-06)
Field: Materials Science — Materials Chemistry

Orbital Hall conductivity and orbital diffusion length of Vanadium thin films by Hanle magnetoresistance In spintronics, the spin Hall effect has been widely used to generate and detect spin currents in materials with strong spin-orbit coupling such as Pt and Ta. Recently, its orbital counterpart has drawn attention as a new tool to generate and detect orbital currents and thus investigate orbital transport parameters. In this study, we investigate vanadium (V), a $3d$ transition metal with weak spin-orbit coupling but with a theoretically large orbital Hall conductivity. We measure a large Hanle magnetoresistance in V thin films with a magnitude comparable to that of heavy metals and at least one order of magnitude higher than the spin Hall magnetoresistance observed in a Y$_3$Fe$_5$O$_{12}$/V bilayer, pointing to the orbital Hall origin of the effect. A fit of the magnetic-field dependence and thickness dependence of the Hanle magnetoresistance to the standard diffusion model allows us to quantify the orbital diffusion length (~2 nm) and the orbital Hall conductivity (~78 ($\hbar/2e$) $Ω^{-1}$cm$^{-1}$) of V. The obtained orbital Hall conductivity is two orders of magnitude smaller than theoretical calculations of the intrinsic value, suggesting there is an important role of disorder. Magnetoresistance ; Hall effect ; Spin (aerodynamics) ; Coupling (piping) ; Spin Hall effect ; Conductivity ; Electrical resistivity and conductivity ; Diffusion Chemical and Physical Properties of Materials ; Magnetic properties of thin films ; Topological Materials and Phenomena
Authors: Dong Li | Hanbo Li | Chen Fengjuan | Liu JIN
Source: SSRN Electronic Journal (preprint, 2025-01-01)
Field: Materials Science — Materials Chemistry

SRIM - Based Simulation and Characterization of Helium Ion Implantation-Induced Irradiation Damage in Concrete Irradiation ; Helium ; Radiation damage ; Nucleation ; Characterization (materials science) ; Microstructure ; Ion Nuclear materials and radiation effects ; Concrete and Cement Materials Research ; Fusion materials and technologies
Authors: Daniel Glückman (21168123) | Francesca Quinto (1957012) | Claudia Joseph (6866063) | Volker Metz (21168126) | Karin Hain (10111284) | Peter Steier (254409) | Horst Geckeis (1407064)
Source: Figshare (article, 2025-04-23)
Field: Chemistry — Inorganic Chemistry

Diffusion of U(VI)in Opalinus Clay Studied down toUltratrace Levels Natural clay rocks, such as Opalinus Clay (OPA), are considered as potential host rocks for the disposal of high-level nuclear waste due to their ability to limit radionuclide transport to molecular diffusion. Laboratory studies related to the investigation of radionuclide diffusion behavior are usually performed at relatively high concentrations. For instance, U diffusion in clay rocks has been investigated at concentrations as low as approximately 10<sup>–4</sup> mol·m<sup>–3</sup> clay. This study addresses <sup>233</sup>U(VI) diffusion in OPA down to ultratrace concentrations of 10<sup>–9</sup> mol·m<sup>–3</sup> using accelerator mass spectrometry. Fitting of the experimental data with a one-dimensional pore diffusion model revealed no significant changes in the U(VI) effective diffusion coefficient (<i>D</i><sub>e</sub>) over the investigated concentration range of 10<sup>–3</sup> to 10<sup>–9</sup> mol·m<sup>–3</sup>. Such concentration-independent behavior constitutes valuable information for the prediction of long-term U(VI) migration in geological repositories with OPA as host rock. Diffusion ; Radionuclide ; Radioactive waste ; Range (aeronautics) ; Waste disposal ; Effective diffusion coefficient ; Accelerator mass spectrometry Radioactive element chemistry and processing ; Radioactive contamination and transfer ; Soil and Unsaturated Flow
Authors: Sterley Labady | Youssef Mesri | Daniel Pino Muñoz | Baptiste Flipon | Marc Bernacki‫
Source: ArXiv.org (article, 2025-12-19)
Field: Materials Science — Materials Chemistry

InfinityEBSD : Metrics-Guided Infinite-Size EBSD Map Generation With Diffusion Models Materials performance is deeply linked to their microstructures, which govern key properties such as strength, durability, and fatigue resistance. EBSD is a major technique for characterizing these microstructures, but acquiring large and statistically representative EBSD maps remains slow, costly, and often limited to small regions. In this work, we introduce InfinityEBSD, a diffusion-based method for generating monophase realistic EBSD maps of arbitrary size, conditioned on physically meaningful microstructural metrics. This approach supports two primary use cases: extending small experimental EBSD maps to arbitrary sizes, and generating entirely new maps directly from statistical descriptors, without any input map. Conditioning is achieved through eight microstructural descriptors, including grain size, grain perimeter, grain inertia ratio, coordination number and disorientation angle distribution, allowing the model to generate maps that are both visually realistic and physically interpretable. A patch-wise geometric extension strategy ensures spatial continuity across grains, enabling the model to produce large-scale EBSD maps while maintaining coherent grain boundaries and orientation transitions. The generated maps can also be exported as valid Channel Text Files (CTF) for immediate post-processing and analysis in software such as MTEX or simulation environments like DIGIMU. We quantitatively validate our results by comparing distributions of the guiding metrics before and after generation, showing that the model respects the statistical targets while introducing morphological diversity. InfinityEBSD demonstrates that diffusion models, guided by physical metrics, can bridge the gap between synthetic and realistic materials representation, paving the way for future developments such as 3D realistic microstructure generation from 2D data. Electron backscatter diffraction ; Orientation (vector space) ; Grain boundary ; Diffusion ; Key (lock) ; Software ; Channel (broadcasting) Machine Learning in Materials Science ; Block Copolymer Self-Assembly ; Model Reduction and Neural Networks