jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: A. Dash
Source:  (preprint, 2025-01-10)
Field: Materials Science — Surfaces, Coatings and Films

Energy Efficiency Improvement in Cryogenic Electron Microscopy: Strategies to Mitigate Foul Emissions Electron microscope ; Environmental science ; Materials science ; Engineering physics ; Energy (signal processing) ; Electron ; Efficient energy use ; Cryogenic temperature ; Nanotechnology ; Nuclear engineering ; Physics ; Nuclear physics ; Engineering ; Electrical engineering ; Optics ; Composite material Electron and X-Ray Spectroscopy Techniques ; nanoparticles nucleation surface interactions
Authors: Qiuyu Zeng | Jun Xie | Jinbo Zhu | Jianqiang Yin | Wenliang Zhu
Source: Minerals (article, 2025-05-20)
Field: Materials Science — Biomaterials

Structural Distortion and Optoelectronic Signatures in Metal-Substituted Kaolinite: A First-Principles Investigation This study employs density functional theory (DFT) simulations to systematically investigate the structural and optoelectronic modifications induced by the substitution of metal ions (Mg2+, Ca2+, Mn2+, Fe2+/3+, Co2+, and Ni2+) in kaolinite. First-principles calculations reveal distinct substitution behaviors: Na-Ni (II)-1 exhibits the lowest cell energy, indicating superior structural stability, while Na-Mn (II)-1 demonstrates the most favorable substitution energy (−5.44 eV). XRD simulations of divalent substitutions show a positive correlation between atomic number and diffraction intensity at 8.778° and 9.774°, suggesting a spectral marker for substitution detection. Electronic structure analysis identifies significant bandgap reduction, with Na-Fe (II)-4 achieving an ultranarrow gap of 1.014 eV, attributed to spin-polarized d-orbital contributions. X-ray absorption fine-structure (XAFS) simulations further reveal metal-specific bond elongation, with Fe3+ substitutions preserving near-pristine coordination distances. These findings establish a comprehensive framework linking metal substitution to structural distortion and optoelectronic response, providing theoretical insights for optimizing kaolinite-based material properties through computational feature extraction. Kaolinite ; Distortion (music) ; Metal ; Materials science ; Optoelectronics ; Metallurgy Clay minerals and soil interactions ; Geochemistry and Geologic Mapping ; Mineralogy and Gemology Studies
Authors: Niksoney Azevedo Mendonça | Marise Helen Vale de Oliveira | Thaís Elias Almeida
Source:  (preprint, 2025-01-13)
Field: Chemistry — Analytical Chemistry

Spectral signatures as evidence to test hypotheses in plant species complexes Traditional methods for species definition, based on macromorphological characteristics, face limitations due to the high phenotypic plasticity observed in plants, which makes it challenging to accurately identify species complexes. Fourier transform near-infrared spectroscopy emerges as a promising, non-destructive technique for analyzing plant material, enabling the distinction of species. This study focuses on the Scaly clade of the fern genus Microgramma, characterized by complex taxonomic boundaries and morphological variations. A total of 94 samples from eight species, including fertile and sterile leaves of dimorphic and monomorphic species, were evaluated to test the effectiveness of FT-NIR in distinguishing these lineages. The average identification accuracy ranged from 86% to 91%, depending on the models and validation employed. Species with better-defined morphological characteristics, such as Microgramma percussa, achieved an accuracy of 100%. Conversely, species with higher morphological overlap showed lower accuracy, which may be associated with hybridization, introgression, or cryptic variation. Dimorphic species, with morphologically distinct fertile and sterile fronds, exhibited higher intraspecific spectral variation compared to monomorphic species, which may explain their lower accuracy rates. Fertile fronds, in some cases, provided more informative data, possibly due to the presence of sori increasing the complexity of spectra. This study highlights the potential of FT-NIR as a complementary tool in plant systematics. However, further research is needed to understand the influence of processes such as hybridization and features such as the indumentum on spectral readings. Overall, FT-NIR presents itself as a promising method to elucidate species limits in ferns and improve knowledge about their diversity. Test (biology) ; Econometrics ; Computer science ; Environmental science ; Mathematics ; Geology ; Paleontology Spectroscopy and Chemometric Analyses
Authors: Patrice Bras | Mario Maglione | Mohamed AMMARI | Brandon Faceira | Christine Kui | Ambreen Khan | Lionel Teulé‐Gay | Aline Rougier
Source: Journal of The Electrochemical Society (article, 2025-10-01)
Field: Materials Science — Polymers and Plastics

CV Shape as a Tool for Predicting Memory Effect in WO <sub>3</sub> Sputtered Electrochromic Films WO 3 films are among the most investigated materials for electrical tuning of optical properties, the so-called electrochromic effect. Of particular interest for applications of these films is the recently tuned memory effect, which allows persistence of an induced optical state after interruption of the applied potential. By comparing two process routes for amorphous WO 3 film synthesis, we show that the memory effect is a general feature, which opens the way for further investigation of this interesting property. We propose an empirical relationship between the shape of the cyclic voltammetry curves measured on these films and the occurrence of the memory effect. This is a decisive step towards accelerating the development of devices based on these films using the CV shape as a predictive tool. Finally, preliminary understanding of the origin of the memory effect is discussed through morphological characterizations of the WO 3 sputtered films. Electrochromism ; Amorphous solid ; Shape-memory alloy ; Cyclic voltammetry ; Electrochromic devices ; Thin film ; Non-volatile memory Transition Metal Oxide Nanomaterials ; Advanced Memory and Neural Computing ; Gas Sensing Nanomaterials and Sensors
Authors: Aleksandra Pashtetskaia | Alexandra Kravtsova | Alexandra Peshkova | Inga Zinicovscaia | О. М. Шевчук
Source: Plants (article, 2025-11-22)
Field: Chemistry — Organic Chemistry

Mineral Composition of Olea europaea L. Leaves and Tisanes The study aimed to identify mineral determinants of potential therapeutic effects of <i>Olea europaea</i> L. leaves from introduced cultivars of the Southern Coast of Crimea and to assess their suitability for functional aqueous tisanes. Using ICP-OES, eighteen macro- and micro-elements were identified in dried leaves, with K and Ca predominant (>10.0 g/kg), followed by P, S, and Mg (>1.0 g/kg). Maximum values occurred in 'Nikitskaya' (K 15.6 g/kg; S 2.05 g/kg; and P 1.97 g/kg) and 'Tlemcen' (Ca 18.6 g/kg and Mg 1.46 g/kg). Extractability into infusion (2 g/100 mL, 60 min) reached 325 mg/L for K, 26 mg/L for Ca, 48 mg/L for S, 18 mg/L for P, and 9 mg/L for Mg. Potentially toxic elements were below detection limits, indicating the safety of both the raw material and beverage. Principal component, correlation, and Ward clustering analyses highlighted 'Nikitskaya', 'Lomashenskaya', and 'Coregiolo' as having the highest cumulative mineral value among the tested six cultivars. Overall, the findings support the feasibility of olive-leaf tisanes as accessible sources of K, Ca, S, P, and Mg, with potential contributions to antioxidant defense, blood-pressure regulation, and lipid and carbohydrate metabolism. Olea ; Cultivar ; Mineral ; Antioxidant ; Aqueous extract ; Chemical composition Edible Oils Quality and Analysis ; Nuts composition and effects ; Essential Oils and Antimicrobial Activity
Authors: Robbin Steentjes | Egbert Zojer
Source: Monatshefte für Chemie - Chemical Monthly (article, 2025-12-09)
Field: Materials Science — Materials Chemistry

The dynamics of stacking in layered covalent organic frameworks Abstract Polymeric porous materials have a variety of applications ranging from gas storage and catalysis to sensing. A particularly interesting class comprises covalent organic frameworks (COFs), which are often realized as materials consisting of 2D extended, covalently bonded layers stacked on top of each other. The stacking order in layered COFs (LCOFs) is typically not well defined, but impacts virtually all of their properties. In fact, recent studies suggest that stacking does not occur in a strictly periodic fashion. When modeling such disordered COF stacks, the focus so far has been on the static situation, as simulations of the layer-stacking dynamics have either been too expensive (using ab initio methods) or too inaccurate (using generic force fields). This situation has changed with the advent of system-specific, machine-learned potentials (MLPs). In the present contribution, it is described for the prototypical material COF-1, how to parametrize a machine-learned force field that is capable of accurately reproducing the key features of the DFT-calculated potential energy surface. This is possible, even though the energy differences between the local minima are only on the order of a few ten meV per unit cell. The obtained MLP is then used to demonstrate that in molecular dynamics simulations large enough supercells need to be chosen to avoid a massive overestimation of the tendency of layers to slip dynamically. Moreover, the dynamic stability of local minimum structures is tested and the highly anisotropic thermal expansion coefficients of COF-1 are predicted. The present study outlines a strategy that serves as a basis for future computational investigations of dynamical properties of layered materials. Graphical Abstract Stacking ; Maxima and minima ; Molecular dynamics ; Covalent bond ; Ab initio ; Force field (fiction) ; Potential energy ; Anisotropy Covalent Organic Framework Applications ; Machine Learning in Materials Science ; Supramolecular Chemistry and Complexes
Authors: Ms. Mamatha Mahalingappa | H P Akash | Kumar Akash | S Chethan | S Y Likhith
Source: IJARCCE (article, 2025-11-17)
Field: Materials Science — Polymers and Plastics

WEARABLE-BASED KINEMATIC ANALYSIS OF CRICKET BOWLING Kinematics ; Cricket Textile materials and evaluations ; Sports Dynamics and Biomechanics ; Mechanical and Thermal Properties Analysis
Authors: Mohamed AbdulHameed | Khadija Mahbuba | Mahmoud Yaseen | Amr F. M. Ibrahim | Daniel Moneghan | Benjamin Beeler
Source: ArXiv.org (preprint, 2025-08-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Modeling of silver transport in cubic SiC: Integrating molecular dynamics, bounds averaging, and uncertainty quantification Silver released from TRISO fuel particles can migrate through the SiC layer and deposit on reactor components, posing radiation hazards and operational challenges. Despite numerous proposed mechanisms, the precise pathway of silver transport through intact 3C-SiC remains unresolved. We present a physics-informed model for estimating the effective diffusivity of silver in polycrystalline 3C-SiC. Molecular dynamics (MD) simulations yield diffusivities for {Σ3} and {Σ9} grain boundaries (GBs), while literature values are used for other GB types and the bulk. These are combined using a bounds-averaging approach accounting for distinct GB transport properties. Bayesian inference of experimental data provides credible intervals for effective Arrhenius parameters and reveals a correlation between activation energy and pre-exponential factor. Although the homogenized model captures GB-mediated transport mechanisms, it overpredicts silver diffusivity relative to experiments. To resolve this, a multiplicative correction based on reversible trapping at nano-pores is introduced. It is derived from first principles and is shown to reproduce observed transport behavior. Sensitivity analysis identified trap desorption energy and {Σ9} GB diffusivity as dominant factors influencing Ag transport. The resulting framework provides a mechanistic description of Ag transport suitable for integration into higher-scale fuel performance models. Thermal diffusivity ; Multiplicative function ; Uncertainty quantification ; Bayesian inference ; Yield (engineering) ; Arrhenius equation ; Sensitivity (control systems) ; Diffusion ; Isothermal process ; Activation energy Copper Interconnects and Reliability ; Semiconductor materials and devices ; Silicon Carbide Semiconductor Technologies
Authors: Shuonan Wu | Yuchen Xie | Deng Pan | Lei Zhang | YuLiang JIN
Source: ArXiv.org (article, 2025-12-22)
Field: Materials Science — Materials Chemistry

Hierarchical and ultrametric barriers in the energy landscape of jammed granular matter According to the mean-field glass theory, the (free) energy landscape of disordered systems is hierarchical and ultrametric if they belong to the full-replica-symmetry-breaking universality class. However, examining this theoretical picture in three-dimensional systems remains challenging, where the energy barriers become finite. Here, we numerically explore the energy landscape of granular models near the jamming transition using a saddle dynamics algorithm to locate both local energy minima and saddles. The multi-scale distances and energy barriers between minima are characterized by two metrics, both of which exhibit signatures of an ultrametric space. The scale-free distribution of energy barriers reveals that the landscape is hierarchical. Ultrametric space ; Energy landscape ; Maxima and minima ; Universality (dynamical systems) ; Energy (signal processing) ; Saddle ; Saddle point Material Dynamics and Properties ; Theoretical and Computational Physics ; Nonlinear Photonic Systems
Authors: Fangping Yao | M. S. Joshi | Megan Bland-Rothgeb | Peter A. Cripton | Duane S. Cronin | John Magliaro
Source: Frontiers in Mechanical Engineering (article, 2025-12-09)
Field: Materials Science — Polymers and Plastics

Mechanical and material heterogeneity, strain localization and deformation rate effects in crushable expanded polystyrene foams Low-density expanded polystyrene (EPS) foams are widely used in lightweight energy absorption systems such as helmets due to their ability to readily mold into complex geometries. However, varying material flow and cooling rates during manufacturing produce exterior skin layers with substantially higher density and aspect ratio from the core, and the resultant mechanical properties have not been quantified. Previous studies assumed EPS foams were homogeneous, overlooking or intentionally removing the skin from test specimens and constrain their scopes to out-of-plane compression. In this study, closed-cell EPS foam pucks of 30, 50, 80, and 100 g/L were tested under in-and out-of-plane compression at loading rates spanning 0.001–10/s. Specimens were prepared with as molded and core (skin removed) configurations to quantify anisotropy from heterogeneity. Measurements revealed a 98% ± 8% higher density in the skin layers relative to nominal material density and cells skewed 41% ± 6% in the in-plane direction. As-molded specimens exhibited a 38% ± 4% higher plateau stress for in-plane loading compared to out-of-plane, highlighting foam cell elongation as a key strengthening mechanism. Quasi-orthotropic behavior was observed for the core foam material, which possessed more evenly sized cells. Digital image correlation quantified rate-dependent strain localization, providing novel evidence of internal pressure redistribution from viscous gas dynamics within the EPS beads, with 39% lower peak true strains, on average, measured at 10/s compared to 0.001/s. Unloading data also revealed progressive increases in post-crushing strain recovery, increasing an order of magnitude from 0.04 mm/mm to 0.42 mm/mm between 0.001-10/s for the 30 g/L group, confirming more even load distribution and cell fracture mitigation at elevated rates. Polystyrene ; Digital image correlation ; Expanded polystyrene ; Anisotropy ; Deformation (meteorology) ; Compression (physics) ; Strain rate ; Elongation ; Relative density Polymer Foaming and Composites ; Cellular and Composite Structures ; Elasticity and Material Modeling
Authors: Yucong Su | Yadong Yin
Source: National Science Review (article, 2025-05-15)
Field: Materials Science — Biomaterials

Thermochromic nacre-inspired structural material Thermochromism ; Materials science ; Polymer science ; Nanotechnology ; Chemistry ; Organic chemistry Calcium Carbonate Crystallization and Inhibition ; Paleontology and Stratigraphy of Fossils ; Bone Tissue Engineering Materials
Authors: Ostap Kutyansky | Yurii Rybak
Source: Measuring Equipment and Metrology (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

SYSTEMIZATION OF REQUIREMENTS FOR OPERATIONAL QUALITY CONTROL SYSTEMS OF MEAT PRODUCTS This paper presents a study on organizing requirements for automated meat quality control systems. It identifies key quality indicators–color, texture, marbling, and gloss–and analyzes the technical and functional parameters essential for practical assessment. The research highlights integrating computer vision, image processing, and machine learning algorithms to enhance objectivity, accuracy, and evaluation speed. The proposed approach aims to reduce human influence, enable real-time monitoring, and offer scalable solutions suitable for large-scale producers and small enterprises Computer science ; Scalability ; Quality (philosophy) ; Gloss (optics) ; Control (management) ; Key (lock) ; Marbled meat ; Risk analysis (engineering) ; Industrial engineering ; Artificial intelligence ; Database ; Engineering ; Computer security ; Business Spectroscopy and Chemometric Analyses ; Food Supply Chain Traceability
Authors: T. Dorigo | M. Doro | Max Aehle | Nicolas R. Gauger | Muhammad Awais | Rafael Izbicki | Jan Kieseler | Luca Masserano | Federico Nardi | Luis Vergara
Source: ArXiv.org (preprint, 2025-01-23)
Field: Materials Science — Materials Chemistry

On the Utility Function of Experiments in Fundamental Science The majority of experiments in fundamental science today are designed to be multi-purpose: their aim is not simply to measure a single physical quantity or process, but rather to enable increased precision in the measurement of a number of different observable quantities of a natural system, to extend the search for new phenomena, or to exclude a larger phase space of candidate theories. Most of the time, a combination of the above goals is pursued; this breadth of scope adds a layer of complexity to the already demanding task of designing the measurement apparatus in an optimal way, by defining suitable geometries and choosing the most advantageous materials and appropriate detection technologies. The precise definition of a global optimality criterion may then require experimentalists to find a consensus on the relative scientific worth of those goals. In this work, we discuss the problem of formulating a utility function for multipurpose experiments, as an enabling step to employ artificial intelligence tools to explore the design space and assist humans in finding solutions at the Pareto front. Computer science ; Scope (computer science) ; Task (project management) ; Function (biology) ; Measure (data warehouse) ; Process (computing) ; Space (punctuation) ; Observable ; Systems engineering ; Data mining ; Engineering Machine Learning in Materials Science ; Process Optimization and Integration
Authors: Javier Kipen | Matthew Beauregard Smith | Thomas Blom | Shengying Zhou | Edward M. Marcotte | Joakim Jaldén
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-07-14)
Field: Chemistry — Spectroscopy

Protein Abundance Inference via Expectation Maximization in Fluorosequencing Fluorosequencing produces millions of single-peptide reads, yet a principled strategy for converting these data into quantitative protein abundances has been lacking. We introduce a probabilistic framework that adapts expectation maximization to the fluorosequencing measurement process, estimating relative protein abundances with peptide inference results delivered by previously developed peptide-classification tools. The algorithm iteratively updates protein abundances, maximising the likelihood of the observed reads by obtaining more accurate protein abundance estimations. We first assess performance on simulated five-protein mixtures that reflect realistic labelling and system errors. A simple Python implementation processes one million reads in under ten seconds on a standard work-station and lowers the mean absolute error in relative abundance by more than an order of magnitude compared with a uniform-abundance guess, demonstrating robustness in protein inference for small-scale settings. Scalability is then evaluated with simulations of the complete human proteome (20 642 proteins). Ten million reads are processed in less than four hours on a NVIDIA DGX system using one Tesla V100 GPU, confirming that the method remains tractable at proteome scale. Using error rates characteristic of current fluorosequencing, the algorithm produces marginal improvements in relative abundance accuracy. However, when error rates were artificially lowered, estimation error decreased significantly. This result suggests that improvements in fluorosequencing chemistry could directly translate into substantially more accurate quantitative proteomics with this computational framework. Together, these results establish EM-based inference as a scalable model-driven bridge between peptide-level classification and protein-level quantification in fluorosequencing, laying computational groundwork for highthroughput single-molecule proteomics. Furthermore, the proposed protein inference framework can also be used as a refinement step within other inference methods, enhancing their protein abundance estimates. Inference ; Abundance (ecology) ; Maximization ; Econometrics ; Computer science ; Artificial intelligence ; Mathematics ; Psychology ; Biology ; Ecology ; Social psychology Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Genomics and Phylogenetic Studies
Authors: Hongjin Wu | Juan Dang | Xiaomeng Zhang | Weichen Yang | Shuai Tian | Shibo Zhang | Qingzhu Zhang | Wenxing Wang
Source:  (article, 2025-08-25)
Field: Materials Science — Materials Chemistry

Key Role of Nitrogen-containing Oxygenated Organic Molecules (OOMs) in SOA Formation Evidenced by OH/NO <sub>3</sub> -induced Terpinolene Oxidation Abstract. Oxygenated organic molecules (OOMs), generated from the oxidation of various biogenic volatile organics with diverse yields, are a great contributor to SOA formation. Terpinolene is an isomeride of limonene, with an even higher SOA yield. Herein we investigated the elaborate oxidation mechanism of terpinolene by OH and NO3, elucidating the new formation mechanism of OOMs and their yield profiles based on the newly-built zero-dimensional chemical model under three typical atmospheric conditions. For terpinolene oxidation by OH, H shift imposes restrictions on continuous autoxidation, instead by the reactions with HO2/NO/NO2 resulting in chain termination. For the reaction of terpinolene with NO3, the transfer of the radical center via bond breaking, triggering a new round of autoxidation, is newly found to be pivotal in the formation of nitrogen-containing OOMs with high yields. The effective saturation concentration (C*) of nitrogen-containing OOMs is mostly lower than the OOMs formed by OH oxidation, more easily distributed into particle phase. The estimated C* of the generated OOMs are distinctly varied among OOM isomers, which emphasizes the necessity of determining their molecular structures, peculiarly the number of rings. The comparative analysis of OH-initiated (daytime) and NO3-driven (nocturnal) terpinolene oxidation mechanism, highlighted the formation of nitrogen-containing OOMs, would be conducive to molecular structures identification of OOMs in atmospheric monitoring and atmospheric chemical model refinement. Key (lock) ; Nitrogen ; Chemistry ; Metal-organic framework ; Environmental chemistry ; Organic chemistry ; Computer science ; Operating system Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions