jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Denis D. Caprioti | Matheus Haas | Constantino Francisco Vasconcelos | Mauricio Girardi‐Schappo
Source: ArXiv.org (article, 2026-01-12)
Field: Materials Science — Materials Chemistry

Learning About Learning: A Physics Path from Spin Glasses to Artificial Intelligence The Hopfield model, originally inspired by spin-glass physics, occupies a central place at the intersection of statistical mechanics, neural networks, and modern artificial intelligence. Despite its conceptual simplicity and broad applicability -- from associative memory to near-optimal solutions of combinatorial optimization problems -- it is rarely integrated into standard undergraduate physics curricula. In this paper, we present the Hopfield model as a pedagogically rich framework that naturally unifies core topics from undergraduate statistical physics, dynamical systems, linear algebra, and computational methods. We provide a concise and illustrated theoretical introduction grounded in familiar physics concepts, analyze the model's energy function, dynamics, and pattern stability, and discuss practical aspects of simulation, including a freely available simulation code. To support instruction, we conclude with classroom-ready example problems designed to mirror research practice. By explicitly connecting fundamental physics to contemporary AI applications, this work aims to help prepare physics students to understand, apply, and critically engage with the computational tools increasingly central to research, industry, and society. Artificial neural network ; Intersection (aeronautics) ; Spin glass ; Content-addressable memory ; Simplicity ; Path (computing) ; Physicist ; Hopfield network Machine Learning in Materials Science ; Quantum many-body systems ; Quantum Computing Algorithms and Architecture
Authors: Junkang Li | Tristan Cazenave | Swann Legras | Arthur Queffelec | Véronique Ventos
Source: Proceedings of the AAAI Conference on Artificial Intelligence (article, 2026-03-14)
Field: Materials Science — Materials Chemistry

Nested Depth Search Nested Monte Carlo Search (NMCS) has numerous applications, ranging from chemical retrosynthesis to quantum circuit design. We propose a generalization of NMCS that we named Nested Depth Search (NDS), in which a fixed depth search is used during a higher-level playout to generate the states sent to lower-level exploration. We establish the runtime of NDS and provide algorithms to compute the exact probability distribution of sequences generated by NDS. Experiments with the Set Cover problem and the Multiple Sequence Alignment problem show that NDS outperforms NMCS with the same time budget. Generalization ; Cover (algebra) ; Set (abstract data type) ; Sequence (biology) ; Ranging ; Search algorithm ; Monte Carlo method ; Probability distribution Machine Learning in Materials Science ; Machine Learning and Algorithms ; Quantum Computing Algorithms and Architecture
Authors: Maria Suzana Oliveira da Silva | Natali Aparecida Santana | Valdinete Vieira Nunes | Matheus Emannuel Oliveira Vieira | Crislaine Costa Calazans | Daniela Aparecida de Castro Nizio | Renata Silva-Mann
Source: Genetic Resources and Crop Evolution (article, 2026-04-01)
Field: Chemistry — Organic Chemistry

Field-image endocarp phenotyping for provenance discrimination and traceability in Spondias tuberosa Abstract Understanding how fruit traits capture provenance structure is essential for traceability and the effective use of native fruit trees in conservation and pre-breeding. We assessed 30 mother trees of Spondias tuberosa (umbuzeiro) from three provenances in Sergipe, Brazil; due to asynchronous fruiting and field-access constraints, ripe fruits were obtained for 23 trees within the sampling window. Basic shape descriptors were computed under a simple, standardized setup, and basic shape descriptors were computed (length, width, aspect ratio, circularity) and CIELAB color indices. Exploratory analyses revealed clear phenotypic structure by provenance, with color channels—especially lightness and the green–red axis—carrying much of the discriminating signal, while simple shape metrics added complementary information. Models based on a compact subset of descriptors distinguished provenances with moderate performance, indicating that low-cost, image-derived features are sufficient to recover geographic structure. Dendrometric traits and fruit-quality measures (total soluble solids, pH, titratable acidity, firmness) provided additional context but did not replace the information captured by endocarp images. We translate these results into a concise descriptor panel and a field-ready workflow that can be implemented in collections and nurseries to support seed-lot traceability, germplasm management, and the selection of mother trees. The findings demonstrate a practical path to phenotyping at scale for conservation and sustainable use of umbuzeiro. Germplasm ; Context (archaeology) ; Traceability ; Morphometrics ; Provenance ; Heritability Wood and Agarwood Research ; Plant Gene Expression Analysis ; Smart Agriculture and AI
Authors: Chhunheng Lor | Sakobyly Kiv | Sungjoon Lim
Source: Advanced Optical Materials (article, 2026-02-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Rotation‐Driven Phase Modulation in a Mechanical Gear‐Matrix Metasurface for Beam Splitting, Wide‐Angle Scanning, Polarization Conversion ABSTRACT Simultaneous polarization conversion, beam scanning, and beam splitting are essential for advanced wireless systems requiring adaptive, multifunctional wavefront control. We present a mechanically reconfigurable metasurface driven by a gear matrix network, enabling wide‐angle circular polarization (CP) beam scanning through linear‐to‐circular polarization (LP‐to‐CP) conversion, as well as the generation of right‐ and left‐handed CP (RHCP and LHCP) components via coordinated rotation of unit cells (UCs). Rotation‐driven phase modulation provides a scalable and power‐efficient approach to radiofrequency beam manipulation. Unlike electronically tunable systems based on positive‐intrinsic‐negative diodes or transistors—often limited by cost, complexity, and scalability—the proposed system relies entirely on mechanical phase modulation for dynamic beam control. Each UC integrates a rotary dual X–Y polarization‐to‐CP frequency selective surface and a central rotation gear connected to a rack‐and‐gear array, enabling row‐wise tuning of the output phase. The phase of the transmitted wave varies according to the rotation angle (α) applied to the X–Y polarization components. By precisely controlling the phase gradient through mechanical rotation, the metasurface achieves beam scanning over a wide angular range of ± 70°, while simultaneously generating RHCP and LHCP components. Experimental results show excellent agreement with full‐wave simulations, validating the effectiveness of the gear matrix architecture. Wavefront ; Polarization (electrochemistry) ; Phase modulation ; Beam steering ; Beam (structure) ; Phase (matter) ; Rotation (mathematics) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Neural Networks and Reservoir Computing
Authors: Rachael Zoe Murray | Nadja Beck | Annalese BT Semmler | Francesca D. Frentiu | Lisa K. Chopin | Yasmin J. Antwertingere
Source: Research Square (preprint, 2026-03-16)
Field: Chemistry — Physical and Theoretical Chemistry

Designing edtech‑integrated authentic assessments for deep learning: insights from digital illustration tasks Preparedness ; Perception ; Grounded theory ; Qualitative property ; Qualitative research ; Online assessment ; Authentic assessment ; Educational assessment ; Credibility ; Higher education Various Chemistry Research Topics ; Student Assessment and Feedback ; Science Education and Pedagogy
Authors: Cheng Shen | Luzhen Zhao | XiaoJie Tang | Kunpeng Jin | Sibin Zhang | Guofeng Zhang
Source: Engineering Research Express (article, 2026-03-01)
Field: Materials Science — Materials Chemistry

Research on online monitoring of SF6 gas leakage environment based on 5G communication technology Abstract Based on 5G communication technology, this study proposes an innovative system for online monitoring of SF6 gas leakage environment. As a commonly used insulating gas in high-voltage electrical equipment, SF6 gas not only affects the equipment performance when it leaks, but also may have a serious greenhouse effect on the environment. Therefore, real-time monitoring of its leakage is crucial to ensure equipment safety and environmental protection. With the development of 5G communication technology, its characteristics of high speed, low latency and high connection density provide new technical support for gas leakage monitoring, which can significantly improve the efficiency and real-time performance of data transmission. In this study, multiple SF6 gas sensors were used to collect data such as gas concentration, temperature and humidity, and air pressure in real time at different monitoring points, and the data was transmitted to the cloud platform for processing and analysis through the 5G network. The experimental data show that the concentration of SF6 gas increases with time, especially when the equipment load increases, the gas concentration increases significantly. Within 1 h, the SF6 concentration increased from 18 ppm to 25 ppm, indicating that there is a certain correlation between equipment operating load and gas leakage. In addition, it is also found that temperature has a significant influence on the concentration of SF6, especially in high temperature environment, the gas concentration increases significantly. By analyzing the concentration changes under different weather conditions, the research shows that the concentration of SF6 varies greatly under high temperature conditions. This indicates that high-concentration SF6 gas leakage not only impacts the environment but also increases the failure rate of the equipment. Therefore, timely detection and response to gas leaks are crucial for ensuring equipment safety. Leakage (economics) ; Greenhouse gas ; Response time ; Cloud computing ; Toxic gas ; Real gas ; Temperature measurement High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission ; Intravenous Infusion Technology and Safety
Authors: Chaojiang Hu
Source: Textile & Leather Review (article, 2026-01-22)
Field: Materials Science — Polymers and Plastics

A Personalized Clothing Design System Enabled by Digital Textile Manufacturing The global textile industry is transitioning towards sustainable development, necessitating innovations in manufacturing that minimize material waste and enhance efficiency. This paper proposes a computational framework for personalized textile products enabled by digital textile manufacturing (DTM), directly addressing the inefficiencies of traditional textile processing. The system digitizes the entire manufacturing workflow, from raw-material selection to the finished product. It is designed to process a variety of yarn types, including natural fibers such as wool and cotton, as well as synthetic fibers. The architecture integrates modules for versatile user data input, parametric modeling based on materials science principles, and realistic simulation of textile properties. A key innovation is the proposed computational translation architecture, which utilizes a machine-agnostic intermediate representation (IR) to bridge the gap between digital design and production. By operating within a defined parametric design space, the system enables the deterministic and automated generation of machine-specific code for industrial knitting machinery. This approach is designed to drastically reduce material waste associated with cutting. The framework is conceptualized to be extensible, envisioning future integration with downstream digital processes, such as targeted chemical treatments. A validation study demonstrates the fidelity of the proposed logic in producing custom wool garments, confirming the system's ability to generate deterministic manufacturing data. Textile ; Digital manufacturing ; Process (computing) ; Textile industry ; Variety (cybernetics) ; Flexibility (engineering) ; Context (archaeology) ; Key (lock) ; Bridge (graph theory) ; Wool Textile materials and evaluations ; 3D Shape Modeling and Analysis ; Crafts, Textile, and Design
Authors: Francesco Pellicanò | Yuri V. Mikhlin | Konstantin V. Avramov | Antonio Zippo
Source: Vibration (article, 2026-02-05)
Field: Materials Science — Materials Chemistry

Editorial for the Special Issue of Vibration: Nonlinear Vibration of Mechanical Systems Nonlinear vibration phenomena play a central role in modern engineering, spanning applications from large-scale civil infrastructure to microscale and nanoscale systems [...] Microscale chemistry ; Mechanical system ; Vibration ; Nonlinear system ; Mechanical vibration ; Nonlinear dynamical systems Nonlocal and gradient elasticity in micro/nano structures ; Vibration Control and Rheological Fluids ; Mechanical and Optical Resonators
Authors: W. Marciniak | Joanna Marciniak | José Ángel Castellanos-Reyes | Ján Rusz
Source: Ultramicroscopy (preprint, 2026-01-21)
Field: Materials Science — Materials Chemistry

Mode-dependent phonon relaxation in time-resolved electron diffraction pattern simulations Time-resolved pump-probe experiments offer unique possibilities for studying ultrafast processes; however, simulation tools for interpreting phonon dynamics in electron diffraction patterns at the sub-picosecond scale remain limited. We introduce the frozen trajectory excitation (FTE) method of exciting phonons beyond their thermal equilibrium population by modifying a molecular dynamics trajectory in the (q→,ω)-space, and couple it with a new approach to ensemble sampling that extends frozen phonon multislice simulations into the time domain. In this approach, phonons with a certain natural frequency (ω) and located within an arbitrarily selected range of phonon wave vector (q→) are first selectively excited within a single molecular dynamics trajectory. Subsequently, several parallel relaxation runs are started at random points, and snapshots from these trajectories serve as inputs for multislice simulations at defined time delays. We apply this framework to fcc Ni with relaxation time resolution of 10fs. The simulations reveal multi-phonon scattering processes as well as strong mode dependence in phonon relaxation, highlighting the importance of considering phonon-specific behavior in ultrafast dynamics. Our results show that mode-dependent relaxation leaves measurable signatures in diffraction patterns, providing predictive guidance for future time-resolved TEM studies. Phonon ; Relaxation (psychology) ; Trajectory ; Mode (computer interface) ; Molecular dynamics ; Dynamics (music) ; Physics ; Condensed matter physics ; Materials science ; Statistical physics ; Quantum mechanics ; Computer science Thermal Expansion and Ionic Conductivity ; Thermal properties of materials ; Superconductivity in MgB2 and Alloys
Authors: Jinpeng Peng | Yi Zhang | Zihao Chen | Qiye Wen | ShaoMeng Wang | YaoYao Li | Aiwu Zhou | Zhengnan Sun | Xiaohui Mu | Xiaosheng Zhang
Source: Nano-Micro Letters (article, 2026-01-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Annular Microfluidic Meta-Atom Fusion-Enabled Broadband Metamaterial Absorber Electromagnetic (EM) metamaterial absorbers (MMAs) with broadband absorption are of growing interest for applications such as stealth and EM interference mitigation. In this work, we present a novel 3D-printed MMA based on a fused annular microfluidic meta-atom (FAMMA) architecture, designed for W-band absorption. The FAMMA structure features three kinds of orthogonally fused annual meta-atoms, forming a complex 3D microfluidic meta-atom with intricate architecture. Fabricated via high-precision micro 3D printing technology, the FAMMA-based MMA exploits the synergistic solid-liquid coupling effect of the unique three-dimensional orthogonal structure to achieve strong broadband absorption. Three representative FAMMAs with different geometric dimensions have achieved ultra-low reflection loss (RL of - 42.1 dB), ultra-broadband effective absorption bandwidth (EAB of 31.3 GHz), and dual-band absorption (in 76.0-85.3 and 99.1-105.6 GHz), respectively. The underlying absorption mechanisms are elucidated by impedance matching theory and electromagnetic field distribution analyses. Application demonstrations show that the FAMMA-based MMA significantly suppresses radar echo power and renders metallic targets undetectable to both radar detector and radar imaging systems, highlighting its potential in stealth technology. Overall, this work establishes a new design concept for high-performance broadband millimeter wave MMAs, opening new avenue for future applications such as high-speed communication, through-wall sensing, and drone detection. Broadband ; Metamaterial ; Metamaterial absorber ; Microfluidics ; Bandwidth (computing) ; Radar ; Absorption (acoustics) ; Impedance matching ; Microwave Metamaterials and Metasurfaces Applications ; Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies
Authors: Katarzyna Macur | Aleksandra Bogucka | Anna Fel-Tukalska | Jarosław Skokowski | Stanisław Ołdziej | Paulina Czaplewska
Source: Frontiers in Molecular Biosciences (article, 2026-02-19)
Field: Chemistry — Spectroscopy

A label-free microLC–SWATH-MS methodology with immunoaffinity depletion of highly abundant serum proteins for quantitative proteomic comparison of fresh-frozen human normal breast tissue and tumor clinical specimens This proof-of-concept study demonstrates that the developed microLC-SWATH-MS approach, combined with a custom spectral library generated from pooled breast tissue and tumor samples immunoaffinity-depleted of 14 high-abundance serum proteins, enables robust and high-throughput proteomic profiling of breast tissue and tumors. Further expansion of high-quality spectral libraries may enhance proteome coverage and improve the clinical applicability of this approach. While the methodology supports the discovery of candidate biomarkers and therapeutic targets relevant to translational research and precision oncology, the biological conclusions drawn from this study should be interpreted with caution due to the limited sample size. Validation in larger patient cohorts using orthogonal methods will be required to confirm the potential clinical utility of the identified proteins. Proteome ; Proteomics ; Breast cancer ; Human breast ; Quantitative proteomics ; Tandem mass spectrometry ; Extracellular matrix ; Extracellular ; Breast tumor Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Lijun Dong | Hao Chen | Gang Dai | Xudan Chen | Dawei Yin | Xiaopeng Song | Ying Liu | Yinfeng Qian
Source: Quantitative Imaging in Medicine and Surgery (article, 2026-02-13)
Field: Materials Science — Materials Chemistry

Grading of glioma and prediction of IDH mutation status via longitudinal relaxation time in rotating frame mapping on 5-T magnetic resonance imaging: added value to amide proton transfer-weighted imaging Both T1rho mapping and APT-CEST can be used to grade gliomas and differentiate IDH mutational status. Combining these two techniques further aids in the differentiation of HGG from LGG. Glioma ; Grading (engineering) ; Magnetic resonance imaging ; Isocitrate dehydrogenase ; White matter ; Receiver operating characteristic ; Lesion Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: August Hoel | Fredrik Hoel | Sissel Elisabeth Dyrstad | Henrique Chapola | Ingrid G. Rekeland | Kristin Risa | Kine Alme | Kari Sørland | Karl A. Brokstad | Hans-Peter Marti | Olav Mella | Øystein Fluge | Karl Johan Tronstad
Source: Cell Reports Medicine (article, 2026-03-01)
Field: Chemistry — Spectroscopy

Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating condition often triggered by infections, with unclear mechanisms and no established biomarkers or treatments. We apply aptamer-based serum proteomics to 50 ME/CFS patients and 29 healthy controls, analyzing 7,326 protein targets. We identify 1,823 aptamers with significant differences between the groups (845 after false discovery rate [FDR] correction). Distinct patterns of tissue- and process-specific changes are seen. There is a broad increase in secreted proteins, while intracellular proteins, e.g., from skeletal muscle, particularly show reduction. Immune cell-associated signatures indicate immune reprogramming, including a distinct reduction in proteins secreted by activated neutrophils. Focused secretome analysis supports intensified regulatory interactions related to immune activity, inflammation, vasculature, and metabolism. Validation of measurements using antibody-based methods confirms findings for a selection of proteins. The uncovered serum proteome patterns in ME/CFS patients may contribute to understanding the pathophysiology and inform future biomarker research and therapeutic development. Profiling (computer programming) ; Proteome ; Human proteome project ; Proteomics ; Proteogenomics Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Biotin and Related Studies
Authors: Surendra Balraadjsing | Willie J. G. M. Peijnenburg | Martina G. Vijver
Source: Data (article, 2026-01-15)
Field: Materials Science — Materials Chemistry

A Curated Dataset on the Acute In Vivo Ecotoxicity of Metallic Nanomaterials from Published Literature Metallic engineered nanomaterials (ENMs) have enormous technological potential and are increasingly applied across different fields and products. However, substances (including ENMs) can be detrimental to the environment and human health, thus requiring systematic testing to uncover potential hazardous effects (in compliance with REACH). Although hazard testing traditionally involves the use of animal experiments, recent years have seen a shift towards in silico modeling. High-quality data is required for in silico modeling, which is frequently not readily available for ENMs. Vast amounts of data have been published in literature but they are unstructured and scattered across numerous sources. To mitigate the limitations in data availability, we have compiled and created a nanotoxicity dataset based on published literature. The compiled dataset focuses mainly on acute in vivo endpoints conducted in a laboratory setting using metallic nanomaterials. The data extracted from literature include material information, physico-chemical properties, experimental conditions, endpoint information, and literary meta-data. The dataset presented here is useful for meta-analysis or in silico modeling purposes. In silico ; Ecotoxicity ; Nanotoxicology ; Hazard ; Hazard analysis Nanoparticles: synthesis and applications ; Effects and risks of endocrine disrupting chemicals ; Nanoparticle-Based Drug Delivery