jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rodolfo O. Esquivel | Hazel Vázquez-Hernández | Jonathan Ornelas-Muñoz
Source: Quantum Reports (article, 2026-03-12)
Field: Chemistry — Physical and Theoretical Chemistry

The Periodic Table as an Emergent Helicoidal Manifold: A Unified Information-Theoretic Analysis of the Atomic Elements Z = 1–103 Here we perform a detailed information-theoretic (IT) analysis of atomic electron densities in the periodic table, from hydrogen (Z = 1) to lawrencium (Z = 103). By use of the Shannon entropy, the Fisher information and the disequilibrium functionals in both position and momentum spaces as fundamental descriptors of the atomic densities, the periodic table can be represented in a three-dimensional information space as a continuous, highly ordered manifold. The analysis shows that chemical periodicity naturally emerges as a helicoidal manifold (reminiscent of a helix) at the coordinates of a 3D theoretic-information space (Shannon, Fisher, Disequilibrium), with each period forming one segment within the continuous global trajectory. We find information-theoretic signatures of shell structure, sub-shell filling, and electron-configuration anomalies, such as the familiar irregularities seen in chromium and copper. Therefore, the helicoidal character emerges naturally and is not imposed a priori. Further, through the uncertainty principle of the complementary analysis in momentum space, more insights are gained by exposing maximal information-theoretic differentiation for lighter atoms and compression among heavy elements. Notably, momentum-space analysis reveals that hydrogen occupies a natural intermediate position between helium and lithium based on kinetic energy distribution—contrasting with IT position-space results that emphasize hydrogen’s unique delocalized electron density. Indeed, the 3D IT representation of the elements in position space aligns with the view that H does not belong to either the alkali metals or the halogens, but rather stands as a unique, standalone element. This complementary perspective provides new quantitative support for understanding hydrogen’s dual chemical nature, providing new quantitative insight into ongoing debates about hydrogen’s optimal periodic table position. Furthermore, by considering triadic relationships and complexity properties in relation to the López–Mancini–Ruiz (LMC) and Fisher–Shannon (FS) functionals, we show that atomic complexity increases monotonically along with nuclear charge, and we provide a quantitative measure of how organized atomic electron densities are distributed throughout the periodic system. Based on our IT analyses, the fundamental character of periodicity could be addressed by employing helicoidal representations that highlight the characteristics of hydrogen, while simultaneously preserving the autonomy of the blocks of elements. Periodic table ; Position (finance) ; Space (punctuation) ; Manifold (fluid mechanics) ; Representation (politics) ; Momentum (technical analysis) ; Table (database) ; Position and momentum space ; Electron History and advancements in chemistry ; Machine Learning in Materials Science ; Quantum Mechanics and Non-Hermitian Physics
Authors: Robbin Bouwmeester | Alireza Nameni | Arthur Declercq | Robbe Devreese | Kevin Velghe | Vladimir Gorshkov | Pelayo Álvarez Penanes | Frank Kjeldsen | Magali Rompais | Christine Carapito | Ralf Gabriels | Lennart Martens
Source: Nature Communications (article, 2026-02-10)
Field: Chemistry — Spectroscopy

Transfer learning in DeepLC improves LC retention time prediction across substantially different modifications and setups While LC retention time prediction of peptides and their modifications has proven useful, widespread adoption and optimal performance are hindered by variations in experimental parameters. These variations can render retention time prediction models inaccurate and dramatically reduce the value of predictions for identification, validation, and DIA spectral library generation. To date, mitigation of these issues has been attempted through calibration or by training bespoke models for specific experimental setups, with only partial success. We here demonstrate that transfer learning can successfully overcome these limitations by leveraging pre-trained model parameters. Remarkably, this approach can even fit highly performant models to substantially different peptide modifications and LC conditions than those on which the model was originally trained. This impressive adaptability of transfer learning makes it a highly robust solution for accurate peptide retention time prediction across a very wide variety of imaginable proteomics workflows. Bespoke ; Adaptability ; Transfer of learning ; Retention time ; Variety (cybernetics) ; Calibration ; Flexibility (engineering) Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; vaccines and immunoinformatics approaches
Authors: Yishu Zhang | Tianfeng Yan
Source: Applied Sciences (article, 2026-02-02)
Field: Materials Science — Materials Chemistry

Classification and Recognition of Ultra-High-Frequency Partial Discharge Signals in Transformers Based on AHAFN Insulation defects are the main cause of transformer faults, and the partial discharge phenomenon generated by defects under high-voltage excitation can reflect the internal characteristics of the defects. Therefore, studying the characteristics of partial discharge signals can provide an important basis for the analysis of transformer partial discharge problems. This article proposes a transformer partial discharge ultra-high-frequency signal classification and recognition method based on the Adaptive Hybrid Attention Fusion Network. The feature extraction of partial discharge waveform is carried out through a dual flow network structure, where the ResNet branch focuses on extracting local features and the Swin Transformer branch focuses on extracting global features. Then, a new Adaptive Hybrid Attention Fusion Network fusion model is used to weight the extracted features according to adaptive allocation weights, ultimately achieving the classification and recognition of transformer partial discharge ultra-high-frequency signals. The experiment shows that this method achieves a fault detection accuracy of 99.58%, with a loss rate of only 0.73%. Compared to various existing network models, the accuracy of the proposed model reached 99.58%, the recall was 99.58%, and the F1 score was 99.58%, which is significantly better than other model methods, indicating that the model has significant advantages in detection performance. Partial discharge ; Transformer ; Pattern recognition (psychology) ; Feature extraction ; Cascade High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Power Systems Fault Detection
Authors: Thakorn Pruktanakul | Konstantinos Theofilatos
Source: Journal of Cardiovascular Development and Disease (article, 2026-01-01)
Field: Chemistry — Spectroscopy

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome Proteins exist as multiple chemical and sequence-specific proteoforms, each of which may serve as a critical mediator of physiological or pathological signalling. This diversity arises from processes such as alternative splicing of gene transcripts, translation into amino acid sequences, and various post-translational modifications (PTMs), leading to an exponential increase in biological complexity. This manuscript provides an overview of the mechanisms underlying proteoform generation in biological systems and highlights strategies for their analysis using mass spectrometry (MS)-based proteomics and bioinformatics. Additionally, it focuses on recent findings linking PTMs to cardiovascular disease (CVD), highlighting the MS-based methods and workflows that have been used to study uncommon PTMs and their role in CVD. This review provides a comprehensive collection of tools and knowledge to explore the breadth of proteoforms, particularly PTMs, within their specific areas of interest in cardiovascular physiology. Proteomics ; Proteome ; Alternative splicing ; Profiling (computer programming) ; Human proteome project ; Systems biology ; Workflow Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Metabolomics and Mass Spectrometry Studies
Authors: Xiang Shu | Zhaoyang Wang | Ying Wen | Yuexin Shi | Xue‐Wang Gao | Shumin Yang | Jianqun Shao | Ke Feng | Bin Chen | Nan Xie | Chen-Ho Tung | Li-Zhu Wu
Source: Nano Research (article, 2026-02-14)
Field: Materials Science — Biomaterials

Photochemically fabricated peptide hydrogels from de novo design to application in antibacterial therapy and wound healing <em>De novo</em> designed peptide amphiphiles have been exemplified as building blocks for direct fabrication of biofunctional hydrogels through a photochemical approach. Herein, by incorporating diphenylalanine (FF) as a self-assembling antibacterial motif and dityrosine (YY) as a photocrosslinkable unit, the peptide sequences are interconnected through alternating hydrophilic D (<em>L</em>-aspartate) and hydrophobic X (<em>ε</em>-aminocaproic acid) residues to achieve a precise balance between non-covalent fibrillization and covalent crosslinking. Upon visible-light irradiation, these peptides undergo rapid photocrosslinking in aqueous media, yielding hydrogels with tunable gelation properties, robust mechanical stability, and adjustable functionality. The optimized 4Y6F hydrogel exhibits strong antibacterial efficacy against both Gram-positive and Gram-negative bacteria, attributed to synergistic structural interactions. <em>In vivo</em> wound healing studies demonstrate accelerated re-epithelialization, enhanced collagen deposition, and improved angiogenesis, significantly outperforming control groups and commercial formulations. This study presents a versatile peptide platform for the photochemical fabrication of hydrogels, advancing from <em>de novo</em> design to practical applications in antibacterial therapy and wound healing, and offering a promising bottom-up approach for a wide range of biomedical scenarios. Self-healing hydrogels ; Peptide ; Amphiphile ; Wound healing ; Antibacterial activity ; Fabrication ; Aqueous solution ; Antibacterial peptide Supramolecular Self-Assembly in Materials ; Hydrogels: synthesis, properties, applications ; Polydiacetylene-based materials and applications
Authors: Xue Zhang | Wenqiang Tang | Shuzhan Yan | Yun Fang
Source: Journal of Applied Physics (article, 2026-03-10)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A residual multi-layer perceptron framework for transmission prediction and physical interpretation of terahertz responses in multilayer compound metal–dielectric metasurfaces Metamaterials have emerged as promising candidates for terahertz applications. Among different structures, metal–dielectric composite periodic arrays have gained significant interest due to their ability to efficiently manipulate electromagnetic wave propagation and enhance transmission in the terahertz range. In this work, we present a deep-learning-driven modeling framework based on a Residual Multi-Layer Perceptron (ResMLP) to predict the transmittance of multilayer metal–dielectric composite periodic annular-aperture arrays. A large-scale dataset comprising geometric parameters and transmittance spectra obtained from full-wave electromagnetic simulations was used to train the ResMLP. The trained model achieves highly accurate predictions of optical responses, with a validation mean squared error of 0.000 166. To further assess reliability, a “closed-loop verification” was performed, in which the predicted geometric parameters were reintroduced into the forward simulator to regenerate the transmittance spectra, yielding high consistency with the target spectra. Compared to full-wave simulation, our approach offers up to 105-fold improvement in computational efficiency without compromising accuracy. This study demonstrates the potential of deep learning in accelerating the design and optimization of multilayer metal–dielectric metasurfaces, thereby facilitating the development of terahertz photonic devices. Transmittance ; Terahertz radiation ; Residual ; Transmission (telecommunications) ; Multilayer perceptron ; Consistency (knowledge bases) ; Photonics ; Perceptron ; Mean squared error Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Terahertz technology and applications
Authors: Mehmet Budakci | Serdar Kaçamer | Ferzan Katırcıoğlu
Source: Dialnet (Universidad de la Rioja) (article, 2026-01-01)
Field: Materials Science — Biomaterials

Image based colorimetric characterization of scrub induced color changes in UV printed and water transfer printed MDF boards Conventional colorimetric evaluation methods remain inadequate for accurately characterizing scrub-induced color changes on UV-printed and water transfer-printed decorative coatings applied to MDF after chemical resistance testing; therefore, this study proposes an image-based colorimetric characterization approach using an Image Processing-Based Scrub Tester to quantitatively assess such changes under simulated domestic chemical exposure. For this study, 8 mm thick Medium-Density Fiberboard sheets with a bright white, polyvinyl chloride-coated Medium-Density Fiberboard, high-gloss acrylic coating Medium-Density Fiberboard, Medium-Density Fiberboard lam, and Medium-Density Fiberboard sheets treated with polyurethane, cellulose-based, water-based and acrylic paints were utilized. A carbon fiber-patterned organic finish was applied to the surfaces of the pre-treated Medium-Density Fiberboard sample using ultraviolet printing and water transfer printing (WTP) techniques, followed by scrubbing testing with various domestic cleaning agents in compliance with Turkish Standards. As part of the picture evaluation process in this study, digital picture of the samples was captured after and before the scrubbing process. Color measurements were then analyzed based on L*, a*, and b* coordinates, conforming to the Commission Internationale de l'Éclairage (CIE L*a*b*) color system, utilizing a newly developed evaluation technique. From the outcomes of the study, it was observed that the overall color shift of the water transfer printing samples was 124,63% more than the ultraviolet printed samples. To assess the precision of the Image Processing-Based Scrub Tester's color measurement system developed in this research, its results were benchmarked against those from a different color tester. As a result, the findings strongly suggest that the color test analysis performed with Image Processing-Based Scrub Tester, together with the developed software, has the potential to serve as an alternative to industrial testing equipment. Fiberboard ; Color difference ; Colorimetry ; Medium density fiberboard ; Ultraviolet ; Characterization (materials science) ; Colorimeter ; Chromaticity Advanced Cellulose Research Studies ; Material Properties and Processing ; Fiber-reinforced polymer composites
Authors: Mouad Chettab
Source: Journal of Information Systems Engineering & Management (article, 2026-04-04)
Field: Materials Science — Materials Chemistry

Influence of Physical Parameters on p-CuO/n-CdS/n-Zn2SnO4 Solar cell: A Numerical Investigation Achieving Efficiency of 28.50 % Using SCAPS-1D This work presents a comprehensive numerical investigation of CuO thin-film solar cells using SCAPS-1D, focusing on replacing conventional CdTe and CIGS absorber layers with environmentally friendly alternative CuO metal oxide. The simulation explores the influence of absorber, buffer and window layer thicknesses, as well as temperature on the key photovoltaic parameters of CuO-based devices. The optimization study shows that an absorber thickness of 4 µm maximizes light absorption without excessive recombination, while the buffer and window layers achieve optimal performance at 0.02 µm. The results indicate that increasing the temperature from 300 K to 400 K causes a gradual decline in efficiency from 21.62 % to 16.58 %. Furthermore, specific parameters of p-CuO/n-CdS/n-Zn2SnO4 heterostructure, such as the influence of defects density, acceptor concentration, metal work function, Rs and Rsh were examined. Our findings revealed that the efficiency could be improved by increasing the acceptor concentration of p-type CuO layer and metal work function of the contact and reduced defects density and balancing between Rs and Rsh. The optimized p-CuO/n-CdS/n-Zn2SnO4 configuration attains a high conversion efficiency of 28.50 % under AM 1.5 illumination, demonstrating that CuO solar cell can achieve competitive performance. This study provides valuable insights for the design of cost-effective, non-toxic, and high-efficiency photovoltaic devices. Photovoltaic system ; Copper indium gallium selenide solar cells ; Work (physics) ; Absorption (acoustics) ; Energy conversion efficiency ; Buffer (optical fiber) ; Cadmium telluride photovoltaics ; Layer (electronics) Copper-based nanomaterials and applications ; Chalcogenide Semiconductor Thin Films ; ZnO doping and properties
Authors: Bernardo Ribeiro | José Monteiro | Mariana Truta | Rúben F. Santos | Maria Barbosa | Elsa W. Sequeiros
Source: Journal of Sustainable Metallurgy (article, 2026-01-14)
Field: Materials Science — Materials Chemistry

Trends and Challenges in Lead-Free Brass Alloy Development for Machining Applications: A Systematic Literature Review Abstract Lead (Pb) is widely used in brass alloys (Cu–Zn) to enhance machinability, as its deformation into needle-like particles promotes chip breakage by initiating cracks. However, growing awareness of Pb’s toxicity has led to strict environmental regulations and growing demand for sustainable, lead-free alternatives. This systematic review, conducted following the PRISMA 2020 framework, consolidates recent research on the development and performance of machinable lead-free brass alloys. A comprehensive search was performed in the Web of Science, ScienceDirect, and Scopus databases, identifying 93 studies for full-text analysis. Various strategies have been identified for the development of lead-free brass, including process optimization, heat treatments, direct Pb substitution, and novel alloy design. The review highlights significant progress in achieving acceptable mechanical and machining performance, although trade-offs in cost, corrosion resistance, and large-scale manufacturability remain. The consolidated key findings offer a structured basis for future alloy design and promote consistent evaluation of microstructural, mechanical, and machining properties. Graphical Abstract Brass ; Machining ; Systematic review ; Design for manufacturability ; Scopus ; Alloy Metallurgy and Material Science ; Nanoporous metals and alloys ; Aluminum Alloys Composites Properties
Authors: Ronghua Li | Xiaoqian Fu | Chuanwei Li | Lian Yuan | Yaozhi Liu | Lin Yang | Xiaojia Fang | Xiao‐Bin Zhang | Guangya Zhang | Xiangdong Du
Source: Frontiers in Psychiatry (article, 2026-01-07)
Field: Chemistry — Spectroscopy

Five differentially expressed proteins identified to serve as potential blood biomarkers for schizophrenia screening based on proteomics Our research indicates that neural cell adhesion molecule L1, integrin alpha-M, alpha-actinin-1, filamin-A and profilin-1 which are associated with cytoskeleton, synapse and immunity were preliminarily screened as candidate protein markers for schizophrenia. Moreover, mitogen-activated protein kinase signaling pathway may be related to the pathology of schizophrenia, and PI3K-Akt signaling pathway may be related to the efficacy and side effects of antipsychotic drugs. Proteomics ; Schizophrenia (object-oriented programming) ; Signal transduction ; Integrin ; Cell adhesion molecule ; Cell adhesion ; Cell signaling ; Antipsychotic Advanced Proteomics Techniques and Applications ; Schizophrenia research and treatment ; Tryptophan and brain disorders
Authors: Uguru Chukwudi Clement | David Chinonso Anih | Adamu Kamaliddeen Salisu | Nwanze Tobechukwu Joseph
Source: Asian Journal of Earth Sciences (article, 2026-01-15)
Field: Materials Science — Biomaterials

Hidden Mechanisms of Critical-Metal Enrichment in Deep Tropical Lateritic Weathering Profiles This review brings together recent field based and laboratory studies (2020 to 2025) that investigate concealed concentrations of critical metals, including rare earth elements (REEs), scandium, nickel and cobalt, within deep tropical lateritic weathering profiles.Using a PRISMA framework, the authors reduced an initial pool of 1,240 records to fifty studies that satisfied strict inclusion criteria for geochemical, isotopic and mineralogical data quality.The aim is to integrate lines of evidence to explain how these metals are mobilized, transported and fixed beneath the visible laterite mantle and to highlight consequences for exploration and environmental management.The selected investigations deployed high sensitivity trace element analysis (ICP MS), neodymium and strontium isotopes measured by multi collector ICP MS, X ray diffraction, scanning electron microscopy with energy dispersive spectroscopy, and sequential leaching experiments to partition operational metal fractions.By comparing depth resolved geochemical profiles, isotopic fingerprints and mineral host relationships, the synthesis distinguishes metals inherited from parent lithology from those redistributed by fluid flow and redox processes.Clear and consistent patterns emerge across diverse tropical settings.Parent rock composition exerts a primary control: Mafic protoliths favor nickel and cobalt enrichment typically hosted by iron oxyhydroxides and manganese phases, while felsic sources more often retain REE and scandium within resistant accessory minerals such as zircon, monazite and anatase.Isotopic gradients, together with sequential leach results, support a working model in which metals are leached from surficial horizons and reprecipitated at depth, forming cryptic enrichment zones commonly between about 10 and 20 m below ground.Seasonal water table shifts, oscillating redox conditions, organic complexation and microbial activity emerge as key modulators of metal mobility.The review demonstrates that reliance on shallow sampling can overlook blind deposits.Integrated exploration strategies that combine deep coring, isotopic mapping, targeted mineralogical screening and sequential leaching enhance discovery success.Equally important, responsible development requires life cycle assessment, circular economy measures and inclusive land use planning to limit deforestation, erosion and water contamination.By synthesizing multiproxy evidence, this study advances a refined conceptual model for hidden lateritic enrichment and offers practical guidance for more effective and environmentally responsible critical metal exploration in tropical regions. Weathering ; Laterite ; Total organic carbon ; Hydrology (agriculture) Clay minerals and soil interactions ; Building materials and conservation ; Concrete and Cement Materials Research