jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Masahiko Araki | Yuki Sakai | Yoshiki Iwazaki
Source: Journal of the Ceramic Society of Japan (article, 2025-01-24)
Field: Materials Science — Materials Chemistry

Stability and defect state of vanadium at BaTiO&lt;sub&gt;3&lt;/sub&gt; grain boundaries First-principles and molecular dynamics simulations are used to understand the stability and defect state of vanadium ions at BaTiO3 grain boundaries. Qualitative analysis is performed based on two approaches to approximate polycrystalline grain boundaries. First, stable grain boundaries are modeled to evaluate the defect formation energies of grain boundary sites and bulk sites. Second, amorphous BaTiO3 is used to analyze the relationship between defect structure and stability of vanadium. The electronic states of vanadium atoms in the amorphous state are statistically analyzed to understand the effect of complex structures such as grain boundaries. These results suggest that vanadium acts as a donor at grain boundaries. Materials science ; Vanadium ; Grain boundary ; Grain growth ; State (computer science) ; Engineering physics ; Mineralogy ; Chemical engineering ; Metallurgy ; Crystallography ; Condensed matter physics ; Grain size ; Microstructure ; Chemistry Electronic and Structural Properties of Oxides ; Advanced materials and composites ; Advanced Materials Characterization Techniques
Authors: Miaomiao Chen | Yujie Gou | Ming Lei | Leming Xiao | Miaoying Zhao | Xu‐Dong Huang | Dan Liu | Zihao Feng | Di Peng | Yu Xue
Source: Genomics Proteomics & Bioinformatics (article, 2025-06-01)
Field: Chemistry — Spectroscopy

EPSD 2.0: An Updated Database of Protein Phosphorylation Sites Across Eukaryotic Species As one of the most crucial post-translational modifications, protein phosphorylation regulates a broad range of biological processes in eukaryotes. Biocuration, integration, and annotation of reported phosphorylation events will deliver a valuable resource for the community. Here, we present an updated database, the eukaryotic phosphorylation site database 2.0 (EPSD 2.0), which includes 2,769,163 experimentally identified phosphorylation sites (p-sites) in 362,707 phosphoproteins from 223 eukaryotes. From the literature, 873,718 new p-sites identified through high-throughput phosphoproteomic research were first collected, and 1,078,888 original phosphopeptides together with primary references were reserved. Then, this dataset was merged into EPSD 1.0, comprising 1,616,804 p-sites within 209,326 proteins across 68 eukaryotic organisms. We also integrated 362,190 additional known p-sites from 10 public databases. After redundancy clearance, we manually re-checked each p-site and annotated 88,074 functional events for 32,762 p-sites, covering 58 types of downstream effects on phosphoproteins, and regulatory impacts on 107 biological processes. In addition, phosphoproteins and p-sites in 8 model organisms were meticulously annotated utilizing information supplied by 100 external platforms encompassing 15 areas. These areas included kinase/phosphatase, transcription regulators, three-dimensional structures, physicochemical characteristics, genomic variations, functional descriptions, protein domains, molecular interactions, drug-target associations, disease-related data, orthologs, transcript expression levels, proteomics, subcellular localization, and regulatory pathways. We expect that EPSD 2.0 will become a useful database supporting comprehensive studies on phosphorylation in eukaryotes. The EPSD 2.0 database is freely accessible online at https://epsd.biocuckoo.cn/. Phosphorylation ; Database ; Computational biology ; Proteomics ; Biology ; Annotation ; Protein phosphorylation ; Bioinformatics ; Gene ; Protein kinase A ; Biochemistry ; Computer science Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Glycosylation and Glycoproteins Research
Authors: Iara Jeanice Souza Ferreira | Daniel dos Santos Costa | Larissa Araújo Rolim | Sérgio Tonetto de Freitas | Nathália Andrezza Carvalho de Souza | Bárbara Teruel
Source: Journal of Food Composition and Analysis (article, 2025-07-17)
Field: Chemistry — Analytical Chemistry

Monitoring pesticides with portable NIR spectroscopy in different intact fruits Pesticide ; Spectroscopy ; Environmental chemistry ; Chemistry ; Environmental science ; Biology ; Agronomy ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Joannes Dekker | Carli Peters | Rachel Winter | Matthew J. Collins | Marc R. Dickinson | Virginia L. Harvey | Eden Hill | Bharath Nair | Takumi Tsutaya | Laura Viñas Caron | Christina Warinner | Frido Welker | Zandra Fagernäs
Source: Peer Community Journal (article, 2025-08-06)
Field: Chemistry — Spectroscopy

Open science, communication, and collaboration for the future of palaeoproteomics Palaeoproteomics focuses on studying the past by analysing proteins preserved in historical, archaeological, and palaeontological materials. Over the past fifteen years, the number of publications and research questions in this field has grown substantially, as has the number of researchers and research groups utilising palaeoproteomic methods. PAASTA (Palaeoproteomics And Archaeology, Society for Techniques and Advances) is an international early career researcher-driven community, which aims to bring together researchers from all subdisciplines of palaeoproteomics by providing a platform for open communication. Here, we discuss ways in which this fast-growing research field can benefit from adopting principles of open science and increased communication and collaboration between researchers. We approach this question from all stages of a typical research project, from experimental design and sample selection, to data analysis and raw data sharing. Although we acknowledge that each of these guidelines and recommendations may not be applicable to every research project, we aim to provide a foundation which, when applied collectively, will strengthen the future of palaeoproteomics. Field (mathematics) ; Foundation (evidence) ; Data science ; Open science ; Raw data ; Sample (material) ; Engineering ethics ; Selection (genetic algorithm) ; Open research ; Computer science ; Data sharing ; Sociology ; World Wide Web ; Engineering ; Archaeology ; Geography Advanced Proteomics Techniques and Applications ; Forensic and Genetic Research ; Scientific Computing and Data Management
Authors: Tingting Li | Alexander Wenger | Cristina Coman | Corinna Borutzki | Michael R. Kreutz | Robert Ahrends
Source: PROTEOMICS (article, 2025-08-01)
Field: Chemistry — Spectroscopy

SIMPLEX Enriches Hydrophobic and Lipidated Proteins in Membrane Proteomics Experiments Synaptosomes (Syn) and synaptic junctions (SJ) are key neuronal compartments that have been widely characterized in omics studies to understand neurotransmitter- and signal transduction-related events. While synapses are lipid-rich, multiomics approaches integrating lipids and proteins remain largely underexplored. Liquid-liquid extraction (LLE), commonly used in lipidomics, offers significant potential for multiomics analyses by enabling the extraction of diverse molecular classes from a single sample. However, its impact on protein and phosphoprotein analysis in membrane-enriched samples has not been thoroughly investigated or compared to one-phase extraction methods. In this study, we assessed SIMPLEX (Simultaneous Metabolite, Protein, Lipid Extraction), an LLE-based method, against conventional acetone protein precipitation for mass spectrometry-based protein identification. SIMPLEX proved superior for proteomics and phosphoproteomics of SJ, achieving a 42% enrichment in membrane proteins compared to acetone precipitation. It enriched not only transmembrane proteins but also S-palmitoylated proteins. Enriched phosphoproteins included those with beta-transducin repeats (WD40), Armadillo repeats (ARM), and various transmembrane domains, highlighting the SIMPLEX potential and enhanced performance for multiomics analyses. Proteomics ; Computational biology ; Membrane protein ; Chemistry ; Membrane ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications ; Lipid Membrane Structure and Behavior ; Cellular transport and secretion
Authors: Aurélien Decelle | Alfonso de Jesús Navas Gómez | Beatriz Seoane
Source: Physical Review Letters (preprint, 2025-11-12)
Field: Chemistry — Spectroscopy

Inferring Higher-Order Couplings with Neural Networks Maximum entropy methods, rooted in the inverse Ising or Potts problem of statistical physics, have been fundamental in inferring pairwise interaction models of complex systems. These models have found impactful applications in fields such as bioinformatics, where they are used to infer protein structural contacts, and in neuroscience, for describing patterns of neural activity. Despite their considerable success, these approaches fail to capture higher-order interactions that could be crucial for a full description of collective behavior. In contrast, modern machine learning methods can model such interactions, but their interpretability usually comes at a prohibitive computational cost. Restricted Boltzmann machines (RBMs) provide a computationally efficient alternative by encoding statistical correlations through hidden units in a bipartite architecture. In this Letter, we introduce a method that maps RBMs onto generalized Potts models, enabling the systematic extraction of interactions up to arbitrary order. Leveraging large-$N$ approximations, made tractable by the RBM's structure, we extract effective many-body couplings with minimal computational effort. We further propose a robust framework for recovering higher-order interactions in more complex generative models, and introduce a simple gauge-fixing scheme for the effective Potts representation. Validation on synthetic data demonstrates accurate recovery of two- and three-body interactions. Applied to protein sequence data, our method reconstructs contact maps with high fidelity and outperforms state-of-the-art inverse Potts models. These results establish RBMs as a powerful and efficient tool for modeling higher-order structure for high-dimensional categorical data. Order (exchange) ; Computer science ; Artificial neural network ; Deep neural networks ; Artificial intelligence ; Cognitive science ; Psychology ; Economics Spectroscopy and Laser Applications ; Neural Networks and Applications ; Image and Signal Denoising Methods
Authors: Cai Zhang | Wenhui Zhao | Duo Zuo | Tao Zhou | Wenjing Hou | Lingling Wang | Shangheng Shi | Yang Yang | Yuanyuan Liu | Shao‐Kai Sun | Li Ren | Zhaoxiang Ye | Dingbin Liu | Dong Li | Xiaoyuan Chen | Jihui Hao
Source: Advanced Science (article, 2025-11-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

AI‐Guided SERS Defines a Pan‐Cancer Diagnostic Biomarker Early and accurate detection of multiple cancers through a single test remains an unmet clinical need, hindered by current limitations in accuracy, throughput, automation, and multiplexing. Here, we present an AI-powered SERS chip that combines automated exosome capture with AI-enabled molecular fingerprinting to accurately distinguish ten common cancer types from a single serum test. The system employs a peptide-functionalized SERS chip enabling the selective enrichment of exosomes directly from patient serum, enhancing label-free Raman fingerprint signals. AI-driven spectral analysis achieved 97.4% accuracy in distinguishing cancer from healthy samples, 97.08% accuracy for early-stage cancer detection, and 93.89% accuracy in classifying ten common cancer types, including breast, thyroid, esophageal, kidney, pancreatic, duodenal, lung, colorectal, ovarian, and gastric cancers. Crucially, based on molecular profiling, we identified exosomal deoxyadenosine triphosphate as a promising pan-cancer biomarker consistently upregulated across diverse tumor types. This discovery establishes a potential pan-cancer diagnostic marker, while the fully automated, scalable platform offers significant promise for clinical translation in early and differential cancer diagnosis. Diagnostic biomarker ; Cancer biomarkers ; Biomarker ; Cancer ; Exosome ; Diagnostic test ; Diagnostic accuracy ; Biomarker discovery ; Companion diagnostic Gold and Silver Nanoparticles Synthesis and Applications ; Extracellular vesicles in disease ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: S. J. Kim | Jongkwon Choi
Source: Buildings (article, 2025-10-10)
Field: Materials Science — Materials Chemistry

Electrochemical and Gravimetric Assessment of Steel Rebar Corrosion in Chloride- and Carbonation-Induced Environments This study investigates the corrosion performance of reinforced steel in concrete subjected to carbonation and chloride ingress. Four systems were examined: normal concrete (NC15), chloride-exposed (ClC15), carbonated (COC15), and chloride-exposed carbonated concrete (COClC15). A comprehensive assessment was carried out using electrochemical testing, gravimetric weight loss, chloride profiling, Temkin adsorption isotherm modeling, and SEM analysis. Electrochemical results showed a marked increase in corrosion activity under combined chloride–carbonation exposure. The highest corrosion current density (icorr) was obtained in COClC15 (0.4779 µA/cm2), compared with only 0.0106 µA/cm2 for NC15. Gravimetric analysis confirmed these findings, with COClC15 exhibiting a corrosion rate nearly 1.5 times greater than ClC15 and 52 times higher than NC15 after 120 days. Chloride profiling revealed reduced binding efficiency in carbonated concrete; at 5 mm depth, COClC15 bound only 0.06% chloride, while ClC15 retained 0.43%. The Temkin adsorption isotherm further quantified the weakened binding capacity. The binding coefficient (β) of COClC15 was considerably lower than ClC15 and NC15, reflecting the impact of C–S–H decalcification and aluminate phase transformation into carboaluminates, which restrict Friedel’s salt formation. SEM micrographs corroborated these observations, showing extensive microstructural degradation in COClC15. This study revealed that the synergy of carbonation and chloride ingress reduces chloride-binding capacity, accelerates depassivation, and severely compromises the durability of reinforced concrete in aggressive environments. Carbonation ; Gravimetric analysis ; Corrosion ; Chloride ; Electrochemistry ; Rebar Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Andrew Golabek | Nikhil K. Barua | Ehsan Niknam | Luke T. Menezes | Holger Kleinke
Source: Materials (article, 2025-01-14)
Field: Materials Science — Materials Chemistry

Large Improvements in the Thermoelectric Properties of SnSe by Fast Cooling As reported during the last five years, SnSe is one of the leading thermoelectric (TE) materials with a very low lattice thermal conductivity. However, its elements are not as heavy as those of classical thermoelectric materials like PbTe or Bi<sub>2</sub>Te<sub>3</sub>. Its outstanding TE properties were revealed after repeated purification steps to minimize the amount of oxygen contamination, followed by spark plasma sintering. Recently, we showed that hot-pressing-once optimized-can yield comparable or even better TE performance using the examples of Na- and Cu- as well as Na- and Ag-co-doped SnSe. However, long-term stability remains a challenge during cycling between low and high temperatures. Here, we investigated whether the cooling procedure has a significant impact on the thermoelectric properties of SnSe. We compared cooling of the melt with a 1:1 ratio of Sn:Se from 1273 K down to room temperature in air with quenching in water. As typical for undoped SnSe, both materials were extrinsic <i>p</i>-type semiconductors due to Sn defects. The air-quenched sample exhibited higher thermal conductivity, lower electrical conductivity, and higher Seebeck coefficient, all consistent with a smaller number of defects and thus a smaller number of charge carriers due to the slower cooling procedure. This resulted in a comparatively low peak figure-of-merit value <i>zT</i> of 0.61 at 823 K for the air-quenched sample, compared to the substantially higher peak <i>zT</i> of 1.58 at 813 K for the water-quenched sample. Spark plasma sintering ; Materials science ; Thermoelectric effect ; Seebeck coefficient ; Thermoelectric materials ; Thermal conductivity ; Figure of merit ; Electrical resistivity and conductivity ; Analytical Chemistry (journal) ; Semiconductor ; Quenching (fluorescence) ; Doping ; Composite material ; Sintering ; Optoelectronics ; Thermodynamics ; Chemistry ; Electrical engineering ; Optics Advanced Thermoelectric Materials and Devices ; Chalcogenide Semiconductor Thin Films ; Heusler alloys: electronic and magnetic properties
Authors: Oscar Hernán Franco Montoya | Luis Joel Martínez
Source: Agronomía Colombiana (article, 2025-04-30)
Field: Chemistry — Analytical Chemistry

Comparing spectral models to predict manganese content in Rosa spp. leaves using VIS-NIR data This study, conducted on the Freedom rose cultivar grown under greenhouse conditions in the municipality of Tocancipá, Cundinamarca (Colombia), implemented Partial Least Squares Regression (PLSR) and Principal Component Regression (PCR) methods using visible and near infrared (VIS-NIR) spectroradiometry from 350 to 2500 nm to predict manganese (Mn) content in rose leaves. A randomized complete block design (RCBD) with manganese doses of 0%, 25%, 50%, 75%, and 100% of the reference dose of 2 mg L-1 was established in 25 plots with five treatments and five replicates. Samplings were conducted in the five phenological stages of “palmiche”, “rice”, “chickpea”, “scratch color”, and “straight sepals”, analyzing 10 plants per treatment, and spectral responses were measured on the adaxial leaf surface using the FieldSpec® 4 spectroradiometer. For model generation (PLSR and PCR), 24 predictive models were evaluated, comprising three spectral response ranges: range 1 (350-1000 nm), range 2 (350-1800 nm), and range 3 (350-2500 nm), applying different spectral correction methods: raw data (RD), Savitzky-Golay (SG), range normalization (RN), and Savitzky-Golay followed by range normalization (SG-RN). A total of 100 samples were used: 80 for calibration and 20 for external validation, randomly selected to represent the variability of the treatments. The spectral corrections improved the accuracy and robustness of the predictions, with the RN-PLSR and SG-RN-PLSR models showing the best performance metrics (R², RMSE, and RPD). The most relevant wavelengths were 523 nm, 557 nm, and around 720 nm, with correlations greater than 0.6 with the Mn concentration in leaves. Manganese ; Content (measure theory) ; Horticulture ; Mathematics ; Artificial intelligence ; Computer science ; Chemistry ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Ma Hui | Lingmeng Hu | Jingyuan Zhao | Jie He | Aidong Wen | Daizhu Lv | Zhixiang Xu | Weijie Lan | Leiqing Pan
Source: Foods (article, 2025-04-11)
Field: Chemistry — Analytical Chemistry

Comparative Analysis of Chilling Injury in Banana Fruit During Storage: Physicochemical and Microstructural Changes, and Early Optical-Based Nondestructive Identification Chilling injury (CI) during postharvest storage seriously impairs bananas' quality and marketability. This study systematically investigated CI mechanisms through physicochemical, microstructural, and optical analyses and innovatively developed a hyperspectral imaging (HSI)-based approach for early CI detection. Bananas stored at suboptimal (7 °C) and optimal (13 °C) conditions exhibited distinct physicochemical changes. CI progression was related to increased browning symptoms, an abnormal moisture redistribution (reduced pulp moisture content), and delayed softening. Microstructural analysis revealed membrane destabilization, cellular lysis, intercellular cavity formation, and inhibited starch hydrolysis under chilling stress. Hyperspectral microscope imaging (HMI) captured chilling-induced spectral variations (400-1000 nm), enabling the t-SNE-based clustering of CI-affected tissues. Machine learning models using first derivative (1-st)-processed spectra achieved a high accuracy. Both PLS-DA and RF had a 99% calibration accuracy and 98.5% prediction accuracy for CI classification. Notably, HSI detected spectral signatures of early CI (2 days post-chilling treatment) before visible symptoms, achieving a 100% identification accuracy with an optimized PLS-DA combined with 1-st processing. This study provides a theoretical basis for studying fruit CI mechanisms and a novel nondestructive optical method for early CI monitoring in postharvest supply chains. Postharvest ; Hyperspectral imaging ; Browning ; Softening ; Horticulture ; Moisture ; Pulp (tooth) ; Materials science ; Lysis ; Food science ; Chemistry ; Biology ; Composite material ; Remote sensing ; Biochemistry ; Medicine Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Postharvest Quality and Shelf Life Management
Authors: Yifei Tu | Guozhang Wu
Source: Polymer Composites (article, 2025-08-08)
Field: Materials Science — Surfaces, Coatings and Films

Dispersion Analysis of Short Carbon Fibers in Two‐Phase Fluids ABSTRACT Dispersion of short fibers in two‐polymer mixtures is complex. Selective adsorption of polymer chains causes fibers either to aggregate into bundles or to preferentially distribute in one of the polymer phases, depending on the size and orientation of the polymer domain. To observe the process, we systematically investigated the morphology evolution of short carbon fibers in non‐polar paraffin oil upon the addition of a polar solvent, a mixture considered to be similar to carbon fiber dispersion in HDPE/PA6. Adding a small amount of formamide, the uniformly dispersed short fibers in paraffin oil gradually aggregate into a fibril network, as evidenced by a gradual increase in mixture viscosity. This is rationalized by the fact that many formamide drops preferentially segregate at the junction of two fibers due to capillarity. With increasing formamide loading, the capillary force between formamide and carbon fibers drives the fibers aggregation into bundles, and ultimately coagulation into big clusters. This process was confirmed by a gradual decrease in viscosity. Enhancing the shear rate and paraffin oil viscosity effectively suppresses bundle formation. Furthermore, adjusting the capillary force by matching the surface tension of the polar solvent facilitates morphology control from the fibril network to the bundle formation. Materials science ; Formamide ; Composite material ; Polymer ; Dispersion (optics) ; Surface tension ; Capillary action ; Viscosity ; Chemical engineering ; Solvent ; Fiber ; Phase (matter) ; Organic chemistry ; Chemistry ; Thermodynamics Surface Modification and Superhydrophobicity ; Fiber-reinforced polymer composites ; Polymer crystallization and properties