jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Debora Monego | Matthias Brosz | Johanna Buck | Vsevolod Viliuga | Paulius Greicius | Jaewoon Jung | Torsten Stuehn | Matthias Schmies | Yuji Sugita | Frauke Gräter
Source: Bioinformatics (article, 2025-04-30)
Field: Materials Science — Biomaterials

ColBuilder: flexible structure generation of crosslinked collagen fibrils ColBuilder is available both as an open-source command-line application and through a web interface at https://colbuilder.mpip-mainz.mpg.de. Fibril ; Collagen fibril ; Molecular dynamics ; Computer science ; Homology modeling ; Materials science ; Biological system ; Biophysics ; Chemistry ; Biology ; Computational chemistry Collagen: Extraction and Characterization ; Bone health and osteoporosis research
Authors: Simon T. Hackl | Caroline Jachmann | Mathias Witte Paz | Theresa Harbig | Lennart Martens | Kay Nieselt
Source: Journal of Proteome Research (article, 2025-01-08)
Field: Chemistry — Spectroscopy

PTMVision: An Interactive Visualization Webserver for Post-translational Modifications of Proteins Recent improvements in methods and instruments used in mass spectrometry have greatly enhanced the detection of protein post-translational modifications (PTMs). On the computational side, the adoption of open modification search strategies now allows for the identification of a wide variety of PTMs, potentially revealing hundreds to thousands of distinct modifications in biological samples. While the observable part of the proteome is continuously growing, the visualization and interpretation of this vast amount of data in a comprehensive fashion is not yet possible. There is a clear need for methods to easily investigate the PTM landscape and to thoroughly examine modifications on proteins of interest from acquired mass spectrometry data. We present PTMVision, a web server providing an intuitive and simple way to interactively explore PTMs identified in mass spectrometry-based proteomics experiments and to analyze the modification sites of proteins within relevant context. It offers a variety of tools to visualize the PTM landscape from different angles and at different levels, such as 3D structures and contact maps, UniMod classification summaries, and site specific overviews. The web server's user-friendly interface ensures accessibility across diverse scientific backgrounds. PTMVision is available at https://ptmvision-tuevis.cs.uni-tuebingen.de/. Computer science ; Context (archaeology) ; Visualization ; Posttranslational modification ; Proteome ; Variety (cybernetics) ; Identification (biology) ; Proteomics ; Interface (matter) ; Computational biology ; Web server ; Data science ; World Wide Web ; Human–computer interaction ; Bioinformatics ; Chemistry ; Data mining ; Biology ; The Internet ; Artificial intelligence Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: А.А. Щерба | O.D. Podoltsev | І.М. Кучерява | M.S. Hutorova | Lubomyr Petryshyn | Yuliya Pazynich
Source: Polityka Energetyczna – Energy Policy Journal (article, 2025-09-30)
Field: Materials Science — Materials Chemistry

Computer simulation and management of partial discharges in XLPE insulation of high-voltage power cable Computer simulation and management of partial discharges in XLPE insulation of Power cable ; Power (physics) ; Partial discharge ; Reliability (semiconductor) High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission ; Power Line Communications and Noise
Authors: Mohsen Rezahasani | Habib Amiri Savadroodbari | Milad Razbin | Majid Safar Johari
Source: Scientific Reports (article, 2025-05-29)
Field: Materials Science — Polymers and Plastics

Optimizing drawing frame variables to enhance polyester spun yarn quality using soft computing techniques This study explores optimizing the production of 100% polyester spun yarn by analyzing key drawing frame variables, such as break draft, total draft, back roller gauge, and front roller gauge, using a systematic and algorithmic approach. Response Surface Methodology (RSM) was employed to design the experiment and produce yarn samples. The yarn mass variation per unit length (CVm%) and the Imperfection Index (IPI), which includes the total count of thick places, thin places, and neps, were modeled using an Artificial Neural Network (ANN) and optimized with a Genetic Algorithm (GA). These two yarn quality responses significantly determine the appearance quality of textiles. Sensitivity analysis of the ANN models revealed that break draft was the most influential input variable, contributing 35.58% and 28.72% to the models for CVm% and IPI, respectively. The optimal drawing frame variables were determined as a break draft of 1.33, a total draft of 7, a back roller gauge of 60.5 mm, and a front roller gauge of 47.5 mm, yielding CVm% and IPI values of 11.91% and 22.82, respectively. This study integrates RSM, ANN, and GA to present a innovative approach for optimizing yarn spinning. The findings not only enhance yarn quality with greater precision and efficiency but also offer valuable insights applicable to broader textile manufacturing processes. Yarn ; Soft computing ; Frame (networking) ; Polyester ; Computer science ; Quality (philosophy) ; Soft tissue ; Engineering drawing ; Composite material ; Artificial intelligence ; Materials science ; Engineering ; Medicine ; Surgery Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Mechanical Engineering and Vibrations Research
Authors: Khaoula Loukili | Smail Imame | Mohammed Bakkali | Mohamed Lagseir | Mohamed Sadoq | Hafssa Atlas | Soukaina El Bourachdi | Amal Lahkimi | Fatima Boukhlifi
Source: E3S Web of Conferences (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Application of Box–Behnken Design for the Optimization of Crystal Violet Removal from Aqueous Solutions Using Acorn Waste from Quercus ilex This study explores the optimization of Crystal Violet (CV) dye removal from aqueous solutions using Quercus ilex acorn waste (AW), a natural and low-cost adsorbent. The Box–Behnken Design (BBD), a response surface methodology (RSM) approach, was employed to assess the effects of three primary operational variables: adsorbent mass, initial CV concentration, and temperature. The main objective was to maximize removal efficiency while minimizing operational costs. Seventeen experiments were conducted, and the results were modeled using a second-order polynomial equation. Analysis of variance (ANOVA) confirmed the statistical significance of the model ( p &lt; 0.0001), with a high coefficient of determination ( R 2 = 0.99), demonstrating strong predictive capability. Adsorbent mass and initial dye concentration positively influenced removal efficiency, whereas temperature had a negative influence. The optimal conditions for maximum removal were an initial CV concentration of 100 mg/L, an adsorbent dosage of 0.5 g/L, and a pH of 10. This study highlights the potential of AW as an effective and sustainable adsorbent for textile dye remediation and demonstrates the value of BBD in optimizing adsorption processes for environmental applications. Crystal violet ; Adsorption ; Response surface methodology ; Aqueous solution ; Environmental remediation ; Wastewater ; Contamination Pigment Synthesis and Properties
Authors: Kyra Lützel | Henryk Laqua | Manjima B. Sathian | Benedikt Nißl | Judit Katalin Szántó | Christina‐Anna Senser | Gökçen Savaşçı | Lars Allmendinger | Bilal Kicin | Vincent A. P. Ruf | Dominik Kammerer | Theobald Lohmüller | Konstantin Karaghiosoff | Ahmed M. Ali | Ursula Storch | Michael Mederos y Schnitzler | Christian Ochsenfeld | David B. Konrad
Source: Angewandte Chemie International Edition (article, 2025-06-04)
Field: Materials Science — Materials Chemistry

A Platform for the Development of Highly Red‐Shifted Azobenzene‐Based Optical Tools Azobenzenes are versatile photoswitches that can be used to generate elaborate optical tools, including photopharmaceuticals. However, the targeted application-guided design of new photoswitches with specific properties remains challenging. We have developed synthetic protocols for derivatives of the dfdc (di-ortho-fluoro-di-ortho-chloro) azobenzene scaffold with chemical alterations in the para-/ortho-positions and performed an in-depth study into the effects of their structures on their photophysical properties with an emphasis on the n → π* absorption band using NMR, UV-vis, and X-ray analysis. The data was used to establish and validate a computational approach that allows to compute realistic UV-vis spectra by combining TD-DFT excited-state calculations from 6000 thermally accessible structures generated through MD simulations while considering the high structural flexibility of ortho-substituted azobenzenes. We added 15 new visible light-operated photoswitches to the toolbox for the development of optical devices with relaxation rates across multiple orders of magnitude and identified several examples with stronger bathochromic shifts than the dfdc azobenzene lead structure. Our combined experimental and computational study forms the foundation for the advanced in silico design and synthesis of new highly red-shifted photoswitches. To showcase the potential of dfdc azobenzenes for the development of chemical tools, we synthesized dfdc-OptoBI-1 and demonstrated its biological activity as a red light-operated activator of TRPC6 channels in HEK293 cells. Azobenzene ; Computer science ; Nanotechnology ; Materials science Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Supramolecular Self-Assembly in Materials
Authors: Sotirios Tasioulas | Jessie Watson | Dimitrios S. Kasampalis | Pavlos Tsouvaltzis
Source: Agronomy (article, 2025-02-16)
Field: Chemistry — Analytical Chemistry

Integration of Color Analysis, Firmness Testing, and visNIR Spectroscopy for Comprehensive Tomato Quality Assessment and Shelf-Life Prediction This study evaluates the potential of integrating visible and near-infrared (visNIR) spectroscopy, color analysis, and firmness testing for non-destructive tomato quality assessment and shelf-life prediction. Tomato fruit (cv. HM1823) harvested at four ripening stages were monitored over 12 days at 22 °C to investigate ripening stage-specific variations in key quality parameters, including color (hue angle), firmness (compression), and nutritional composition (pH, soluble solids content, and titratable acidity ratio). Significant changes in these parameters during storage highlighted the need for advanced tools to monitor and predict quality attributes. Spectral data (340–2500 nm) captured using advanced and cost-effective portable spectroradiometers, coupled with chemometric models such as partial least squares regression (PLSR), demonstrated reliable predictions of shelf-life and nutritional quality. The near-infrared spectrum (900–1700 nm) was particularly effective, with variable selection methods such as genetic algorithm (GA) and variable importance in projection (VIP) scores enhancing model accuracy. This study highlights the promising role of visNIR spectroscopy as a rapid, non-destructive tool for optimizing postharvest management in tomato. By enabling real-time quality assessments, these technologies support sustainable agricultural practices through improved decision-making, reduced postharvest losses, and enhanced consumer satisfaction. The findings also validate the utility of affordable spectroradiometers, offering practical solutions for stakeholders aiming to balance cost efficiency and reliability in postharvest quality monitoring. Shelf life ; Quality (philosophy) ; Environmental science ; Quality assessment ; Agricultural engineering ; Biological system ; Food science ; Reliability engineering ; Chemistry ; Engineering ; Biology ; Evaluation methods ; Physics Spectroscopy and Chemometric Analyses
Authors: Shai Gertler | Zeyu Kuang | Colin Christie | Hao Li | Owen D. Miller
Source: Science Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Many photonic design problems are sparse QCQPs Photonic design is a process of mathematical optimization of a desired objective (beam formation, mode conversion, etc.) subject to the constraint of Maxwell's equations. Finding the optimal design is challenging: Generically, these problems are highly nonconvex and finding global optima is NP hard. Here, we show that the associated optimization problem can be transformed to a sparse-matrix, quadratically constrained quadratic program (QCQP). Sparse QCQPs can be tackled with convex optimization techniques (such as semidefinite programming) that have thrived for identifying global bounds and high-performance designs in many areas of science and engineering but seemed inapplicable to the design problems of wave physics. We apply our formulation to prototypical photonic design problems, showing the possibility to compute fundamental limits for large-area metasurfaces, as well as the identification of designs approaching global optimality. Our approach appears directly extensible to any design problem whose governing dynamics are bilinear differential equations, as arise in structural optimization, fluid dynamics, and quantum control. Quadratically constrained quadratic program ; Semidefinite programming ; Mathematical optimization ; Computer science ; Photonics ; Optimization problem ; Quadratic growth ; Global optimization ; Quadratic programming ; Mathematics ; Algorithm ; Physics Metamaterials and Metasurfaces Applications ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Boxue Chang | Zhen Li | Kaidi Ji | Yinlan Ruan | Rukuan Liu
Source: Processes (article, 2025-02-08)
Field: Chemistry — Analytical Chemistry

Rapid Quantitative Determination of Adulteration of Camellia Oil Using Portable Raman Spectroscopy and Chemometrics Over the past decade, Raman spectroscopy and chemometrics have been extensively utilized in the food industry for the research and development of new products but have failed to establish a strong foothold in quality control and the assessment of food items. To bridge this gap, we introduce a novel application of Raman spectroscopy capable of swiftly identifying free fatty acids (FFAs) in cooking oil and quantifying adulteration. This advanced method was validated using camellia oil, a highly esteemed cooking oil in China and various Asian countries known for its nutritional richness and diverse culinary applications. With its growing popularity among high-end food consumers in Asia, camellia oil has increasingly become a target for adulteration, causing dissatisfaction among both consumers and genuine producers. In this study, we employed Raman spectroscopy to characterize the FFA profiles of cooking oil samples, complemented by principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) for sample categorization and adulteration detection in camellia oil. By segregating camellia oil from other vegetable oils and differentiating genuine from adulterated samples using the partial least squares (PLS) method, we achieved a high determination coefficient (R2) of over 0.98 and a low root mean square error of prediction (RMSEP) of less than 1.45%. These findings offer a robust predictive model for rapid camellia oil adulteration assessment, potentially augmenting traditional qualitative tests and streamlining sampling procedures in the food industry. Chemometrics ; Partial least squares regression ; Camellia ; Food science ; Linear discriminant analysis ; Mathematics ; Principal component analysis ; Chemistry ; Statistics ; Chromatography ; Botany ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Gyeong-Yeol Lee | Gyung‐Suk Kil
Source: Electronics (article, 2025-05-09)
Field: Materials Science — Materials Chemistry

Insulation Defect Diagnosis Using a Random Forest Algorithm with Optimized Feature Selection in a Gas-Insulated Line Breaker Fault diagnosis based on the partial discharge (PD) recognition has been widely applied on a gas-insulated line breaker (GILB) and gas-insulated switchgear (GIS) as a reliable online condition monitoring method. This paper dealt with insulation defect diagnosis based on a Random Forest (RF) algorithm with an optimized feature selection method. Four different types of insulation defect models, such as the free-moving particle (FMP) defect, the protrusion-on-conductor (POC) defect, the protrusion-on-enclosure (POE) defect, and the delamination defect, were prepared to simulate representative PD single pulses and PRPD patterns generated from the GILB. The PD signals generated from defect models were detected using the PRPD sensor which can detect phase-synchronized PD signals with the applied high-voltage (HV) signals without the need for additional equipment. Various statistical PD features were extracted from PD single pulses and PRPD patterns according to four kinds of PD defect models, and optimized features were selected with respect to variance importance analysis. Two kinds of PD datasets were established using all statistical features and top-ranked features. From the experimental results, the RF algorithm achieved accuracy rates exceeding 92%, and the PD datasets using only half of the statistical PD features could reduce the computational times while maintaining the accuracy rates. Circuit breaker ; Line (geometry) ; Selection (genetic algorithm) ; Random forest ; Feature selection ; Feature (linguistics) ; Algorithm ; Computer science ; Engineering ; Nuclear engineering ; Electrical engineering ; Mathematics ; Artificial intelligence High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrical Fault Detection and Protection
Authors: Jordy Peeters | Pieter De Gauquier | Fardine Ameli | Yvan Vander Heyden | Debby Mangelings | Kenno Vanommeslaeghe
Source: PLoS ONE (article, 2025-10-17)
Field: Chemistry — Spectroscopy

Development of Ensemble Steric and Electrostatic Chirality (ESEC) descriptors for modelling chromatographic enantioseparations In this work, chiral molecular descriptors were defined using 2 distinct approaches: (1) scalar triple products of vectorial molecular properties, and (2) descriptors that attempt to quantify the amount of twist in the overall molecular shape. Because both approaches give rise to conformation dependence, descriptor values were averaged over a conformational ensemble obtained by Molecular Dynamics. In addition, a method is introduced that attempts to quantify the asymmetry of the distribution of the descriptor values over the conformational ensemble. The totality of the resulting descriptors were named "Ensemble Steric and Electrostatic Chirality (ESEC) descriptors". A pilot validation study was performed by building Quantitative Structure-Enantioselectivity Relationships (QSER), i.e. mathematical models to predict the chromatographic separation of enantiomers, using a test set of 43 structurally diverse pharmaceuticals analyzed on a polysaccharide-based chiral stationary phase. The best linear regression model (7 descriptors) for the chiral separation (expressed as selectivity factor) featured a low leave-one-out cross validation error (0.0814), a well-predicted elution sequence of the separated enantiomers (21 out of 23 molecules) and a well-predicted αRS for 27 out of 42 molecules. To the best of our knowledge, this is the first time that acceptable linear QSER models were obtained for chiral chromatographic separations of such a chemically diverse set of pharmaceuticals. Steric effects ; Enantiomer ; Chirality (physics) ; Molecular descriptor ; Elution ; Molecular model ; Quantitative structure–activity relationship ; Linear regression Analytical Chemistry and Chromatography ; Molecular spectroscopy and chirality ; Chromatography in Natural Products
Authors: Heyu Wang | Zhonglei Li | Guoning Sun | Boxue Du
Source: High Voltage (article, 2025-09-18)
Field: Materials Science — Materials Chemistry

Optical Imaging‐Based 3D Reconstruction of Electrical Tree in Polypropylene Cable Insulation Under Mechanical Bending ABSTRACT This study proposes a nondestructive optical imaging‐based three‐dimensional (3D) reconstruction method to analyse electrical tree propagation in polypropylene (PP) cable insulation under mechanical bending. The technique combines focus‐stacked optical imaging with a feature fusion algorithm to segment in‐focus regions across depth layers, enabling 3D reconstruction of electrical trees in PP homopolymer (PPH), block copolymer (PPB) and elastomer‐blended (PP/TPE) samples. The results demonstrate that mechanical bending accelerates electrical tree propagation in PPH, and that degradation channels transition from a branch‐like to a straight‐stick morphology, tending to grow directionally towards stretched regions. With a bending radius of 10 mm, the breakdown time drops from 297.0 min for the undeformed samples to 6.3 min. PPB and PP/TPE delay the time to breakdown by 70.6% and 171.2%, respectively, highlighting their superior resistance under bending stress, which is attributed to maintaining elasticity rather than yield deformation under bending stresses. This study provides a novel tool for evaluating the electrical tree resistance of PP composites under the mechanical stress, guiding the development of recyclable high‐voltage direct current cable insulation. Bending ; Electrical resistance and conductance ; Polypropylene ; Bend radius ; Tree (set theory) ; Deformation (meteorology) ; Elasticity (physics) ; Sheet resistance High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Surface Roughness and Optical Measurements
Authors: Ki Hyun Nam
Source: Crystals (article, 2025-01-22)
Field: Materials Science — Materials Chemistry

Temperature-Dependent Structural Changes of the Active Site and Substrate-Binding Cleft in Hen Egg White Lysozyme Lysozyme plays a crucial role in the natural immune system, protecting against invading bacteria or viruses. The room-temperature (RT) structure of lysozymes is important for understanding accurate structural information compared to the crystal structure determined at cryogenic temperature. Several RT structures of lysozymes are determined by serial crystallography, but their temperature-dependent structural properties are not fully elucidated. To better understand the temperature-dependent structural change, the RT and cryogenic temperature structures of hen egg white lysozyme (HEWL) were determined by serial synchrotron crystallography (SSX) and macromolecular crystallography (MX), respectively. Structural comparisons of HEWLRT and HEWLCryo showed that the positions of the loops above the substrate-binding cleft of HEWL differed. The width of the substrate-binding cleft between the α- and β-domains of HEWLRT was wider than that of HEWLCryo. The distance between the two catalytic residues Glu53 and Asp70 and their interaction with neighbor residues and water molecules showed the distant between HEWLRT and HEWLCryo. Due to temperature, the subtle movements of the active site and substrate-binding cleft of HEWL led to different docking results for N-acetylglucosamine and N,N′,N″-triacetylchitotriose. These results will provide useful information to more accurately understand the molecular function of HEWL and insights into the temperature effects for ligand design. Lysozyme ; Egg white ; Active site ; White (mutation) ; Substrate (aquarium) ; Binding site ; Chemistry ; Biophysics ; Crystallography ; Biology ; Biochemistry ; Enzyme ; Ecology Enzyme Structure and Function ; Biochemical effects in animals ; Protein Structure and Dynamics