jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Louis Hellequin | Vicent J. Borràs | Patrick Romann | Nandita Vishwanathan | Jonathan Souquet | Thomas K. Villiger
Source: Analytical and Bioanalytical Chemistry (article, 2025-07-08)
Field: Chemistry — Analytical Chemistry

Synthetic spectral libraries for Raman model calibration Raman spectroscopy has become increasingly popular in the process analytical technology (PAT) landscape due to its versatility and predictive capability in bioprocesses. However, model building remains a time-consuming and cost-intensive task. Building upon a fast calibration workflow based on physical pure compounds spiking in water, this work explores the novel use of in silico spiking of pure spectral fingerprints of various analytes. Through data fusion, a synthetic spectral library (SSL) is created that combines base spectra information from mammalian cell culture runs with matrix variability, as well as pure component spectra in water, aiming to greatly reduce the cost and time required for efficient model building. The findings indicate that the in silico addition of pure compounds provides spectral information comparable to physically spiked measurements. Consequently, this approach allows for the generation of an extensive number of information-rich spectra, forming a robust foundation for various regression algorithms and enhancing Raman calibration of existing spectral databases. Calibration ; Workflow ; Raman spectroscopy ; Computer science ; Biological system ; Matrix (chemical analysis) ; Analyte ; Process (computing) ; Chemometrics ; Component (thermodynamics) ; Sensor fusion ; Process engineering ; Biochemical engineering ; Data mining ; Chemistry ; Artificial intelligence ; Machine learning ; Database ; Engineering ; Mathematics ; Physics ; Chromatography ; Optics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Viral Infectious Diseases and Gene Expression in Insects
Authors: Rachel Lusy Karenza | Adanti Wido Paramadini | Muhammad Yusro
Source: Journal of Energy Mechanical Material and Manufacturing Engineering (article, 2025-12-05)
Field: Materials Science — Biomaterials

Establishing Polylactic Acid (PLA)-Collagen-Polyvinyl Alcohol (PVA) nanofiber structure as an alternate vascular path membrane This research aimed at fabricating membrane vascular patches based on PLA and Collagen. Although various studies have reported the use of PLA and PVA nanofibers for soft tissue applications, as well as collagen for enhancing biocompatibility, few studies have comprehensively evaluated the three-component combination of PLA‑collagen‑PVA in a porous structure specifically designed as a vascular pathway membrane. PVA is a nontoxic and electrospinnable polymer. It is implemented as a carrier polymer. Membrane fabrication with 90/10, 80/20, 70/30, and 60/40 ratios has been tested. Characterisation using FTIR, degradability, and SEM has been conducted. Based on the results, the best-recommended composition is 80/20. The results of the FTIR test show that the C=O group at 1,634.00 cm-1 peak, and C-H at 2,930.19 cm-1 peak indicate the presence of PLA as a characteristic of its molecular structure. As a protein, collagen includes amide I and C-O groups at the 1,077.62 cm-1 peak. It is typical for protein structures. PVA contains an O-H group detected at the 3,295.09 cm-1 peak. The degradability test promises results in the same degradation rate as the regeneration process of vascular cells. With a degradation rate of 0.0001 g per day, a 90/10 ratio sample will be thoroughly degraded on the 110th day. It corresponds to the vascular regeneration process in 3-6 months. The 80/20 sample degrades more slowly, and the diameter reaches 497.50 ± 53.82 nm in the SEM test. Thus, vascular patch membrane fabrication is a suitable and effective therapeutic alternative for the CHD. Membrane ; Nanofiber ; Polylactic acid ; Fabrication ; Degradation (telecommunications) ; Electrospinning ; Biocompatibility ; Vascular tissue ; Porosity Electrospun Nanofibers in Biomedical Applications ; Collagen: Extraction and Characterization ; Nanocomposite Films for Food Packaging
Authors: Anna Pietrenko‐Dabrowska | Sławomir Kozieł
Source: Scientific Reports (article, 2025-11-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Variable-fidelity EM analysis and simplex-anchored regression surrogates for efficient global optimization of microwave passive circuits Formal optimization is nowadays ubiquitous in microwave design. It is frequently conducted using electromagnetic (EM) simulations, which guarantee dependability. Yet, it is computationally expensive. Local tuning may involve hundreds of system analyses, whereas global EM-driven optimization typically generates unmanageable expenses. However, global search is often imperative, for example, in design of miniaturized components, large-scale operating frequency re-design, problems with multiple local optima (design of metasurfaces or frequency selective surfaces). This study suggests a procedure for low-cost globalized optimization of microwave circuits. Its keystones are simplex-based regression surrogates constructed to represent the circuit's operating parameters. Geometrical simplicity of the surrogate and only a slightly nonlinear relation between the circuit dimensions and operating parameters, as well as conducting global search using low-resolution EM simulations, lead to a remarkable cost efficiency of the algorithm. Meanwhile, the assumed simplex updating rules guarantee convergence. The reliability is secured by a supplementary fine tuning executed using high-resolution EM models. As demonstrated, the presented framework exhibits perfect success rate with satisfactory designs found in each algorithm run out of multiple instances executed. The cost is just sixty high-resolution EM analyses, whereas design quality is competitive over the benchmark methods. Benchmark (surveying) ; Global optimization ; Reliability (semiconductor) ; Microwave ; Surrogate model ; Nonlinear system ; Optimization problem ; Electronic circuit ; Quality (philosophy) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Optimization
Authors: Puja Das | Prakash Kumar Nayak | Radha krishnan Kesavan
Source: Sustainable Food Technology (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Kinetic and thermodynamic characterization of thermosonication-assisted extraction of bioactives from lapsi fruit juice optimized by ANN-GA Thermosonication resulted in the enhancement of nutritional &amp; functional attributes of lapsi fruit juice. Kinetic studies revealed that the thermosonication-based extraction followed a pseudo-second-order model, demonstrating high R 2 &amp; low χ 2 values. Extraction (chemistry) ; Fruit juice ; Characterization (materials science) ; Kinetic energy ; Chemistry ; Food science ; Chromatography ; Materials science ; Nanotechnology ; Physics Spectroscopy and Chemometric Analyses ; Microbial Inactivation Methods ; Sensory Analysis and Statistical Methods
Authors: Walter Polilli | Angelica Galieni | Fabio Stagnari
Source: Remote Sensing (article, 2025-05-28)
Field: Chemistry — Analytical Chemistry

Nitrate Content in Open Field Spinach, Applicative Case for Hyperspectral Reflectance Data Spinach, leafy vegetables with growing demand and high nutritional value, has a heightened focus on nitrate content. An open-field experiment evaluated the potential of vis-NIR-SWIR hyperspectral data for classifying spinach nitrate content. Shallow artificial neural networks (ANN) and ensemble techniques—majority voting (MV) and stacked generalization (stacked)—were applied. The competitive adaptive reweighted sampling (CARS), its stability version (SCARS), Elastic Net, and modified boosted versions of each (CARSplus, SCARSplus, and ENplus) were used as feature selection methods. ANNs were optimized for hidden layer size. The resulting models were further used in ensemble techniques by grouping them into two sets: one with all models and another with models trained using the three boosted feature selection subsets (fifty-three wavelengths). The best-performing ANNs were based on the SCARS, SCARSplus, and full datasets, achieving an accuracy (Acc) of 0.83. While the majority voting approach did not improve performance (Acc 0.82), the stacked ensemble models reached Acc 0.88. Notably, stacked performed well also with models trained on 53 wavelengths, demonstrating strong potential for transferability as the required sensors would be less complex than those used in this study. Furthermore, a simulation of the practical application was conducted using Italian Ministry of Health official data with the scope of showing a potential use case in improving nitrate management and for advancing efficient farming practices in agriculture. The stacked models demonstrated their utility in doubling the monitoring capacity for internal quality assurance in spinach farming within a regulated framework. Hyperspectral imaging ; Spinach ; Reflectivity ; Nitrate ; Remote sensing ; Field (mathematics) ; Environmental science ; Geology ; Mathematics ; Optics ; Chemistry ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Shigenori Ogihara
Source: Open Journal of Geology (article, 2025-01-01)
Field: Materials Science — Biomaterials

Characteristics of Fluorescent Inclusions in Quartz Crystals Hosted by Organic-Rich Black Limestone in Sakawa Town, Kochi Prefecture, Southern Shikoku, Japan The Torinosu Limestone in Sakawa Town, Kochi Prefecture, Japan, is rich in organic matter and has long been recognized as a black limestone with a high concentration of organic material. Quartz containing petroleum-like substances occurs in veins within this black limestone. The quartz hosting these petroleum-like fluid inclusions typically exhibits a bipyramidal to tabular habit. Under ultraviolet light, the fluid inclusions display intense fluorescence. The polycyclic aromatic hydrocarbon (PAH) fraction extracted from the fluorescent quartz contains significant amounts of methylnaphthalene and methylphenanthrene, which are responsible for the observed fluorescence. In addition to these compounds, unsubstituted pyrene, chrysene, and perylene were detected in the black limestone. Methylnaphthalene, methylphenanthrene, and squalene—the primary fluorescent components—were likely derived from the organic-rich black limestone during the formation of the quartz veins and subsequently incorporated into the quartz. Quartz ; Fluid inclusions ; Fluorescence ; Ultraviolet ; Perylene ; Hydrocarbon Clay minerals and soil interactions ; Mineralogy and Gemology Studies ; Building materials and conservation
Authors: Md Riad Hossain Sabuj | M I S Hossain | M A Toma | M M Khan | A K Mondal
Source: Bangladesh Journal of Scientific and Industrial Research (article, 2025-12-28)
Field: Materials Science — Biomaterials

Color enhancement of chrome tanned goat leathers using aqueous tea extracts as dyeing agent The leather industry is undergoing a transformative shift towards sustainable practices due to increasing environmental concerns associated with synthetic dyes. This research explores the potential of natural dyes derived from tea extracts as an eco-friendly alternative for leather dyeing. In this study, the aqueous extracts of dried commercial tea leave (Camellia Sinensis) (10%, 12%, and 15% w/v) with and without mordant were used for dyeing of chrome tanned goat leathers and its color intensity parameters were examined using Milton Roy Colormate HDS spectrophotometer. In addition, the quality of dyed leather was evaluated by dye exhaustion test, fastness test, tensile strength test, scanning electronic microscopy (SEM) imaging, and thermogravimetric analysis. The optimized application of dye extract was 12% (without mordant) showed better color intensities (L* = 56.33 ± 0.57, DL* = -13.74 ± 0.48), highest dye exhaustion (84.68 ± 0.06%), tensile strength (18.75 ± 0.25), and residual mass in TGA, better color fastness (wet-4/5, dry-4/5, perspiration-3/4, and light fastness-4/5 in Grey Scale rating), and best fiber orientation in SEM image. In addition, another optimized was (with mordant) 15% dye extract with 1% Copper (II) Sulphate produced the highest color intensity (L* = 51.21± 1.06, DL* = -18.86±0.72). These findings offer the potential of tea extracts as a viable solution for natural leather dyeing, offering both environmental and aesthetic benefits. Bangladesh J. Sci. Ind. Res. 60(4), 251-262, 2025 Dyeing ; Mordant ; Ultimate tensile strength ; Aqueous solution ; Natural dye ; Thermogravimetric analysis Collagen: Extraction and Characterization ; Dyeing and Modifying Textile Fibers ; Biological Stains and Phytochemicals
Authors: Shun Sato | Issei Sato
Source: arXiv (Cornell University) (preprint, 2025-05-28)
Field: Materials Science — Materials Chemistry

Can Test-time Computation Mitigate Reproduction Bias in Neural Symbolic Regression? Mathematical expressions play a central role in scientific discovery. Symbolic regression aims to automatically discover such expressions from given numerical data. Recently, Neural symbolic regression (NSR) methods that involve Transformers pre-trained on synthetic datasets have gained attention for their fast inference, but they often perform poorly, especially with many input variables. In this study, we analyze NSR from both theoretical and empirical perspectives and show that (1) ordinary token-by-token generation is ill-suited for NSR, as Transformers cannot compositionally generate tokens while validating numerical consistency, and (2) the search space of NSR methods is greatly restricted due to reproduction bias, where the majority of generated expressions are merely copied from the training data. We further examine whether tailored test-time strategies can reduce reproduction bias and show that providing additional information at test time effectively mitigates it. These findings contribute to a deeper understanding of the limitation of NSR approaches and provide guidance for designing more robust and generalizable methods. Code is available at https://github.com/Shun-0922/Mem-Bias-NSR . Artificial neural network ; Computation ; Transformer ; Code (set theory) ; Regression ; Symbolic regression ; Empirical research Machine Learning in Materials Science ; Evolutionary Algorithms and Applications ; Generative Adversarial Networks and Image Synthesis
Authors: Micha J. Birklbauer | Louise Marie Buur | Sabrina Kaser | Fränze Müller | Manuel Matzinger | Karl Mechtler | Stephan Winkler | Viktoria Dorfer
Source: bioRxiv (Cold Spring Harbor Laboratory) (article, 2025-12-22)
Field: Chemistry — Spectroscopy

Unified down-stream analysis of crosslinking mass spectrometry results with pyXLMS Abstract Crosslinking mass spectrometry has become the method of choice for the identification of protein–protein interactions and for gaining insight into the structures of proteins in vivo . However, connecting crosslink search engine results with down-stream analysis tools, and therefore gaining biological insight from crosslink identifications, has remained a manual and cumbersome step in the analysis that often requires expert bioinformatics knowledge. Here we introduce pyXLMS, a python package and public web application which aims to simplify and streamline this intermediate step, enabling researchers even without bioinformatics knowledge to conduct in-depth crosslink analyses. In its current state pyXLMS supports input from seven different crosslink search engines, as well as the mzI-dentML format of the HUPO Proteomics Standards Initiative. Down-stream analysis is facilitated by functionality that is directly available within pyXLMS such as aggregation, validation, annotation, filtering, and visualization. In addition, the data can easily be exported to more than ten supported down-stream analysis tools and formats. We demonstrate the applicability and benefits of pyXLMS by re-analyzing a publicly available crosslink dataset with a variety of different search engines and show how the same data analysis workflow can be applied using pyXLMS. pyXLMs is available via https://github.com/hgb-bin-proteomics/pyXLMS . Workflow ; Python (programming language) ; Mass spectrometry ; Search engine ; Data exploration ; Identification (biology) ; Variety (cybernetics) ; State (computer science) Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Biotin and Related Studies
Authors: Zekai Yuan | Junjie Zeng | Hao An | Lan Meng | Xiaohong Yan
Source: Journal of Applied Physics (article, 2025-10-15)
Field: Materials Science — Materials Chemistry

Low-energy-barrier ferroelectric in monolayer CdX (X = Se and Te) and their potential applications in electrical device and photocatalyst: A first-principles study Ferroelectric materials exhibit switchable spontaneous polarization and provide significant potential in advanced electronics. This study employs density functional theory to investigate two-dimensional (2D) CdX (X = Se and Te) monolayers, which possess an asymmetric buckled structure leading to out-of-plane spontaneous polarization. The results show that both CdSe and CdTe monolayers are semiconductors with favorable bandgaps (1.35 and 1.32 eV) and exhibit spontaneous polarizations of 9.13 and 9.27 pC/m, respectively. The energy barriers of CdSe and CdTe monolayers are very low (17 and 57 meV) and their polarization direction can be switched by applying a low electric field of ∼0.3 V/Å. At a thickness of 4 nm, CdSe and CdTe monolayers possess tunneling electroresistance of 7.18 and 6.44, respectively, revealing significant potential for ferroelectric tunnel junction applications. Furthermore, the strong redox capability of photogenerated carriers endows CdX (X = Se and Te) monolayers well-suited for photocatalytic applications in all acid–base solutions (pH = 0–14). These results reveal that CdX (X = Se and Te) monolayers are remarkable ferroelectrics for applications in nanoelectronics and photocatalysts. Monolayer ; Nanoelectronics ; Ferroelectricity ; Semiconductor ; Cadmium telluride photovoltaics ; Polarization (electrochemistry) ; Quantum tunnelling Ferroelectric and Piezoelectric Materials ; 2D Materials and Applications ; Electronic and Structural Properties of Oxides
Authors: Ігор Невлюдов | I.V. Gurin | V.Ye. Ovcharenko | О. Токарєва
Source:  (article, 2025-10-13)
Field: Materials Science — Materials Chemistry

INVESTIGATION OF ELECTRICAL THERMAL NOISE OF C/C COMPOSITES IN A HIGH-TEMPERATURE VACUUM CHAMBER The electrical thermal noise properties of carbon-carbon composite materials have been investigated. The results of studying the effect of thermal influence on the magnitude of Johnson thermal noise in a 10- resistor made of carbon-carbon composite material in the frequency range up to 1 MHz at temperatures up to 3000 K in a thermal vacuum chamber are presented. Recommendations are provided regarding the application of noise thermometry in nuclear reactors. Thermal ; Noise (video) ; Resistor ; Composite number ; Range (aeronautics) ; Y-factor ; Vacuum chamber Graphite, nuclear technology, radiation studies ; Advanced Energy Technologies and Civil Engineering Innovations ; Advanced Electrical Measurement Techniques
Authors: Fathima Begum M | V. S. K. Reddy | Lokesh Reddy.K
Source: International Research Journal of Innovations in Engineering and Technology (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Early Price Prediction of Crops Using Machine Learning Model The agriculture sector is a cornerstone of India’s economy, contributing as the third-largest GDP sector and supporting the livelihoods of millions. While farmers in India have extensive knowledge of climate conditions and crop suitability, they often face significant investment losses due to over production of specific crops, leading to low market prices. This overproduction is frequently driven by a lack of accurate price forecasting and guidance on crop selection. To address this challenge, machine learning (ML) techniques can be leveraged to predict optimal crops for cultivation and their base market prices. By analysing historical data, market trends, and environmental factors, these advanced models can provide actionable insights to farmers, help farmers increase profits, thereby reducing losses. This approach ensures informed decision-making, minimizes risks, and promotes sustainable economic growth in the agriculture sector. Machine learning ; Computer science ; Artificial intelligence ; Agricultural engineering ; Engineering Spectroscopy and Chemometric Analyses ; Evolutionary Algorithms and Applications ; Smart Agriculture and AI
Authors: Andreas W. Götz | W. J. Schmidt | Volkmar Senz | Niels Grabow | Sabine Illner
Source: Current Directions in Biomedical Engineering (article, 2025-09-01)
Field: Materials Science — Biomaterials

Methods for characterization of nanofiber nonwovens for biomedical applications – overview and future demands Abstract Nanofiber nonwovens are of increasing significance in the field of biomedical applications. Knowledge of material characteristics is a fundamental requirement for the development of safe medical devices. A variety of suitable methods are required for process monitoring and to analyze material parameters. We consider and reflect specific features of selected methods like microscopy, scattering techniques or porosimetry. Potential methodological demand is discussed. A brief literature based overview is provided regarding to characterization methods for in situ or post process routines. Upcoming demands are derived from existing gaps in the spectrum of methods. Possible potential concepts for new optical techniques that can be designed and implemented in prospect technologies are introduced and discussed. The authors are actively working on method development regarding to material characterization and process monitoring. Characterization (materials science) ; Process (computing) ; Variety (cybernetics) ; Field (mathematics) ; Process development Electrospun Nanofibers in Biomedical Applications ; Textile materials and evaluations ; Polymer Nanocomposite Synthesis and Irradiation