jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Raju Potharaju | K. Nageshwara Rao | B Reddy | M. Aruna
Source: Acta Botanica Plantae (article, 2025-10-13)
Field: Materials Science — Materials Chemistry

Algae: A Prospective Source for Nanoparticle Production with Some Potential Applications and Limitations In order to achieve a large-scale circular economy, it is necessary to create environmentally friendly alternatives to the traditional physicochemical pathways for nanomaterials, which pose risks to the environment. You may use algae from the Cyanophyceae, Chlorophyceae, Phaeophyceae, and Rhodophyceae families as nanomachinery. These algae can synthesize metallic nanoparticles, such as gold (Au), silver (Ag), and others, both within and outside of their cells. A variety of biocompatible reductants, including pigments and antioxidants, are found in algae cell extracts, which make them an attractive platform for the manufacture of nanomaterials. Nanoparticles having antibacterial characteristics, possibly replacing current antibiotics, have been thoroughly investigated in Chlorella and Sargassum spp. We used state-of-the-art spectroscopic, diffractographic, and microscopic techniques, such as UV-Vis FT-IR, DLS, XPS, XRD, SEM, TEM, AFM, HR-TEM, to characterize nanoparticles (NPs) made from algae. Algae ; Biocompatible material ; Nanoparticle ; Sargassum ; Environmentally friendly ; Chlorella Nanoparticles: synthesis and applications ; Algal biology and biofuel production ; Diatoms and Algae Research
Authors: Claudia-Olimpia Stasac | Andrei-Dan Tomșe | T. Costea | Livia Bandici | Mircea-Nicolae Arion | Francisc-Ioan Hathazi
Source: Processes (article, 2025-06-11)
Field: Materials Science — Polymers and Plastics

Accelerated Aging Process of Carbon Black-Reinforced PVC (CB-PVC) Insulation by UVB-Induced Chemical Degradation This study examines the UVB-induced (Ultraviolet B radiation) degradation of carbon black-filled polyvinyl chloride (CB-PVC) composites. After 500 h of exposure, the material exhibited a 30.13% drop in dielectric strength, a 27.6% increase in surface roughness, and significant pit formation, indicating substantial physicochemical deterioration. Degradation followed a triphasic kinetic pattern: an initial induction phase, an autocatalytic acceleration, and a stabilization phase, driven by radical propagation and photo-oxidation. These findings highlight the complex role of UVB in the photodegradation of cable sheeting. Degradation (telecommunications) ; Carbon black ; Accelerated aging ; Plasticizer ; Materials science ; Composite material ; Polyvinyl chloride ; Pulp and paper industry ; Chemical engineering ; Natural rubber ; Engineering ; Electrical engineering Polymer Science and PVC ; Microplastics and Plastic Pollution ; Effects and risks of endocrine disrupting chemicals
Authors: Talgat Kaiym | Аmandyk Tuleshov | Askar Seidakhmet | Suleimen Kaimov | Aidarkhan Kaimov | Abylay Kaimov | Azil Zamanbek | Yelaman Abussagatov | Aliman Alibek | Kaiyrtay Issabayev
Source: Eastern-European Journal of Enterprise Technologies (article, 2025-08-28)
Field: Materials Science — Materials Chemistry

Justification of a dual ventilation system for the complete burial of high-level radioactive waste in spent open mines The complete burial of high-level radioactive waste (HLW) in spent open mines presents a promising solution to long-term waste isolation. This study presents the justification and design of an innovative dual ventilation system aimed at regulating heat and removing gas-dust mixtures from such repositories. The ventilation system is designed to control dust-gas emissions and thermal loads through a two-chimney configuration, enabling efficient gas extraction and convective cooling. A system of main and additional chimneys is proposed: the main chimney channels the rising hot gas-dust mixture, while the additional chimney processes it through a staged treatment system before final disposal. Mathematical modeling, including Fourier’s Law, Darcy’s Law, and Fick’s Law, supports the thermal, hydraulic, and gas dynamics simulations. The study demonstrates that with adequate ventilation flow and composite-layer insulation, internal repository temperatures can be reduced from 300°C to below 100°C within 30 years, significantly lowering the risk of container degradation and gas-induced particle mobilization. The integrated system improves the safety, observability, and long-term reliability of HLW burial in open spent mines, offering a scalable and internationally compliant solution. Through a combination of temperature distribution modeling, structural analysis, and airflow simulations, the system's viability is demonstrated. The results show that the proposed ventilation configuration provides effective thermal regulation, structural resilience under stress, and compatibility with repurposed mining infrastructure. The study contributes a scalable, energy-efficient solution to HLW (High-level radioactive waste) repository management, paving the way for safer and more sustainable nuclear waste isolation High-level waste ; Radioactive waste ; Waste management ; Ventilation (architecture) ; Dual (grammatical number) ; Environmental science ; Dual purpose ; Open air ; Mining engineering ; Engineering ; Architectural engineering ; Art Graphite, nuclear technology, radiation studies ; Nuclear and radioactivity studies
Authors: Ritaban Dutta | Michael Kellam | Daniel Liang
Source: Research Square (preprint, 2025-11-20)
Field: Materials Science — Materials Chemistry

AI-enabled Monitoring of Planar-Flow Casting of Amorphous Steel Foils Robustness (evolution) ; FOIL method ; Amorphous solid ; Fusion ; Thermal ; Infrared ; Casting ; Amorphous metal Solidification and crystal growth phenomena ; Metallurgical Processes and Thermodynamics ; Machine Learning in Materials Science
Authors: Gabriel C. Gauthier | Micah Summerlin | Balasrinivasa R. Sajja | Mariano Uberti | Emma G. Foster | Manjeet Kumar | Martina Thiele | Santhi Gorantla | Aditya N. Bade | Y. Liu
Source: NeuroImmune Pharmacology and Therapeutics (article, 2025-12-27)
Field: Materials Science — Materials Chemistry

CEST MRI assessment of HIV-1-associated neurometabolic impairments in a humanized mouse model CEST MRI detects region-specific metabolic abnormalities during HIV-1 infection and region-specific metabolic recovery with ART, consistent with reduced viral burden and neuroinflammation. These findings support CEST MRI as a promising non-invasive biomarker for monitoring treatment response and disease progression in neuroHIV. Humanized mouse ; Magnetic resonance imaging ; Biomarker ; Disease Lanthanide and Transition Metal Complexes ; HIV Research and Treatment ; MRI in cancer diagnosis
Authors: Remco Geurts | Pavel Potocek
Source:  (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Enhancing Automation and Accessibility in Electron Microscopy through Generative AI <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d18839e62">Electron microscopy (EM) is essential in materials science, providing detailed imaging at atomic and nanoscale resolutions that reveal insights into material composition, morphology, and structural behavior. However, operating EM instruments has traditionally required extensive expertise in user interfaces, electron optics, and beam-specimen interactions. To address these challenges, we explore an AI-driven interface that allows researchers to control EM systems through intuitive, language-based commands. By integrating a Python-based microscope API with large language models (LLMs) and Vision Transformers (ViT), this system simplifies EM operation, making advanced functionalities more accessible and enhancing usability and efficiency. The available microscope functions support a wide range of detectors, including analytical capabilities. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d18839e64">A multi-modal LLM can handle text, voice, and image-based instructions [ <a class="xref-link" href="#r1">1</a>], allowing users to bypass conventional graphical user interfaces (GUIs). Natural language commands, executed via a Python API, enable seamless adjustment of beam settings, detector configurations, and imaging conditions. This reduces the steep learning curve typically associated with EM, democratizing access for users of all expertise levels. The system also supports multiple languages, broadening accessibility for international researchers and facilitating collaboration. By automating routine tasks, this AI interface enhances productivity for experienced users while allowing novice operators to focus on experimental objectives rather than technical challenges. <p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" dir="auto" id="d18839e69">While early versions of LLM-controlled microscopes used multi-modal LLMs and Set of Mark (SOM) [ <a class="xref-link" href="#r2">2</a>, <a class="xref-link" href="#r3">3</a>], here we opted to add zero-shot foundational segmentation models, notably the Segment Anything Model (SAM) [ <a class="xref-link" href="#r4">4</a>], which enables automated, real-time segmentation without task-specific retraining. SAM, combined with LLM support, facilitates automated region-of-interest selection, object tracking, and interactive image data manipulation. Generative grammar ; Automation ; Computer science ; Electron microscope ; Microscopy ; Artificial intelligence ; Human–computer interaction ; Nanotechnology ; Materials science ; Engineering ; Physics ; Optics ; Mechanical engineering Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques
Authors: Vijay Kumar Goli | C. Himavarsha | CH. Ramya | CH. Akhila | C. Jessica | C.Vasanth Paul
Source: International Journal of Research Publication and Reviews (article, 2025-07-01)
Field: Chemistry — Analytical Chemistry

Formulation And Evaluation Of Olsalazine Delayed Release Tablets Medicine Analytical Methods in Pharmaceuticals ; Pharmacological Effects of Natural Compounds ; Natural Products and Biological Research
Authors: Hao Yan | Zhicheng Liu | Haiying Sun | Wang Zhai | Wenyu Sun | Long Mu
Source: Frigid Zone Medicine (article, 2025-06-01)
Field: Chemistry — Spectroscopy

Advances in the detection methods for assessing the viability of cryopreserved samples Abstract Since the beginning of the 21st century, modern medical technology has advanced rapidly, and the cryomedicine has also seen significant progress. Notable developments include the application of cryomedicine in assisted reproduction and the cryopreservation of sperm, eggs and embryos, as well as the preservation of skin, fingers, and other isolated tissues. However, cryopreservation of large and complex tissues or organs remains highly challenging. In addition to the damage caused by the freezing and rewarming processes and the inherent complexity of tissues and organs, there is an urgent need to address issues related to damage detection and the investigation of injury mechanisms. It provides a retrospective analysis of existing methods for assessing tissue and organ viability. Although current techniques can detect damage to some extent, they tend to be relatively simple, time-consuming, and limited in their ability to provide timely and comprehensive assessments of viability. By summarizing and evaluating these approaches, our study aims to contribute to the improvement of viability detection methods and to promote further development in this critical area. Cryopreservation ; Computer science ; Biology ; Fishery Mass Spectrometry Techniques and Applications ; Molecular Biology Techniques and Applications ; Ion-surface interactions and analysis
Authors: Nourredine Tadj | Rabah Djekidel | Abdechafik Hadjadj | Basil Osama Ahmed | Takieddine Meriouma
Source: Journal Européen des Systèmes Automatisés (article, 2025-08-31)
Field: Materials Science — Materials Chemistry

Corrosion Simulation and Optimization of Sacrificial Anode Protection of a Buried Pipeline Using Teaching Learning Based Optimization (TLBO) Algorithm The permanent presence of metallic pipelines in the soil produces electrochemical reactions, which leads to the corrosion activity and thus, an adequate cathodic protection strategy is required.The purpose of this paper is to assess the effect of inductive coupling between an EHV overhead power line and a buried metallic pipeline in normal operation; and to optimize a sacrificial anode cathodic protection system from corrosion evolution using a new efficient meta-heuristic algorithm of Teaching Learning Based Optimization (TLBO).The results obtained indicate that the induced voltage resulting from the inductive coupling exceeds the limit recommended by the majority of international standards; the calculated value of corrosion current density presents a relevant parameter having a significant effect on the corrosion rate and metal loss.Therefore; the selected optimization algorithm proves to be accurate in determining the parameters associated with the design of the sacrificial anode cathodic protection system and is able to meet the current requirement criterion necessary for the protection implemented and to ensure the stability and optimal performance of the hydrocarbon transportation pipeline system. Pipeline (software) ; Optimization algorithm ; Anode ; Corrosion ; Galvanic anode Corrosion Behavior and Inhibition ; Non-Destructive Testing Techniques ; Structural Integrity and Reliability Analysis
Authors: Hongliang Zhang | Mei Chen | Xiang-Rong Chen | Na Ma | Wei Xiang
Source: Applied Mathematics and Nonlinear Sciences (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Tobacco adulteration recognition study by hyperspectral data processing under machine learning Abstract Traditional tobacco adulteration manual detection methods have problems such as complex operation and low precision, which cannot meet the increasingly refined needs of tobacco adulteration detection. In order to realize the discrimination of adulteration of different varieties of tobacco, this study combines hyperspectral imaging technology with deep learning to design a method that can quickly and accurately identify tobacco adulteration. Hyperspectral images of tobacco were collected, and the region of interest for collecting image data of tobacco samples was selected as a means of obtaining spectral data of tobacco leaves. Then the original hyperspectral data were preprocessed using the SNV method, followed by the application of PCA processing method for dimensionality reduction of the hyperspectral data. Finally, the last 5 layers of GoogLeNet were removed and 15 new layers were added, and the ReLU activation function was changed to LeakyReLU activation function in order to improve the CNN model and enhance its expressiveness. Data preprocessing, data dimensionality reduction, and hyperspectral tobacco adulteration recognition method based on improved convolutional neural network were established. The experimental study of tobacco adulteration recognition was carried out. The results show that the recognition accuracy of the improved CNN model in this paper reaches 97.56% after PCA processing. The modeling time was reduced by 30% after data dimensionality reduction by PCA method. It shows that the tobacco adulteration recognition scheme combining the PCA preprocessing method and the improved CNN model of this paper can effectively recognize tobacco adulteration. And it can also play an excellent performance in the problem of tobacco adulteration origin identification, which indicates that the combination of hyperspectral and machine learning technology can provide a powerful means for the field identification of adulterated tobacco, and has a wide range of application prospects in the field of tobacco adulteration identification. Hyperspectral imaging ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) ; Machine learning Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Hyeonjin Eun | P. Szabó | Darlyn Rehhorn | Seungwoo Lee | Yongheum Jo | Marcus Altmaier | Jinyoung Lee | Xavier Gaona | Jong-Il Yun
Source: Repository KITopen (Karlsruhe Institute of Technology) (article, 2025-01-01)
Field: Chemistry — Inorganic Chemistry

Uptake of Eu, Th, U, and Pu by granite and biotite gneiss in Korean fresh groundwater under oxidizing and reducing conditions Uptake of Eu, Th, U, and Pu by granite and biotite gneiss in Korean fresh groundwater Gneiss ; Biotite ; Groundwater ; Oxidizing agent ; Precambrian Radioactive element chemistry and processing ; Geochemistry and Elemental Analysis ; Radioactive contamination and transfer
Authors: Liping Guo | Hongliang Wang | Weiwei Qi | Jun Zhang | Wu Lu
Source: Energies (article, 2025-06-23)
Field: Chemistry — Analytical Chemistry

The Molecular Dynamics of Signature Gas Diffusions in Synthetic-Ester-Based Oil Under a Range of Thermal Conditions Synthetic ester insulating oils are extensively utilized in power transformers due to their exceptional insulating properties, thermal stability, and environmental compatibility. The dissolved gas analysis (DGA) technique, which is employed to diagnose internal faults in transformers by monitoring the concentration and composition of dissolved gases in oil, is thought to be effective in detecting typical faults such as overheating and partial discharges in synthetic esters. However, owing to the significant differences in the properties of traditional mineral oil and synthetic esters, the existing DGA-based diagnostic methods developed for mineral oils cannot be directly applied to synthetic esters. A deep understanding of the microscopic processes occurring during the gas generation and diffusion of synthetic esters is an urgent necessity for DGA applications. Therefore, in this study, we systematically investigated the diffusion behavior of seven typical fault gases in synthetic ester insulating oils within a temperature range of 343–473 K using molecular dynamics simulations. The results demonstrate that H2 exhibits the highest diffusion capability across all temperatures, with a diffusion coefficient of 33.430 × 10−6 cm2/s at 343 K, increasing to 402.763 × 10−6 cm2/s at 473 K. Additionally, this paper explores the microscopic mechanisms underlying the diffusion characteristics of these characteristic gases by integrating the Free-Volume Theory, thereby providing a theoretical foundation for refining the fault gas analysis methodology for transformer insulating oils. Signature (topology) ; Range (aeronautics) ; Thermal ; Molecular dynamics ; Petroleum engineering ; Biochemical engineering ; Chemistry ; Materials science ; Thermodynamics ; Physics ; Engineering ; Computational chemistry ; Mathematics ; Composite material Petroleum Processing and Analysis ; Phase Equilibria and Thermodynamics ; Heat transfer and supercritical fluids
Authors: F. O. Uhegbu | D. O. Okoroafor | J. C. Igwe | K. E. Onwuka | C. U. Aghalibe
Source: Journal of applied science and environmental management (article, 2025-12-10)
Field: Materials Science — Materials Chemistry

Inhibitory Potentials of Ethanol and Aqueous Extracts of Senna alata (Linnaeus) Roxburgh (Candle Bush) leaves on Sulphate Reducing Bacteria Induced Anaerobic Corrosion of Oil Pipeline Steel Coupons Sulphate reducing bacteria (SRB) induced anaerobic corrosion of oil pipeline steel remains one of the major causes of reduced oil recovery in petroleum industry, and as such research interests are geared towards developing sustainable solutions to that. Therefore, the objective of this paper was to investigate the inhibitory potentials of ethanol and aqueous extracts of Senna alata (Linnaeus) Roxburgh (Candle Bush) leaves on sulphate reducing bacteria (SBR) induced anaerobic corrosion of oil pipeline steel coupons using media absorbance examination, Scanning Electron Microscopy (SEM) and gravimetric techniques. Data obtained reveals that the inhibition efficiencies of the test extract on the SRB induced corrosion of the studied metal steel, for the coupons immersed for 14 days, range from 38.89% to 62.96% in aqueous extract and 40.74% to 64.82% in ethanol extract. For the coupons immersed for 28 days, the inhibition efficiencies range from 48.28% to 73.56% in aqueous extract and 50.57% to 74.71% in ethanol extract respectively. The results show that extracts of (Senna alata leaves) inhibited SRB induced corrosion of the metal steel coupons by decreasing the corrosion rate in SRB incubated medium. The inhibition efficiency increased with increase in extract concentration, and corrosion inhibition was more susceptible in ethanol extract than observed in aqueous extract. Adsorption of the plant extract fitted into Langmuir, Freundlich and Temkin adsorption isotherms with positive regression coefficient (R2) values, and the calculated free energy of adsorption of the test plant extract on the pipeline steel were all negative within the range of −1.46 KJmol-1 to −4.80 KJmol-1 which are less negative than −20 KJmol-1 suggesting physisorption mechanism. Therefore, Senna alata ethanol and aqueous leaf extract is a promising corrosion inhibitor of SRB induced anaerobic corrosion of oil pipeline steel on industrial scale application. Corrosion ; Aqueous solution ; Ethanol ; Sulfate-reducing bacteria ; Adsorption ; Carbon steel Corrosion Behavior and Inhibition ; Petroleum Processing and Analysis ; Concrete Corrosion and Durability
Authors: Neha Srikanth | Rachel Rudinger
Source: ArXiv.org (preprint, 2025-02-12)
Field: Chemistry — Electrochemistry

NLI under the Microscope: What Atomic Hypothesis Decomposition Reveals Decomposition of text into atomic propositions is a flexible framework allowing for the closer inspection of input and output text. We use atomic decomposition of hypotheses in two natural language reasoning tasks, traditional NLI and defeasible NLI, to form atomic sub-problems, or granular inferences that models must weigh when solving the overall problem. These atomic sub-problems serve as a tool to further understand the structure of both NLI and defeasible reasoning, probe a model's consistency and understanding of different inferences, and measure the diversity of examples in benchmark datasets. Our results indicate that LLMs still struggle with logical consistency on atomic NLI and defeasible NLI sub-problems. Lastly, we identify critical atomic sub-problems of defeasible NLI examples, or those that most contribute to the overall label, and propose a method to measure the inferential consistency of a model, a metric designed to capture the degree to which a model makes consistently correct or incorrect predictions about the same fact under different contexts. Decomposition ; Microscope ; Materials science ; Nanotechnology ; Chemistry ; Physics ; Optics Electrochemical Analysis and Applications