jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Isha Kalra | Xin Wang | Ru Zhang | Rachael M. Morgan‐Kiss
Source: Photosynthesis Research (article, 2023-06-22)
Field: Chemistry — Spectroscopy

High salt-induced PSI-supercomplex is associated with high CEF and attenuation of state transitions While PSI-driven cyclic electron flow (CEF) and assembly of thylakoid supercomplexes have been described in model organisms like Chlamydomonas reinhardtii, open questions remain regarding their contributions to survival under long-term stress. The Antarctic halophyte, C. priscuii UWO241 (UWO241), possesses constitutive high CEF rates and a stable PSI-supercomplex as a consequence of adaptation to permanent low temperatures and high salinity. To understand whether CEF represents a broader acclimation strategy to short- and long-term stress, we compared high salt acclimation between the halotolerant UWO241, the salt-sensitive model, C. reinhardtii, and a moderately halotolerant Antarctic green alga, C. sp. ICE-MDV (ICE-MDV). CEF was activated under high salt and associated with increased non-photochemical quenching in all three Chlamydomonas species. Furthermore, high salt-acclimated cells of either strain formed a PSI-supercomplex, while state transition capacity was attenuated. How the CEF-associated PSI-supercomplex interferes with state transition response is not yet known. We present a model for interaction between PSI-supercomplex formation, state transitions, and the important role of CEF for survival during long-term exposure to high salt. Salt (chemistry) ; Chemistry ; Physical chemistry Advanced NMR Techniques and Applications ; Carbon Nanotubes in Composites ; Spectroscopy and Quantum Chemical Studies
Authors: Avraham Klein | Vladyslav Kozii | Jonathan Ruhman | Rafael M. Fernandes
Source: Physical review. B./Physical review. B (article, 2023-04-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Theory of criticality for quantum ferroelectric metals Although ferroelectricity in metals was long considered to be impossible, a large family of materials hosting both states has been discovered in recent years, and these properties are often strongly coupled. The authors investigate here the quantum phase transition between the ferroelectric and paraelectric states in metals. They find unique quantum critical properties stemming from unconventional inversion-breaking fluctuations, along with enhanced tendencies to both spin singlet and triplet superconductivity, and provide protocols for strain control of the quantum state of these systems. Ferroelectricity ; Superconductivity ; Criticality ; Quantum ; Condensed matter physics ; Quantum phase transition ; Quantum phases ; Singlet state ; Phase transition ; Dielectric ; Physics ; Quantum critical point ; Quantum state ; Quantum mechanics ; Nuclear physics Iron-based superconductors research ; Electronic and Structural Properties of Oxides ; Ferroelectric and Piezoelectric Materials
Authors: Rim Sarieddine | Hind Kadiri | Bruno Guelorget | Loïc Le Cunff | Akram Alhussein | Roland Habchi | Gilles Lérondel
Source: Advanced Materials Interfaces (review, 2023-12-19)
Field: Materials Science — Surfaces, Coatings and Films

A Review on Potential Mechanically Resistant Materials for Optical Multifunctional Surfaces: Bioinspired Surfaces with Advanced Properties Abstract Mimicking naturethrough nanostructuring allows the creation of multifunctional surfaces withremarkable properties, such as anti‐reflectivity, high optical transmittanceand controlled wettability, enabling anti‐icing or anti‐fogging behaviors. These multifunctionalsurfaces have gained significant interest in civil and military domains. However,integrating them into real‐life applications faces challenges related tocost, high‐throughput large‐scale compatible nanofabrication techniques, andtheir mechanical resistance. While sub‐wavelength patterning improves the optical performance,it often comes at the cost of compromising the mechanical resistance. As opticalperformance improves, mechanical resistance tends to deteriorate, and viceversa. To address this challenge, taking inspiration from the lotus leafstructure, where patterns are covered by a thin 2D wax film, covering thepatterns of structured surfaces with a protective layer can be a viablesolution. This protective layer should enhance the mechanical resistance of thesurface without compromising its multifunctional capabilities. This reviewhighlights the most suitable materials that can be employed as protectivecoatings and their potential to enhance the resistance of structured surfaces.The fundamental concept behind the creation of multifunctional optical surfacesis discussed, followed by a comprehensive examination of mechanical tests thatcan be utilized to characterize their mechanical behavior. This review aims topave the way for the development of durable multifunctional optical surfaces,making them more amenable to industrial applications. Materials science ; Nanotechnology ; Biomimetics ; Wetting ; Layer (electronics) ; Composite material Surface Modification and Superhydrophobicity ; Diamond and Carbon-based Materials Research ; Silicone and Siloxane Chemistry
Authors: Jinjun Gao | Xinlei Sheng | Jianfeng Du | Di Zhang | Chang Han | Yue Chen | Chu Wang | Yingming Zhao
Source: Science Advances (article, 2023-04-05)
Field: Chemistry — Spectroscopy

Identification of 113 new histone marks by CHiMA, a tailored database search strategy Shotgun proteomics has been widely used to identify histone marks. Conventional database search methods rely on the "target-decoy" strategy to calculate the false discovery rate (FDR) and distinguish true peptide-spectrum matches (PSMs) from false ones. This strategy has a caveat of inaccurate FDR caused by the small data size of histone marks. To address this challenge, we developed a tailored database search strategy, named "Comprehensive Histone Mark Analysis (CHiMA)." Instead of target-decoy-based FDR, this method uses "50% matched fragment ions" as the key criterion to identify high-confidence PSMs. CHiMA identified twice as many histone modification sites as the conventional method in benchmark datasets. Reanalysis of our previous proteomics data using CHiMA led to the identification of 113 new histone marks for four types of lysine acylations, almost doubling the number of previously reported marks. This tool not only offers a valuable approach for identifying histone modifications but also greatly expands the repertoire of histone marks. Histone ; Database search engine ; Computational biology ; Shotgun proteomics ; Computer science ; False discovery rate ; Proteomics ; Identification (biology) ; Decoy ; Biology ; Genetics ; Search engine ; DNA ; Information retrieval Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Peptidase Inhibition and Analysis
Authors: Marco C. Lam | R. J. Smith | I. Arcavi | I. A. Steele | Joshua Veitch-Michaelis | Ł. Wyrzykowski
Source: The Astronomical Journal (article, 2023-06-13)
Field: Chemistry — Analytical Chemistry

Automated SpectroPhotometric Image REDuction (ASPIRED) Abstract We provide a suite of public open-source spectral data-reduction software to rapidly obtain scientific products from all forms of long-slit-like spectroscopic observations. Automated SpectroPhotometric REDuction ( ASPIRED ) is a Python -based spectral data-reduction toolkit. It is designed to be a general toolkit with high flexibility for users to refine and optimize their data-reduction routines for the individual characteristics of their instruments. The default configuration is suitable for low-resolution long-slit spectrometers and provides a quick-look quality output. However, for repeatable science-ready reduced spectral data, some moderate one-time effort is necessary to modify the configuration. Fine-tuning and additional (pre)processing may be required to extend the reduction to systems with more complex setups. It is important to emphasize that although only a few parameters need updating, ensuring their correctness and suitability for generalization to the instrument can take time due to factors such as instrument stability. We compare some example spectra reduced with ASPIRED to published data processed with iraf -based and STARLINK -based pipelines, and find no loss in the quality of the final product. The Python -based, iraf -free ASPIRED can significantly ease the effort of an astronomer in constructing their own data-reduction workflow, enabling simpler solutions to data-reduction automation. This availability of near-real-time, science-ready data will allow adaptive observing strategies, particularly important in, but not limited to, time-domain astronomy. Python (programming language) ; Data reduction ; Reduction (mathematics) ; Workflow ; Correctness ; Automation ; Software ; Computer science ; Data processing ; Physics ; Suite ; Computational science ; Algorithm ; Data mining ; Programming language ; Database Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Astronomy and Astrophysical Research
Authors: Carol Castañeda | Karent Bravo | Natalie Cortés | Janeth Bedoya | Warley S. de Borges | Jaume Bastida | Edison Osorio
Source: Journal of Applied Biomedicine (article, 2023-03-31)
Field: Chemistry — Organic Chemistry

Amaryllidaceae alkaloids in skin cancer management: Photoprotective effect on human keratinocytes and anti-proliferative activity in melanoma cells Skin cancer has high rates of mortality and therapeutic failure. In this study, to develop a multi-agent strategy for skin cancer management, the selective cytotoxicity of several alkaloid fractions and pure alkaloids isolated from Amaryllidaceae species was evaluated in melanoma cells. In addition, UVB-stimulated keratinocytes (HaCaT) were exposed to seven alkaloid fractions characterized by GC-MS, and the production of intracellular reactive oxygen species (ROS) and IL-6, were measured to evaluate their photoprotection effects. The Eucharis caucana (bulb) alkaloid fraction (20 μg/ml) had a clear effect on the viability of melanoma cells, reducing it by 45.7% without affecting healthy keratinocytes. This alkaloid fraction and tazettine (both at 2.5 μg/ml) suppressed UVB-induced ROS production by 31.6% and 29.4%, respectively. The highest anti-inflammatory potential was shown by the Zephyranthes carinata (bulb) alkaloid fraction (10 μg/ml), which reduced IL-6 production by 90.8%. According to the chemometric analysis, lycoramine and tazettine had a photoprotective effect on the UVB-exposed HaCaT cells, attenuating the production of ROS and IL-6. These results suggest that Amaryllidaceae alkaloids have photoprotective and therapeutic potential in skin cancer management, especially at low concentrations. HaCaT ; Alkaloid ; Reactive oxygen species ; Cancer cell ; Skin cancer ; Melanoma ; Pharmacology ; Bulb ; Viability assay ; Amaryllidaceae Alkaloids ; Cytotoxicity ; Chemistry ; Amaryllidaceae ; Keratinocyte ; Traditional medicine ; Biology ; Cancer ; Biochemistry ; Botany ; Cell ; Medicine ; In vitro ; Cancer research Chemical synthesis and alkaloids ; Alkaloids: synthesis and pharmacology ; Fungal Biology and Applications
Authors: P. Rybacki | Janetta Niemann | Kiril Bahćevandžiev | K. Durczak
Source: Sensors (article, 2023-02-23)
Field: Chemistry — Analytical Chemistry

Convolutional Neural Network Model for Variety Classification and Seed Quality Assessment of Winter Rapeseed The main objective of this study is to develop an automatic classification model for winter rapeseed varieties, to assess seed maturity and damage based on seed colour using a convolutional neural network (CNN). A CNN with a fixed architecture was built, consisting of an alternating arrangement of five classes Conv2D, MaxPooling2D and Dropout, for which a computational algorithm was developed in the Python 3.9 programming language, creating six models depending on the type of input data. Seeds of three winter rapeseed varieties were used for the research. Each imaged sample was 20.000 g. For each variety, 125 weight groups of 20 samples were prepared, with the weight of damaged or immature seeds increasing by 0.161 g. Each of the 20 samples in each weight group was marked by a different seed distribution. The accuracy of the models' validation ranged from 80.20 to 85.60%, with an average of 82.50%. Higher accuracy was obtained when classifying mature seed varieties (average of 84.24%) than when classifying the degree of maturity (average of 80.76%). It can be stated that classifying such fine seeds as rapeseed seeds is a complex process, creating major problems and constraints, as there is a distinct distribution of seeds belonging to the same weight groups, which causes the CNN model to treat them as different. Rapeseed ; Python (programming language) ; Convolutional neural network ; Artificial intelligence ; Mathematics ; Classifier (UML) ; Artificial neural network ; Computer science ; Pattern recognition (psychology) ; Agronomy ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Magnetic and Electromagnetic Effects
Authors: Ahmad Reza Moosavi‐Zare | Raha Najafi
Source: Scientific Reports (article, 2023-10-01)
Field: Chemistry — Organic Chemistry

Multicomponent synthesis of pyrimido[4,5-b] quinolines over a carbocationic catalytic system Trityl chloride (TrCl) was efficiently used as a neutral catalyst for the multicomponent cyclization reaction of an aldehyde with dimedone and 6-amino-1,3-dimethyluracil for the preparation of pyrimido[4,5-b] quinolines in chloroform under reflux condition. Dimedone ; Aldehyde ; Catalysis ; Chloroform ; Chemistry ; Chloride ; Medicinal chemistry ; Combinatorial chemistry ; Organic chemistry Multicomponent Synthesis of Heterocycles ; Synthesis and biological activity ; Synthesis and Biological Evaluation
Authors: Zakaria Hafidi | Lourdes Pérez | Mohammed El Achouri | Ramón Pons
Source: Pharmaceutics (article, 2023-06-30)
Field: Chemistry — Organic Chemistry

Phenylalanine and Tryptophan-Based Surfactants as New Antibacterial Agents: Characterization, Self-Aggregation Properties, and DPPC/Surfactants Vesicles Formulation Cationic surfactants based on phenylalanine (C<sub>n</sub>PC<sub>3</sub>NH<sub>3</sub>Cl) and tryptophan (C<sub>n</sub>TC<sub>3</sub>NH<sub>3</sub>Cl) were synthesized using renewable raw materials as starting compounds and a green synthetic procedure. The synthesis, acid-base equilibrium, aggregation properties, and antibacterial activity were investigated. Conductivity and fluorescence were used to establish critical micelle concentrations. Micellization of C<sub>n</sub>PC<sub>3</sub>NH<sub>3</sub>Cl and C<sub>n</sub>TC<sub>3</sub>NH<sub>3</sub>Cl occurred in the ranges of 0.42-16.2 mM and 0.29-4.6 mM, respectively. Since those surfactants have some acidic character, the apparent pK<sub>a</sub> was determined through titrations, observing increasing acidity with increasing chain length and being slightly more acidic with the phenylalanine than the tryptophan derivatives. Both families showed promising antibacterial efficacy against eight different bacterial strains. Molecular docking studies against the enzyme peptidoglycan glycosyltransferase (PDB ID:2OQO) were used to investigate the potential binding mechanism of target surfactant molecules. According to small angle X-ray scattering (SAXS) results, the surfactants incorporate into DPPC (Dipalmitoyl Phosphatidyl Choline) bilayers without strong perturbation up to high surfactant concentration. Some of the C<sub>12</sub>TC<sub>3</sub>NH<sub>3</sub>Cl/DPPC formulations (40%/60% and 20%/80% molar ratios) exhibited good antibacterial activity, while the others were not effective against the tested bacteria. The strong affinity between DPPC and surfactant molecules, as determined by the DFT (density functional theory) method, could be one of the reasons for the loss of antibacterial activity of these cationic surfactants when they are incorporated in vesicles. Chemistry ; Pulmonary surfactant ; Micelle ; Antibacterial activity ; Cationic polymerization ; Critical micelle concentration ; Vesicle ; Titration ; Small-angle X-ray scattering ; Tryptophan ; Nuclear chemistry ; Organic chemistry ; Aqueous solution ; Membrane ; Bacteria ; Biochemistry ; Scattering ; Amino acid Antimicrobial agents and applications ; Surfactants and Colloidal Systems ; Pharmaceutical and Antibiotic Environmental Impacts
Authors: Jordi‐Roger Riba | Manuel Moreno‐Eguilaz | Santiago Bogarra
Source: Polymers (review, 2023-09-10)
Field: Materials Science — Materials Chemistry

Tracking Resistance in Polymeric Insulation Materials for High-Voltage Electrical Mobility Applications Evaluated by Existing Test Methods: Identified Research Needs With the increasing electrification of the transportation and mobility sectors, polymer insulation materials are inevitably exposed to harsher environments, including exposure to contamination, wide temperature ranges, operation at higher voltages and switching frequencies, and low-pressure environments. This paper reviews the tests to characterize the polymeric materials used in insulation systems for electric mobility applications, focusing on resistance to tracking. This paper also reports on the limitations of existing standard test methods and identifies the challenges and research needs to meet the increasing demands of the electric mobility industry. To this end, an evaluation of the scientific and technological state of the art is carried out through the analysis of theses, research articles, technical reports, manufacturers' datasheets, international standards, and white papers. Electrification ; Test (biology) ; Test method ; Computer science ; Automotive engineering ; Materials science ; Electrical engineering ; Engineering ; Electricity High voltage insulation and dielectric phenomena ; Advanced Battery Technologies Research ; Electrical Fault Detection and Protection
Authors: Sihan Zhou | Liang Qin | Yong Yang | Zheng Wei | Jialong Wang | Jing Wang | Jiangjun Ruan | Xu Tang | Xiaole Wang | Kaipei Liu
Source: Sensors (article, 2023-05-25)
Field: Materials Science — Materials Chemistry

A Novel Ensemble Fault Diagnosis Model for Main Circulation Pumps of Converter Valves in VSC-HVDC Transmission Systems The intelligent fault diagnosis of main circulation pumps is crucial for ensuring their safe and stable operation. However, limited research has been conducted on this topic, and applying existing fault diagnosis methods designed for other equipment may not yield optimal results when directly used for main circulation pump fault diagnosis. To address this issue, we propose a novel ensemble fault diagnosis model for the main circulation pumps of converter valves in voltage source converter-based high voltage direct current transmission (VSG-HVDC) systems. The proposed model employs a set of base learners already able to achieve satisfying fault diagnosis performance and a weighting model based on deep reinforcement learning that synthesizes the outputs of these base learners and assigns different weights to obtain the final fault diagnosis results. The experimental results demonstrate that the proposed model outperforms alternative approaches, achieving an accuracy of 95.00% and an <i>F</i><sub>1</sub> score of 90.48%. Compared to the widely used long and short-term memory artificial neural network (LSTM), the proposed model exhibits improvements of 4.06% in accuracy and 7.85% in <i>F</i><sub>1</sub> score. Furthermore, it surpasses the latest existing ensemble model based on the improved sparrow algorithm, with enhancements of 1.56% in accuracy and 2.91% in <i>F</i><sub>1</sub> score. This work presents a data-driven tool with high accuracy for the fault diagnosis of main circulation pumps, which plays a critical role in maintaining the operational stability of VSG-HVDC systems and satisfying the unmanned requirements of offshore flexible platform cooling systems. Fault (geology) ; Computer science ; Artificial neural network ; High-voltage direct current ; Transmission system ; Weighting ; Set (abstract data type) ; Transmission (telecommunications) ; Engineering ; Voltage ; Control engineering ; Artificial intelligence ; Direct current ; Electrical engineering ; Telecommunications High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; HVDC Systems and Fault Protection
Authors: Daniel J. Hutton | Kari E. Cordes | Carine Michel | Florian Göltl
Source: Journal of Chemical Information and Modeling (article, 2023-09-18)
Field: Materials Science — Materials Chemistry

Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces In computational surface catalysis, the calculation of activation energies of chemical reactions is expensive, which, in many cases, limits our ability to understand complex reaction networks. Here, we present a universal, machine learning-based approach for the prediction of activation energies for reactions of C-, O-, and H-containing molecules on transition metal surfaces. We rely on generalized Bronsted-Evans-Polanyi relationships in combination with machine learning-based multiparameter regression techniques to train our model for reactions included in the University of Arizona Reaction database. In our best approach, we find a mean absolute error for activation energies within our test set of 0.14 eV if the reaction energy is known and 0.19 eV if the reaction energy is unknown. We expect that this methodology will often replace the explicit calculation of activation energies within surface catalysis when exploring large reaction networks or screening catalysts for desirable properties in the future. Catalysis ; Activation energy ; Chemistry ; Chemical reaction ; Energy (signal processing) ; Set (abstract data type) ; Computer science ; Computational chemistry ; Physical chemistry ; Physics ; Organic chemistry ; Quantum mechanics Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; Advanced Photocatalysis Techniques
Authors: Feng Wang | Jun Cheng
Source: Chinese Journal of Structural Chemistry (article, 2023-03-09)
Field: Materials Science — Materials Chemistry

Understanding the solvation structures of glyme-based electrolytes by machine learning molecular dynamics Solvation ; Chemistry ; Molecular dynamics ; Electrolyte ; Ab initio ; Chemical physics ; Work (physics) ; Lithium (medication) ; Computational chemistry ; Thermodynamics ; Ion ; Physical chemistry ; Physics ; Organic chemistry ; Electrode Machine Learning in Materials Science ; Advanced Battery Materials and Technologies ; Advancements in Battery Materials