jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Nurhan Çevik Elen | Musa Yıldırım | Yasin Kanbur
Source: Functional Composites and Structures (article, 2023-02-27)
Field: Materials Science — Polymers and Plastics

Tribological properties of hemp fiber reinforced polylactic acid bio-composites: effect of different types of modification methods Abstract In this study, green composites are prepared with 30 wt.% hemp fibers reinforced polylactic acid (PLA) to enhance the impact and tribological properties. Different surface treatments of alkali and silane, compatibilizer of maleic anhydride (MA), and blends of thermoplastic polyurethane (TPU) and poly (butylene succinate) were applied to improve interfacial adhesion between fibers and matrix. Hemp-reinforced PLA bio-composites were fabricated and characterized by hardness, impact strength, wear, and friction properties. The tribological tests of the injection-molded components were performed under two different loads (10 N and 20 N) as dry-sliding linearly reciprocating motion per ASTM G133. Modified composites gave better tribological properties than unmodified composites. While no remarkable improvement was observed in the hardness value of untreated fiber-reinforced composite, alkali-treated composite reached up to 43% improvement in hardness value. In general, as the load increased, weight loss increase was observed in all composites. Unmodified bio-composite exhibited a very low weight loss and specific wear rate (SWR) compared to neat PLA under 10 N load. The SWR of the MA bio-composite had the lowest value for both loads (10 N and 20 N) compared to the other bio-samples. The TPU blended bio-composite exhibited the highest impact strength (22.96 kJ m −2 ) after pure PLA (26.5 kJ m −2 ). Therefore, due to surface treatments and blends applied to the fibers, some composites’ hardness and wear resistance were increased while the impact strength and friction coefficient was decreased. Especially silane surface treatment and MA compatibilizer application increased the wear resistance of composites. When the scanning electron microscope images were examined, it was revealed that the fiber and matrix interface bonding was good, and the fibers were firmly embedded in the matrix. Furthermore, forming a protective thin film layer formed by the polymer debris from the surface during dry-sliding increased the wear performance of the bio-composites. Materials science ; Composite material ; Polylactic acid ; Tribology ; Composite number ; Maleic anhydride ; Izod impact strength test ; Silane ; Fiber ; Surface modification ; Ultimate tensile strength ; Polymer ; Copolymer Natural Fiber Reinforced Composites ; Tribology and Wear Analysis ; biodegradable polymer synthesis and properties
Authors: David Vázquez-Parga | Andrea Fernández-Martínez | Francesc Viñes
Source: Journal of Chemical Theory and Computation (article, 2023-11-09)
Field: Materials Science — Materials Chemistry

Quantifying the Accuracy of Density Functionals on Transition Metal Bulk and Surface Properties Density functional theory would be exact when the exact exchange-correlation (<i>xc</i>) functional would be known, but since it is regretfully not known, dozens of <i>xc</i> functionals have been developed in the past decades, with some of them better suited for describing certain systems and/or properties. For transition metals (TMs), recent systematic studies assessing bulk properties─shortest interatomic bond distance, δ, cohesive energy, <i>E</i><sub>coh</sub>, and bulk modulus, <i>B</i><sub>0</sub>─and surface features─surface energy, γ, work function, ϕ, and interlayer distances, δ<sub><i>ij</i></sub>─of 27 TM bulks and 81 TM surfaces, highlighted that generalized gradient approximation (GGA) based <i>xc</i> functionals are, overall, better suited than other types of <i>xc</i> functionals for the TMs bulk and surfaces description, such as Perdew-Burke-Ernzerhof (PBE) or Vega-Viñes (VV). Still, some basic local density approximation <i>xc</i> functionals were not assessed, such as the Hedin-Lundqvist (HL) and Perdew-Zunger (PZ), or GGAs such as the revised Perdew-Burke-Ernzerhof (revPBE) or the Armiento-Mattsson (AM05). Here, we expand the analysis by not only including them but also the recent meta-GGA strongly constrained appropriately normed (SCAN) <i>xc</i> functional, characterized by fulfilling all 17 mathematical conditions an <i>xc</i> must comply, plus the Bayesian error estimation functional (BEEF) <i>xc</i>, a functional parametrized over a large and diverse set of experimental results using machine learning. The present results reveal that none of the <i>xc</i> studied excel neither PBE nor VV, yet AM05 and SCAN performance is quite acceptable, while BEEF <i>xc</i> probably needs more shells of parametrization to reach competitive accuracy levels. Parametrization (atmospheric modeling) ; Density functional theory ; Surface (topology) ; Hybrid functional ; Transition metal ; Work (physics) ; Physics ; Materials science ; Condensed matter physics ; Thermodynamics ; Chemistry ; Mathematics ; Quantum mechanics ; Geometry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Inorganic Chemistry and Materials
Authors: James N. Cobley
Source: BioEssays (article, 2023-05-05)
Field: Chemistry — Organic Chemistry

Oxiforms: Unique cysteine residue‐ and chemotype‐specified chemical combinations can produce functionally‐distinct proteoforms A single protein molecule with one or more cysteine residues can occupy a plurality of unique residue and oxidation-chemotype specified proteoforms that I term oxiforms. In binary reduced or oxidised terms, one molecule with three cysteines will adopt one of eight unique oxiforms. Residue-defined sulfur chemistry endows specific oxiforms with distinct functionally-relevant biophysical properties (e.g., steric effects). Their emergent complexity means a functionally-relevant effect may only manifest when multiple cysteines are oxidised. Like how mixing colours makes new shades, combining discrete redox chemistries-colours-can create a kaleidoscope of oxiform hues. The sheer diversity of oxiforms co-existing within the human body provides a biological basis for redox heterogeneity. Of evolutionary significance, oxiforms may enable individual cells to mount a broad spectrum of responses to the same stimulus. Their biological significance, however plausible, is speculative because protein-specific oxiforms remain essentially unexplored. Excitingly, pioneering new techniques can push the field into uncharted territory by quantifying oxiforms. The oxiform concept can advance our understanding of redox-regulation in health and disease. Cysteine ; Chemotype ; Residue (chemistry) ; Computational biology ; Chemistry ; Redox ; Biology ; Biochemistry ; Organic chemistry Click Chemistry and Applications ; Redox biology and oxidative stress ; Chemical Synthesis and Analysis
Authors: Yijun Zou | Hui Jin | Rongrong Zhu | Ting Zhang
Source: Nanomaterials (article, 2023-12-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metasurface Holography with Multiplexing and Reconfigurability Metasurface holography offers significant advantages, including a broad field of view, minimal noise, and high imaging quality, making it valuable across various optical domains such as 3D displays, VR, and color displays. However, most passive pure-structured metasurface holographic devices face a limitation: once fabricated, as their functionality remains fixed. In recent developments, the introduction of multiplexed and reconfigurable metasurfaces breaks this limitation. Here, the comprehensive progress in holography from single metasurfaces to multiplexed and reconfigurable metasurfaces is reviewed. First, single metasurface holography is briefly introduced. Second, the latest progress in angular momentum multiplexed metasurface holography, including basic characteristics, design strategies, and diverse applications, is discussed. Next, a detailed overview of wavelength-sensitive, angle-sensitive, and polarization-controlled holograms is considered. The recent progress in reconfigurable metasurface holography based on lumped elements is highlighted. Its instant on-site programmability combined with machine learning provides the possibility of realizing movie-like dynamic holographic displays. Finally, we briefly summarize this rapidly growing area of research, proposing future directions and potential applications. Holography ; Multiplexing ; Reconfigurability ; Computer science ; Optics ; Physics ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Liquid Crystal Research Advancements
Authors: Mario Christian Falconi | Antonella Maria Loconsole | Andrea Annunziato | Solenn Cozic | Samuel Poulain | Francesco Prudenzano
Source: Journal of Lightwave Technology (article, 2023-05-11)
Field: Materials Science — Ceramics and Composites

Design of a Broadband Erbium-Doped Fluoroindate Fiber Laser Emitting Up to 3.91 μm In this paper, for the first time, an erbium-doped fluoroindate fiber laser emitting up to 3.91 μm is designed and optimized by means of a numerical investigation performed via a home-made computer code. It is cladding pumped with red light at 635 nm. The employed fiber is commercially available from Le Verre Fluoré and exhibits a double D-shaped geometry. Continuous-wave laser emission is obtained thanks to the population inversion between the <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> F <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9/2</sub> and <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> I <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">9/2</sub> energy levels. The model takes into account measured spectroscopic parameters for the absorption, stimulated emission and spontaneous decay processes. The device performance is investigated by varying several parameters, such as the input pump power, the fiber length, the dopant concentration, the output mirror reflectivity and the signal wavelength. The proposed device is very versatile and is optimized for different scenarios, including: the shortest fiber, the highest output power and the lowest threshold. Simulation results show that the best performance in terms of emission bandwidth is obtained for the laser with the lowest threshold, i.e. only 25 mW, predicting a broadband coherent emission in the 3.25-3.91 μm wavelength range and paving the way to the fabrication of a low-cost and easy-to-pump middle infrared fiber laser. Laser ; Population inversion ; Population ; Optics ; Fiber laser ; Broadband ; Amplified spontaneous emission ; Physics ; Cladding (metalworking) ; Optical fiber ; Materials science ; Optoelectronics Glass properties and applications ; Solid State Laser Technologies ; Photonic Crystal and Fiber Optics
Authors: Shiva Ebrahimi | Xuan Guo
Source:  (article, 2023-12-04)
Field: Chemistry — Spectroscopy

Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry Tandem mass spectrometry (MS/MS) stands as the predominant high-throughput technique for comprehensively analyzing protein content within biological samples. This methodology is a cornerstone driving the advancement of proteomics. In recent years, substantial strides have been made in Data-Independent Acquisition (DIA) strategies, facilitating impartial and non-targeted fragmentation of precursor ions. The DIA-generated MS/MS spectra present a formidable obstacle due to their inherent high multiplexing nature. Each spectrum encapsulates fragmented product ions originating from multiple precursor peptides. This intricacy poses a particularly acute challenge in de novo peptide/protein sequencing, where current methods are ill-equipped to address the multiplexing conundrum. In this paper, we introduce Casanovo-DIA, a deep-learning model based on transformer architecture. It deciphers peptide sequences from DIA mass spectrometry data. Our results show significant improvements over existing STOA methods, including DeepNovo-DIA and PepNet. Casanovo-DIA enhances precision by 15.14% to 34.8%, recall by 11.62% to 31.94% at the amino acid level, and boosts precision by 59% to 81.36% at the peptide level. Integrating DIA data and our Casanovo-DIA model holds considerable promise to uncover novel peptides and more comprehensive profiling of biological samples. Casanovo-DIA is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/Casanovo-DIA. Mass spectrometry ; Peptide ; Tandem mass spectrometry ; Computational biology ; Computer science ; Proteomics ; Multiplexing ; Tandem mass tag ; Chemistry ; Combinatorial chemistry ; Quantitative proteomics ; Biology ; Chromatography ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Genomics and Phylogenetic Studies
Authors: My Nguyen | Kate J. Dolph | Kris T. Delaney | Kevin Shen | Nicholas Sherck | Stephan Köhler | Rohini Gupta | Matthew B. Francis | M. Scott Shell | Glenn H. Fredrickson
Source: The Journal of Chemical Physics (article, 2023-12-27)
Field: Chemistry — Organic Chemistry

Molecularly informed field theory for estimating critical micelle concentrations of intrinsically disordered protein surfactants The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically. Micelle ; Granularity ; Critical micelle concentration ; Field (mathematics) ; Thermodynamics of micellization ; Pulmonary surfactant ; Molecular dynamics ; Nanotechnology ; Entropy (arrow of time) ; Computer science ; Biological system ; Materials science ; Chemistry ; Statistical physics ; Computational chemistry ; Physics ; Thermodynamics ; Mathematics ; Organic chemistry ; Aqueous solution Surfactants and Colloidal Systems ; Spectroscopy and Quantum Chemical Studies ; Protein Structure and Dynamics
Authors: Kinga Czarnota-Łydka | Sylwia Sudoł-Tałaj | Katarzyna Kucwaj‐Brysz | Rafał Kurczab | Grzegorz Satała | Modesto de Candia | Francesco Samarelli | Cosimo Altomare | Alessia Carocci | Alexia Barbarossa | Ewa Żesławska | Monika Głuch‐Lutwin | Barbara Mordyl | Monika Kubacka | Natalia Wilczyńska-Zawal | Magdalena Jastrzębska‐Więsek | Anna Partyka | Nadia Khan | Małgorzata Więcek | Wojciech Nitek | Ewelina Honkisz-Orzechowska | Gniewomir Latacz | Anna Wesołowska | Antonio Carrieri | Jadwiga Handzlik
Source: European Journal of Medicinal Chemistry (article, 2023-07-30)
Field: Chemistry — Organic Chemistry

Synthesis, computational and experimental pharmacological studies for (thio)ether-triazine 5-HT6R ligands with noticeable action on AChE/BChE and chalcogen-dependent intrinsic activity in search for new class of drugs against Alzheimer's disease Chemistry ; Thio- ; Biological activity ; Stereochemistry ; Agonist ; Receptor ; In vitro ; Biochemistry Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and biological activity ; Chemical Reaction Mechanisms
Authors: Yu Xu | Jinmei Kou | Qian Zhang | Shudan Tan | Lichun Zhu | Zhihua Geng | Xuhai Yang
Source: Foods (article, 2023-01-26)
Field: Chemistry — Analytical Chemistry

Visual Detection of Water Content Range of Seabuckthorn Fruit Based on Transfer Deep Learning To realize the classification of sea buckthorn fruits with different water content ranges, a convolution neural network (CNN) detection model of sea buckthorn fruit water content ranges was constructed. In total, 900 images of seabuckthorn fruits with different water contents were collected from 720 seabuckthorn fruits. Eight classic network models based on deep learning were used as feature extraction for transfer learning. A total of 180 images were randomly selected from the images of various water content ranges for testing. Finally, the identification accuracy of the network model for the water content range of seabuckthorn fruit was 98.69%, and the accuracy on the test set was 99.4%. The program in this study can quickly identify the moisture content range of seabuckthorn fruit by collecting images of the appearance and morphology changes during the drying process of seabuckthorn fruit. The model has a good detection effect for seabuckthorn fruits with different moisture content ranges with slight changes in characteristics. The migration deep learning can also be used to detect the moisture content range of other agricultural products, providing technical support for the rapid nondestructive testing of moisture contents of agricultural products. Water content ; Transfer of learning ; Range (aeronautics) ; Artificial intelligence ; Mathematics ; Computer science ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Lukáš Klein | Jan Fulneček | David Seidl | Lukáš Prokop | Stanislav Mišák | Jiří Dvorský | Marian Piecha
Source: Scientific Data (article, 2023-08-21)
Field: Materials Science — Materials Chemistry

A Data Set of Signals from an Antenna for Detection of Partial Discharges in Overhead Insulated Power Line We introduce a data set obtained via a contactless antenna method for detecting partial discharges in XLPE-covered conductors used in medium-voltage overhead power transmission lines. The data set consists of almost three years' worth of data, collected every hour from 9 measuring stations in Czechia and Slovakia. Each sample in the data set represents a single signal gathered for 20 ms. The contactless method is deployed on the same stations as the galvanic contact method, which is used by power distributors and can provide ground truth. Also manually curated data by human expert are present. Successful detection of partial discharges can prevent electricity shutdowns and forest fires resulting from insulation failure due to vegetation contact. The data set is particularly relevant for covered conductors used in mountainous regions where establishing a safe zone is challenging. The contactless method offers advantages such as cheaper and easier installation. The data set has the potential to develop machine learning models to detect partial discharges and facilitate safer and cheaper use of covered conductors. Overhead (engineering) ; Data set ; Electric power transmission ; Antenna (radio) ; Computer science ; Set (abstract data type) ; Electrical conductor ; Data transmission ; Transmission line ; Partial discharge ; Line (geometry) ; Electrical engineering ; Power (physics) ; Transmission (telecommunications) ; Electricity ; Voltage ; Engineering ; Telecommunications ; Computer hardware ; Artificial intelligence ; Physics High voltage insulation and dielectric phenomena ; Thermal Analysis in Power Transmission ; Lightning and Electromagnetic Phenomena
Authors: Maria Frizzarin | Giulio Visentin | Alessandro Ferragina | Elena Hayes | Antonio Bevilacqua | Bhaskar Dhariyal | Katarina Domijan | Hussain Khan | Georgiana Ifrim | Thach Le Nguyen | Joe Meagher | Laura Menchetti | Ashish Singh | Suzy Whoriskey | Robert C. Williamson | Martina Zappaterra | Alessandro Casa
Source: Chemometrics and Intelligent Laboratory Systems (article, 2023-01-18)
Field: Chemistry — Analytical Chemistry

Classification of cow diet based on milk Mid Infrared Spectra: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2022” Chemometrics ; Linear discriminant analysis ; Competition (biology) ; Computer science ; Product (mathematics) ; Food science ; Agricultural science ; Mathematics ; Artificial intelligence ; Machine learning ; Chemistry ; Biology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Priyanka Reddy | Joe Panozzo | Kathryn M. Guthridge | Germán Spangenberg | Simone Rochfort
Source: Sensors (article, 2023-02-06)
Field: Chemistry — Analytical Chemistry

Single Seed Near-Infrared Hyperspectral Imaging for Classification of Perennial Ryegrass Seed The detection of beneficial microbes living within perennial ryegrass seed causing no apparent defects is challenging, even with the most sensitive and conventional methods, such as DNA genotyping. Using a near-infrared hyperspectral imaging system (NIR-HSI), we were able to discriminate not only the presence of the commercial NEA12 fungal endophyte strain but perennial ryegrass cultivars of diverse seed age and batch. A total of 288 wavebands were extracted for individual seeds from hyperspectral images. The optimal pre-processing methods investigated yielded the best partial least squares discriminant analysis (PLS-DA) classification model to discriminate NEA12 and without endophyte (WE) perennial ryegrass seed with a classification accuracy of 89%. Effective wavelength (EW) selection based on GA-PLS-DA resulted in the selection of 75 wavebands yielding 88.3% discrimination accuracy using PLS-DA. For cultivar identification, the artificial neural network discriminant analysis (ANN-DA) was the best-performing classification model, resulting in >90% classification accuracy for Trojan, Alto, Rohan, Governor and Bronsyn. EW selection using GA-PLS-DA resulted in 87 wavebands, and the PLS-DA model performed the best, with no extensive compromise in performance, resulting in >89.1% accuracy. The study demonstrates the use of NIR-HSI reflectance data to discriminate, for the first time, an associated beneficial fungal endophyte and five cultivars of perennial ryegrass seed, irrespective of seed age and batch. Furthermore, the negligible effects on the classification errors using EW selection improve the capability and deployment of optimized methods for real-time analysis, such as the use of low-cost multispectral sensors for single seed analysis and automated seed sorting devices. Hyperspectral imaging ; Linear discriminant analysis ; Perennial plant ; Selection (genetic algorithm) ; Artificial intelligence ; Endophyte ; Pattern recognition (psychology) ; Cultivar ; Biology ; Mathematics ; Agronomy ; Computer science ; Botany Spectroscopy and Chemometric Analyses ; Plant Pathogens and Fungal Diseases ; Spectroscopy Techniques in Biomedical and Chemical Research