jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Shokirbek Shermukhamedov | Michael Probst
Source: Physics of Plasmas (article, 2023-12-01)
Field: Materials Science — Materials Chemistry

Sputtering from rough tungsten surfaces: Data-driven molecular dynamics simulations The sputtering of tungsten surfaces caused by hot plasma particles is an important process in fusion reactors where divertors are typically made of tungsten sheets. In this study, we present a molecular dynamics simulation strategy to investigate the sputtering yields of tungsten surfaces with geometrical defects. This should serve as a model for non-monocrystalline surfaces in general and could also be a rough model for nanoscale “fuzzy” layers, which are known to be formed by surface bombardment with energetic particles. Using a non-cumulative approach, we simulate the irradiation of tungsten surfaces with cone-shaped, cylindrical, and spherical defects by argon atoms. We analyze the sputtering yields as functions of particle energy and defect sizes. As a result, we find that surfaces with distinctly shaped defects always exhibit reduced sputtering yields, compared to smooth ones. We also investigate the angular distributions of sputtered particles and find them mostly to be in accordance with prior experimental and computational results. Sputtering ; Tungsten ; Molecular dynamics ; Physics ; Plasma ; Particle (ecology) ; Argon ; Nanoscopic scale ; Irradiation ; Mechanics ; Atomic physics ; Materials science ; Molecular physics ; Nanotechnology ; Thin film ; Metallurgy ; Nuclear physics Fusion materials and technologies ; Nuclear Materials and Properties ; Ion-surface interactions and analysis
Authors: Morteza Ghayedi | Michał Jasiński
Source: Sustainability (article, 2023-05-11)
Field: Materials Science — Materials Chemistry

Electric Field Distribution on Zinc Oxide Pills in Gapless Surge Arresters Using Finite Element Method and Evolutionary Optimization Algorithms in HVAC Systems This article proposes a new method for the optimal design of zinc oxide arresters based on electric field distribution on the zinc oxide column using smart algorithms and finite element analysis. This design prevents premature aging of zinc oxide tablets, especially the initial and final tablets of the column, which have a higher voltage gradient than other parts of the arrester, and subsequently increases the sustainability of the network. The spacer height, fiberglass layer thickness, and grading ring diameter and its location were taken as the problem variables. The surge arrester was designed in AC/DC mode and two-dimensional symmetry using the COMSOL Multiphysics package. For the first time, rational Bezier curves were also used for the arrester design. This paper presents an optimization approach that combines and dynamically links the electrostatic modeling process and the particle swarm optimization (PSO) and differential evolution (DE) algorithms. The proposed approach is a general method that can be used in the design of high-voltage equipment. The results showed that the lifetime and reliability were increased by reducing voltage variations in the ZnO column. Therefore, maintenance cost and implementation of a surge arrester would be reduced. Finally, the external surface of the porcelain housing was placed under the influence of uniform distribution of electric field. Surge arrester ; Particle swarm optimization ; Finite element method ; Multiphysics ; Voltage ; Lightning arrester ; Engineering ; Algorithm ; Materials science ; Computer science ; Structural engineering ; Electrical engineering High voltage insulation and dielectric phenomena ; Aerosol Filtration and Electrostatic Precipitation ; Power Transformer Diagnostics and Insulation
Authors: Mahmudi Mahmudi | Mutiara Annisa | Mutia Farida | Muhammad Yusuf | Saiful Azhari | Yunda Fachrunniza
Source: Grimsa Journal of Science Engineering and Technology (article, 2023-10-30)
Field: Chemistry — Analytical Chemistry

Assessing Heavy Metal Contamination in Traditional Herbal Medicine (Jamu) by Atomic Absorption Spectrophotometry Heavy metal contamination of traditional herbal medicine (jamu) is a threat to humans, especially at levels above known threshold concentrations. Traditional herbal medicine found in Banda Aceh City – Indonesia, polluted by heavy metals cadmium (Cd), lead (Pb), and mercury (Hg) was performed. Heavy metal analysis used Flame - Atomic Absorption Spectrometry (FAAS) and Chemical Vapor Generation - Atomic Absorption Spectrometry (CVG - AAS) methods. The validation of the method was performed to obtain more accurate heavy metal analysis results for the samples. Heavy metal contamination, especially Pb metal, with concentrations of 4.32 ± 0.14 mg/Kg to 29.25 ± 0.24 mg/Kg. The Cd metal contamination was only found in herbal medicine sample E with a concentration of 0.80 ± 0.02 mg/Kg, above the threshold. The Hg metal contamination was also found with concentrations of 0.20 ± 0.01 to 2.14 ± 0.06 mg/Kg, and some were not detected. The government should be very concerned about stopping the distribution of herbal medicine that can be harmful to health and should inspect drug stores that still sell herbs that do not have established standards. Contamination ; Atomic absorption spectroscopy ; Cadmium ; Mercury (programming language) ; Environmental chemistry ; Metal ; Heavy metals ; Chemistry ; Biology Heavy Metals in Plants ; Heavy metals in environment
Authors: Christa P. Baker | Roland Bruderer | James Abbott | J. Simon C. Arthur | Alejandro J. Brenes
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-10-11)
Field: Chemistry — Spectroscopy

Optimising Spectronaut search parameters to improve data quality with minimal proteome coverage reductions in DIA analyses of heterogeneous samples Abstract Data independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimised to minimise the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings we analysed mouse macrophages and compared their proteome to macrophages spiked with Candida albicans . This experimental system enabled the identification of ‘false positives’ since Candida albicans peptides and proteins should not be present in the mouse only samples. We show that adjusting the search parameters reduced ‘false positive’ identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimised parameters incur a moderate cost, only reducing the overall number of ‘true positive’ identifications across each biological replicate by &lt;6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analysing heterogenous populations of cell types or tissues. False positive paradox ; Proteome ; Replicate ; Candida albicans ; Computational biology ; Identification (biology) ; Computer science ; Biology ; Profiling (computer programming) ; Peptide ; Data mining ; Bioinformatics ; Statistics ; Mathematics ; Biochemistry ; Microbiology ; Artificial intelligence Advanced Proteomics Techniques and Applications ; Biosensors and Analytical Detection ; Mass Spectrometry Techniques and Applications
Authors: Amrutha Pattath Saseendran | C. Hartl | Yu Tian | Yi Qin
Source: Journal of Physics Conference Series (article, 2023-06-01)
Field: Materials Science — Materials Chemistry

Development, optimization, and testing of a hybrid solar panel concept with energy harvesting enhancement Abstract Photovoltaics (PV) is one of the important technologies for electricity generation from renewable energies today and has an excellent environmental sustainability. It is a fast-growing market worldwide and also offers opportunities for aviation to intensify the use of renewable sources. Although the efficiency of PV systems has increased to a certain extent in recent years, a predominant part of solar radiation acting on a PV system is still lost to the environment through reflection and convection as well as heat radiation from the heated PV system. In addition, the efficiency of these systems decreases with increasing heating. Possible solutions for energy harvesting of this energy loss through thermoelectric (TE) have been investigated theoretically and in part experimentally in various cases but have not yet been transferred to larger PV systems. At the same time, cooling the PV system through thermogenerators (TEG) allows its efficiency to be increased. This contribution presents first results from investigations into the design and testing of hybrid PV/TEG systems, which aim to increase the efficiency and improve economic manufacturability of such systems. Among others, important design aspects of hybrid PV/TEG systems and integration of IoT elements (Internet of Things) are addressed and the development of an analytical model to optimise hybrid systems is presented. Photovoltaics ; Renewable energy ; Photovoltaic system ; Hybrid system ; Process engineering ; Design for manufacturability ; Electricity ; Computer science ; Environmental science ; Environmental economics ; Automotive engineering ; Systems engineering ; Mechanical engineering ; Engineering ; Electrical engineering Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Innovative Energy Harvesting Technologies
Authors: Hiroshi Shinotsuka | Kenji Nagata | Malinda Siriwardana | Hideki Yoshikawa | Hayaru Shouno | Masato Okada
Source: Journal of Electron Spectroscopy and Related Phenomena (article, 2023-07-06)
Field: Materials Science — Surfaces, Coatings and Films

Sample structure prediction from measured XPS data using Bayesian estimation and SESSA simulator X-ray photoelectron spectroscopy ; Bayesian probability ; Posterior probability ; Sample (material) ; Computer science ; Sample size determination ; Biological system ; Analytical Chemistry (journal) ; Chemistry ; Statistics ; Artificial intelligence ; Mathematics ; Physics ; Nuclear magnetic resonance Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science ; Scientific Research and Discoveries
Authors: Ángela Pacheco | Ciro Velasco‐Cruz | Paulino Pérez‐Rodríguez | Juan Burgueño | Sergio Pérez‐Elizalde | Francelino A. Rodrigues | Iván Ortiz‐Monasterio | David Hebert del Valle‐Paniagua | Fernando Toledo
Source: Plant Methods (article, 2023-01-20)
Field: Chemistry — Analytical Chemistry

Bayesian modelling of phosphorus content in wheat grain using hyperspectral reflectance data The proposal to predict the phosphorus content in wheat grain using Bayesian approach, reflect with the results as a good alternative. Hyperspectral imaging ; Autoregressive model ; Correlogram ; Bayesian probability ; Statistical model ; Statistics ; Mathematics ; Environmental science ; Remote sensing ; Computer science ; Artificial intelligence ; Geography Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Leaf Properties and Growth Measurement
Authors: Muhammad Haseeb | Fahad Saeed
Source: Scientific Reports (article, 2023-10-31)
Field: Chemistry — Spectroscopy

GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data Database peptide search is the primary computational technique for identifying peptides from the mass spectrometry (MS) data. Graphical Processing Units (GPU) computing is now ubiquitous in the current-generation of high-performance computing (HPC) systems, yet its application in the database peptide search domain remains limited. Part of the reason is the use of sub-optimal algorithms in the existing GPU-accelerated methods resulting in significantly inefficient hardware utilization. In this paper, we design and implement a new-age CPU-GPU HPC framework, called GiCOPS, for efficient and complete GPU-acceleration of the modern database peptide search algorithms on supercomputers. Our experimentation shows that the GiCOPS exhibits between 1.2 to 5[Formula: see text] speed improvement over its CPU-only predecessor, HiCOPS, and over 10[Formula: see text] improvement over several existing GPU-based database search algorithms for sufficiently large experiment sizes. We further assess and optimize the performance of our framework using the Roofline Model and report near-optimal results for several metrics including computations per second, occupancy rate, memory workload, branch efficiency and shared memory performance. Finally, the CPU-GPU methods and optimizations proposed in our work for complex integer- and memory-bounded algorithmic pipelines can also be extended to accelerate the existing and future peptide identification algorithms. GiCOPS is now integrated with our umbrella HPC framework HiCOPS and is available at: https://github.com/pcdslab/gicops . Acceleration ; Computer science ; Mass spectrometry ; Database ; Database search engine ; Accelerator mass spectrometry ; Parallel computing ; Data mining ; Information retrieval ; Computational biology ; Chemistry ; Biology ; Search engine ; Chromatography ; Physics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Xiomara Ribero-Figueroa | Aníbal Pacheco-Sánchez | Aida Mansouri | Pankaj Kumar | Omid Habibpour | Herbert Zirath | Roman Sordan | Francisco Pasadas | David Jiménez | Reydezel Torres‐Torres
Source: IEEE Transactions on Electron Devices (article, 2023-09-13)
Field: Materials Science — Materials Chemistry

Characterization of the Intrinsic and Extrinsic Resistances of a Microwave Graphene FET Under Zero Transconductance Conditions Graphene field-effect transistors (GFETs) exhibit negligible transconductance under two scenarios: for any gate-to-source voltage when the drain-to-source voltage is set to zero and for an arbitrary drain-to-source voltage provided that the gate-to-source voltage equals the Dirac voltage. Hence, extracting the channel and the parasitic series resistances from <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${S}$ </tex-math></inline-formula> -parameters under these conditions enables analyzing their dependence on the gate and drain biases. This is fundamental to assess the portion of the output resistance that is controlled by the gate. Besides, the drain bias dependence of the drain and source resistances is also evidenced. Within the proposal, resistive components accounting for the lossy nature of the gate capacitance are incorporated into the model, which exhibits a broadband correlation with experimental data. This avoids the series resistances to be considered as frequency dependent in the model. Transconductance ; Graphene ; Microwave ; Materials science ; Optoelectronics ; Characterization (materials science) ; Zero (linguistics) ; Condensed matter physics ; Nanotechnology ; Physics ; Transistor ; Electrical engineering ; Engineering ; Quantum mechanics ; Voltage Graphene research and applications ; Advancements in Semiconductor Devices and Circuit Design ; Advanced Memory and Neural Computing
Authors: Prithwish Ghosh | Shinjon Chakraborty
Source:  (article, 2023-04-28)
Field: Chemistry — Analytical Chemistry

Spectral Classification of Quasar Subject to Redshift: A Statistical Study Quasars are astronomical star-like objects having a large ultraviolet flux of radiation accompanied by generally broad emission lines and absorption lines in some cases found at large redshift. The used data is extracted from the Veron Cetti Catalogue of AGN and Quasar. The objective of this work is to partition the quasar based on their spectral properties using multivariate techniques and classify them with respect to the obtained clusters. Performing the K-means partitioning method, two robust clusters were obtained with cluster sizes 39,581 and 129,377. The percentage of misclassification observed based on the obtained clusters considering a multivariate classification technique and machine learning classification algorithm, i.e., linear discriminant analysis and XG-Boost, respectively. The linear discriminant analysis and XG-Boost evaluated a misclassification of around 0.84 and 0.15%, respectively. Additionally, a heuristic literature-based categorization subject to redshift yielded an accuracy of around 96 %. This gives us cross-validating arguments about the astronomical data, that machine learning algorithms might perform on par with conventional multivariate techniques, if not better. Quasar ; Redshift ; Linear discriminant analysis ; Astrophysics ; Pattern recognition (psychology) ; Categorization ; Artificial intelligence ; Multivariate statistics ; Computer science ; Physics ; Discriminant ; Machine learning Spectroscopy and Chemometric Analyses ; Astronomy and Astrophysical Research ; Advanced Statistical Methods and Models
Authors: Yoshio Miura
Source: Journal of the Magnetics Society of Japan (article, 2023-06-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

First-Principles Studies on Spin-Dependent Transport of Magnetic Junctions with Half-Metallic Heusler Compounds Two types of magnetoresistance (MR), i.e., tunnel magnetoresistance (TMR) and current perpendicular to plane giant magnetoresistance (CPP-GMR), are theoretically discussed for systems with half-metallic (HFM) Co-based full Heusler compounds. In TMR, the non-collinear spin structure at the Co2MnSi(CMS)/MgO(001) interface that results from thermal spin fluctuations significantly reduced the TMR ratio at room temperature (RT). Enhancement of the exchange stiffness of CMS/MgO was essential to suppress the reduction in TMR at RT. Furthermore, it is proposed that inserting of a B2-CoFe layer between CMS and MgO is a promising way to enhance the interface exchange stiffness constant. In CPP-GMR, the interface spin asymmetry γ in the Valet-Fert model was essential to enhance GMR at RT, because the temperature dependence of γ in experiments was much larger than that of the bulk spin asymmetry β. I showed that the experimental CPP-GMR ratio increases with the decrease in the theoretical resistance-area product RPA, which is roughly consistent with the RP dependence of γ. This means that matching of the conductive channel between HMF and a non-magnetic metallic spacer is a key parameter to enhance γ. These findings will be very important for room temperature spintronics devices applied in future artificial intelligence hardware. Spintronics ; Materials science ; Condensed matter physics ; Magnetoresistance ; Giant magnetoresistance ; Tunnel magnetoresistance ; Spin (aerodynamics) ; Metal ; Asymmetry ; Perpendicular ; Layer (electronics) ; Nanotechnology ; Magnetic field ; Physics ; Ferromagnetism ; Thermodynamics Heusler alloys: electronic and magnetic properties ; Magnetic properties of thin films ; MXene and MAX Phase Materials
Authors: Mingzheng Jia | Liang Li | Baolin Xiong | Le Feng | Wenbo Cheng | Wen‐Fei Dong
Source: Bioengineering (article, 2023-09-12)
Field: Chemistry — Spectroscopy

Multi-Parameter Auto-Tuning Algorithm for Mass Spectrometer Based on Improved Particle Swarm Optimization Quadrupole mass spectrometers (QMS) are widely used for clinical diagnosis and chemical analysis. To obtain the best experimental results, mass spectrometers must be calibrated to an ideal setting before use. However, tuning the current QMS is challenging. Traditional tuning techniques possess low automation levels and rely primarily on skilled engineers. Therefore, in this study, we propose an innovative auto-tuning algorithm for QMS based on the improved particle swarm optimization (PSO) algorithm to automatically find the optimal solution of QMS parameters and make the QMS reach the optimal state. The improved PSO algorithm is combined with simulated annealing, multiple inertia weights, dynamic boundaries, and other methods to prevent the traditional PSO algorithm from the issue of a local optimal solution and premature convergence. According to the characteristics of the mass spectrum peaks, a termination function is proposed to simplify the termination conditions of the PSO algorithm and further improve the automation level of the mass spectrometer. The results of auto-calibration testing of resolution and mass axis show that both resolution and mass axis calibration could effectively meet the requirements of mass spectrometry experiments. By the experiment of auto-optimization testing of lens and ion source parameters, these parameters were all in the vicinity of the optimal solution, which achieved the expected performance. Through numerous experiments, the reproducibility of the algorithm was established as meeting the auto-tuning function of the QMS. The proposed method can automatically tune the mass spectrometer from its non-optimal condition to the optimal one, which can effectively reduce the tuning difficulty of QMS. Particle swarm optimization ; Computer science ; Algorithm ; Automation ; Spectrometer ; Calibration ; Mass spectrometry ; Simulated annealing ; Inertia ; Engineering ; Mathematics ; Physics ; Mechanical engineering ; Optics Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Yunchi Zhu | Chengda Tong | Zuo-Han Zhao | Zuhong Lu
Source: Database (article, 2023-01-01)
Field: Chemistry — Spectroscopy

MineProt: a stand-alone server for structural proteome curation AlphaFold-like systems are rapidly expanding the scale of proteome structuring, and MineProt provides an effective solution for custom curation of these novel high-throughput data. It enables researchers to build their own server in simple steps, run almost out-of-the-box scripts to annotate and curate their proteins, analyze their data via a user-friendly online interface, and utilize plugins to extend the functionality of server. It is expected to support researcher productivity and facilitate data sharing in the new era of structural proteomics. Database URL MineProt is open-source software available at https://github.com/huiwenke/MineProt. Computer science ; Scripting language ; Interface (matter) ; Software ; World Wide Web ; Plug-in ; Proteome ; Database ; Operating system ; Bioinformatics Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Machine Learning in Bioinformatics