jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ruoling Deng | Weisen Liu | Haitao Liu | Qiang Liu | Jing Zhang | Mingxin Hou
Source: Agronomy (article, 2024-10-17)
Field: Chemistry — Analytical Chemistry

Non-Destructive Measurement of Rice Spikelet Size Based on Panicle Structure Using Deep Learning Method Rice spikelet size, spikelet length and spikelet width, are very important traits directly related to a rice crop’s yield. The accurate measurement of these parameters is quite significant in research such as breeding, yield evaluation and variety improvement for rice crops. Traditional measurement methods still mainly rely on manual labor, which is time-consuming, labor-intensive and error-prone. In this study, a novel method, dubbed the “SSM-Method”, based on convolutional neural network and traditional image processing technology has been developed for the efficient and precise measurement of rice spikelet size parameters on rice panicle structures. Firstly, primary branch images of rice panicles were collected at the same height to build an image database. The spikelet detection model using convolutional neural network was then established for spikelet recognition and localization. Subsequently, the calibration value was obtained through traditional image processing technology. Finally, the “SSM-Method” integrated with a spikelet detection model and calibration value was developed for the automatic measurement of spikelet sizes. The performance of the developed SSM-Method was evaluated through testing 60 primary branch images. The test results showed that the root mean square error (RMSE) of spikelet length for two rice varieties (Huahang15 and Qingyang) were 0.26 mm and 0.30 mm, respectively, while the corresponding RMSE of spikelet width was 0.27 mm and 0.31 mm, respectively. The proposed algorithm can provide an effective, convenient and low-cost tool for yield evaluation and breeding research. Panicle ; Agronomy ; Mathematics ; Biology ; Artificial intelligence ; Biological system ; Botany ; Computer science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: A. Babou | Yasmina Kerboua Ziari | Bachir Dadda | Toufik Chergui | Youcef Kerkoub | Oumaima Brakni
Source: Journal of Renewable Energies (article, 2024-09-18)
Field: Materials Science — Materials Chemistry

Heat transfer enhancement in a large-scale Ti-Mn based metal hydride storage reactor with nanofluids using open source CFD software Metals can safely store hydrogen with high energy densities in the form of metal hydrides through an exothermic process. However, the slow hydrogen absorption kinetics significantly decreases its storage rate. Ensuring efficient heat dissipation from the metal hydride bed can result in a faster charging rate, which in turn improves the storage performance. The objective of this work is to improve the rate of heat and mass transfer in a Ti-Mn-based metal hydrides reactor for large-scale applications using a 3D model. Finite volume simulations with OpenFOAM software were conducted to investigate the influence of various parameters on the hydride reactors’ performance. Water-based alumina (Al2O3/H2O) nanofluid with varying volume fractions up to 5% are used as heat transfer fluids. The results show that accelerating the coolant flow velocity, decreasing its inlet temperature, and increasing the hydrogen supply pressure contribute further to enhancing thermal performance. Compared to pure water, the Al2O3/H2O nanofluid with 5 vol % can improve heat transfer by approximately 11.5%. This can reduce the time needed to reach 90% storage by 18.1%. Also, the pressure drop throughout the hydride reactor at different flow velocities is slightly greater than that in pure water. Nanofluid ; Computational fluid dynamics ; Hydride ; Open source ; Nuclear engineering ; Materials science ; Open source software ; Heat transfer ; Heat transfer enhancement ; Scale (ratio) ; Chemical engineering ; Software ; Process engineering ; Metal ; Thermodynamics ; Computer science ; Metallurgy ; Engineering ; Heat transfer coefficient ; Physics ; Operating system Hydrogen Storage and Materials
Authors: Raphaël Carpintero Perez | Sébastien da Veiga | Josselin Garnier | Brian Staber
Source: arXiv (Cornell University) (preprint, 2024-02-06)
Field: Materials Science — Materials Chemistry

Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels Supervised learning has recently garnered significant attention in the field of computational physics due to its ability to effectively extract complex patterns for tasks like solving partial differential equations, or predicting material properties. Traditionally, such datasets consist of inputs given as meshes with a large number of nodes representing the problem geometry (seen as graphs), and corresponding outputs obtained with a numerical solver. This means the supervised learning model must be able to handle large and sparse graphs with continuous node attributes. In this work, we focus on Gaussian process regression, for which we introduce the Sliced Wasserstein Weisfeiler-Lehman (SWWL) graph kernel. In contrast to existing graph kernels, the proposed SWWL kernel enjoys positive definiteness and a drastic complexity reduction, which makes it possible to process datasets that were previously impossible to handle. The new kernel is first validated on graph classification for molecular datasets, where the input graphs have a few tens of nodes. The efficiency of the SWWL kernel is then illustrated on graph regression in computational fluid dynamics and solid mechanics, where the input graphs are made up of tens of thousands of nodes. Computer science ; Solver ; Graph ; Theoretical computer science ; Kernel (algebra) ; Graph kernel ; Algorithm ; Machine learning ; Mathematics ; Mathematical optimization ; Kernel method ; Kernel embedding of distributions ; Discrete mathematics ; Support vector machine Machine Learning in Materials Science
Authors: Satish Chinchanikar | Nitin Motgi
Source: Frattura ed Integrità Strutturale (article, 2024-09-05)
Field: Materials Science — Materials Chemistry

Tool wear evaluation of self-propelled rotary tool and conventional round tool during turning Inconel 718 Enhancing the machinability of difficult-to-cut materials is imperative, and a non-conventional rotary tool has shown high potential when machining these materials. This work comparatively evaluates the tool wear of conventional round tools (CRTs) and self-propelled rotary tools (SPRTs) when turning Inconel 718. Tool wear progression over time was measured and analyzed, simulated for various cutting conditions by creating mathematical and ANN models. This study found a 67% increase in tool life for SPRTs over CRTs, especially at a higher cutting speed of 65 m/min, due to improved heat transmission and steady wear distribution. However, at lower cutting conditions, the tool life gain was 15–18%, indicating that SPRTs could be reliably used at higher cutting conditions to achieve a machining economy. SPRTs exhibited better chip control and reduced built-up edge formation than CRTs. The cutting speed had the largest impact on tool flank wear, with machining time, feed, and depth of cut following closely behind. However, this effect was more prominent for CRTs. The 0.2 mm tool wear criterion was found to be more feasible since tool failure was caused by cutting tool chipping at this threshold instead of progressive growth of flank wear during Inconel 718 turning. Inconel ; Tool wear ; Mechanical engineering ; Materials science ; Computer science ; Engineering ; Metallurgy ; Machining Metal Alloys Wear and Properties ; Advanced machining processes and optimization ; Advanced Machining and Optimization Techniques
Authors: Shaojie Li | Jianfeng Jin | Hao Sun | Yongbo Wang | Yuping Ren | Mingtao Wang | Gaowu Qin
Source: Nanomaterials (article, 2024-11-11)
Field: Materials Science — Biomaterials

Micromechanics Modeling on Mechanical Properties in Mg Alloys with Bimodal Grain Size Distribution Bimodal grain structure (BGS) Mg alloys containing a high fraction of fine grains (FGs) and a low fraction of coarse grains (CGs) show a good combination of strength and plasticity. Here, taking the ZK60 alloy as an example, the influences of CG size, volume fraction, and texture intensity on mechanical properties and the hetero-deformation-induced (HDI) effect were examined using the Mori-Tanaka mean-field method combined with strain gradient theory of plasticity. The results indicate that the overall mechanical properties decrease with an increase in CG size because the limited HDI effect cannot compensate for the strength and plasticity decrease derived from larger CGs. A higher aspect ratio of CG along the loading direction can weaken the HDI effect and subsequently reduce the overall mechanical properties. Optimal comprehensive mechanical properties can be achieved when the CG volume fraction is approximately 30%. Furthermore, an increasing basal texture intensity in CG results in higher yield strength and lower ultimate tensile strength, while the uniform elongation reaches a maximum value when ~60% of CGs possess hard orientations with Euler angles of (0~30°, 0°, 0°). Micromechanics ; Materials science ; Grain size ; Particle-size distribution ; Composite material ; Metallurgy ; Particle size ; Chemical engineering ; Composite number ; Engineering Magnesium Alloys: Properties and Applications ; Microstructure and mechanical properties ; Aluminum Alloys Composites Properties
Authors: Corinne Steiner | Rebecca Rahmel | Frank Volmer | Reiner Windisch | L. Janßen | P. Pesch | Kenji Watanabe | Takashi Taniguchi | Florian Libisch | Bernd Beschoten | Christoph Stampfer | Annika Kurzmann
Source: JuSER (Forschungszentrum Jülich) (preprint, 2024-11-21)
Field: Materials Science — Materials Chemistry

Current-induced brightening of vacancy-related emitters in hexagonal boron nitride We perform photoluminescence measurements on vacancy-related emitters in hexagonal boron nitride (hBN) that are notorious for their low quantum yields. The gating of these emitters via few-layer graphene electrodes reveals a reproducible, gate-dependent brightening of the emitter, which coincides with a change in the direction of the simultaneously measured leakage current across the hBN layers. At the same time, we observe that the relative increase of the brightening effect scales linearly with the intensity of the excitation laser. Both observations can be explained in terms of a photo-assisted electroluminescence effect. Interestingly, emitters can also show the opposite behavior, i.e. a decrease in emitter intensity that depends on the gate leakage current. We explain these two opposing behaviors with different concentrations of donor and acceptor states in the hBN and show that precise control of the doping of hBN is necessary to gain control over the brightness of vacancy-related emitters by electrical means. Our findings contribute to a deeper understanding of vacancy-related defects in hBN that is necessary to make use of their potential for quantum information processing. Vacancy defect ; Hexagonal boron nitride ; Hexagonal crystal system ; Materials science ; Boron ; Boron nitride ; Current (fluid) ; Nitride ; Condensed matter physics ; Engineering physics ; Nanotechnology ; Crystallography ; Chemistry ; Physics ; Nuclear physics ; Thermodynamics Graphene research and applications ; Diamond and Carbon-based Materials Research ; Boron and Carbon Nanomaterials Research
Authors: Yuhang Li | Shen‐Hsing Annabel Chen | Bijie Bai | Aydogan Ozcan
Source: arXiv (Cornell University) (preprint, 2024-10-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Lying mirror We introduce an all-optical system, termed the "lying mirror", to hide input information by transforming it into misleading, ordinary-looking patterns that effectively camouflage the underlying image data and deceive the observers. This misleading transformation is achieved through passive light-matter interactions of the incident light with an optimized structured diffractive surface, enabling the optical concealment of any form of secret input data without any digital computing. These lying mirror designs were shown to camouflage different types of input image data, exhibiting robustness against a range of adversarial manipulations, including random image noise as well as unknown, random rotations, shifts, and scaling of the object features. The feasibility of the lying mirror concept was also validated experimentally using a structured micro-mirror array along with multi-wavelength illumination at 480, 550 and 600 nm, covering the blue, green and red image channels. This framework showcases the power of structured diffractive surfaces for visual information processing and might find various applications in defense, security and entertainment. Lying ; Physics ; Medicine Metamaterials and Metasurfaces Applications ; Random lasers and scattering media ; Photonic Crystals and Applications
Authors: Thuc Anh Ngo | Tanju Yildirim | Meng‐Qun Feng | Kosuke Minami | Kota Shiba | Genki Yoshikawa
Source: Advanced Sensor Research (article, 2024-11-29)
Field: Chemistry — Physical and Theoretical Chemistry

Empirical Modification of Force Fields for the Development of Peptide‐Based Gas Sensors Abstract Molecular dynamics models combined with computational approaches can be used as advanced screening techniques for finding highly efficient material‐molecule interactions based on binding affinity, including in the development of gas sensors. However, most models are originally designed for liquid phase interactions, which do not align with gas sensing conditions, resulting in lower‐than‐expected performance. This study introduces an empirical modification method to adjust peptide interaction models for a gas phase, aiming to better accommodate the interaction between pentapeptides and target gas molecules. By adapting the weights of terms in the Gibbs free energy equation given in an empirical force field model, we demonstrate a significant increase in the absolute value of coefficient of determination ( R 0 2 ) , from an average of 0.05 with conventional liquid phase models to 0.90 with proposed gas phase models. An empirical modification technique for gas phase interactions markedly enhances the prediction accuracy of models, facilitating the effective development of peptide‐based gas sensors. Peptide ; Nanotechnology ; Materials science ; Chemistry ; Biochemistry thermodynamics and calorimetric analyses ; Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies
Authors: Sara Marziali | Giacomo Nunziati | Alessia Lucia Prete | Neri Niccolai | Monica Bianchini
Source: SoftwareX (article, 2024-06-24)
Field: Chemistry — Spectroscopy

SADIC v2: A modern implementation of the Simple Atom Depth Index Calculator Protein structure analysis plays a primary role in understanding their biological functions. Being able to determine the atom depth index within the protein is crucial to gain insights into molecular interactions and structural stability. To address this need, the original version of Simple Atom Depth Index Calculator (SADIC) software was developed in 2006. However, with the rapid advancement of computational methodologies and the evolution of programming libraries, the original SADIC software has become obsolete and incompatible with modern computational environments. This is why we present SADIC v2, a modernized version of the software that is fully compatible and integrated with modern Python libraries. Calculator ; Computer science ; Simple (philosophy) ; Index (typography) ; Atom (system on chip) ; Arithmetic ; Computer graphics (images) ; Algorithm ; Computational science ; Programming language ; Parallel computing ; Mathematics ; Operating system ; Philosophy ; Epistemology Mass Spectrometry Techniques and Applications ; Advanced Chemical Physics Studies ; Spectroscopy and Quantum Chemical Studies
Authors: Henryk A. Witek | Rafał Podeszwa
Source: Molecules (article, 2024-08-24)
Field: Chemistry — Organic Chemistry

Kekulé Counts, Clar Numbers, and ZZ Polynomials for All Isomers of (5,6)-Fullerenes C52–C70 We report an extensive tabulation of several important topological invariants for all the isomers of carbon (5,6)-fullerenes Cn with <i>n</i> = 52-70. The topological invariants (including Kekulé count, Clar count, and Clar number) are computed and reported in the form of the corresponding Zhang-Zhang (ZZ) polynomials. The ZZ polynomials appear to be distinct for each isomer cage, providing a unique label that allows for differentiation between various isomers. Several chemical applications of the computed invariants are reported. The results suggest rather weak correlation between the Kekulé count, Clar count, Clar number invariants, and isomer stability, calling into doubt the predictive power of these topological invariants in discriminating the most stable isomer of a given fullerene. The only exception is the Clar count/Kekulé count ratio, which seems to be the most important diagnostic discovered from our analysis. Stronger correlations are detected between Pauling bond orders computed from Kekulé structures (or Clar covers) and the corresponding equilibrium bond lengths determined from the optimized DFTB geometries of all 30,579 isomers of C<sub>20</sub>-C<sub>70</sub>. Chemistry ; Fullerene ; Combinatorics ; Double bond ; Topology (electrical circuits) ; Mathematics ; Organic chemistry Fullerene Chemistry and Applications ; Synthesis and Properties of Aromatic Compounds ; Carbon Nanotubes in Composites
Authors: Yusreni Warmi | Sitti Amalia | Zulkarnaini Zulkarnaini | Dasman Dasman | Antonov Bachtiar | Zuriman Anthony | Hamdi Azhar
Source: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (article, 2024-06-04)
Field: Materials Science — Materials Chemistry

Modeling and simulation for flashover location determination on 150 kV insulator string The 150 kV Payakumbuh-Koto Panjang transmission line in West Sumatra is located in an area with high lightning activity. Based on Meteorological, Climatological, and Geophysical Agency (BMKG) data (2017-2023), the average number of lightning days per year (IKL: isokeraunic level) reaches 165-173 days/year, and 79% of the transmission towers are located in hilly and rocky areas. This causes contamination of the insulator, which can reduce its performance and cause flashovers in the insulator circuit. However, in the field, finding flash points in insulators is still a challenge. Therefore, simulation must be used as a tool to determine the location of flashover in an insulator circuit that is affected by temperature and humidity. Simulation by modeling flashover provides an effective solution for determining the location of flashover in insulator circuits, which is the novelty of this research. This research compares laboratory test results with manual calculations modeled using Visual Basic 6. The research results show that temperature and humidity have a significant influence on determining the flashover voltage value on the insulator. The flashover locations during the test are the same as the calculated flashover locations, as shown by these simulations and modeling. Arc flash ; Insulator (electricity) ; Transmission line ; Environmental science ; Meteorology ; Humidity ; Electric power transmission ; Icing ; Voltage ; Electrical engineering ; Engineering ; Marine engineering ; Physics High voltage insulation and dielectric phenomena ; Lightning and Electromagnetic Phenomena ; Thermal Analysis in Power Transmission
Authors: Zhaozhi Wang | Yue Liu | Yunjie Tian | Yunfan Liu | Yaowei Wang | Qixiang Ye
Source: arXiv (Cornell University) (preprint, 2024-05-26)
Field: Materials Science — Materials Chemistry

Building Vision Models upon Heat Conduction Visual representation models leveraging attention mechanisms are challenged by significant computational overhead, particularly when pursuing large receptive fields. In this study, we aim to mitigate this challenge by introducing the Heat Conduction Operator (HCO) built upon the physical heat conduction principle. HCO conceptualizes image patches as heat sources and models their correlations through adaptive thermal energy diffusion, enabling robust visual representations. HCO enjoys a computational complexity of O(N^1.5), as it can be implemented using discrete cosine transformation (DCT) operations. HCO is plug-and-play, combining with deep learning backbones produces visual representation models (termed vHeat) with global receptive fields. Experiments across vision tasks demonstrate that, beyond the stronger performance, vHeat achieves up to a 3x throughput, 80% less GPU memory allocation, and 35% fewer computational FLOPs compared to the Swin-Transformer. Code is available at https://github.com/MzeroMiko/vHeat. Thermal conduction ; Materials science ; Composite material Machine Learning in Materials Science
Authors: Tianbi Zhang | Lukas Berners | Jakub Holzer | T. Ben Britton
Source: arXiv (Cornell University) (preprint, 2024-11-20)
Field: Materials Science — Surfaces, Coatings and Films

Comparison of Kikuchi Diffraction Geometries in Scanning Electron Microscope Recent advances in scanning electron microscope (SEM) based Kikuchi diffraction have demonstrated the important potential for reflection and transmission methods, like transmission Kikuchi diffraction (TKD) and electron backscatter diffraction (EBSD). Furthermore, with the advent of compact direct electron detectors (DED) it has been possible to place the detector in a variety of configurations within the SEM chamber. This motivates the present work where we explore the similarities and differences of the different geometries that include on-axis TKD &amp; off-axis TKD using electron transparent samples, as well as more conventional EBSD. Furthermore, we compare these with the newest method called "reflection Kikuchi diffraction" RKD where the sample is placed flat in the chamber and the detector is placed below the pole piece. Through remapping collected diffraction patterns, all these methods can be used to generate an experimental "diffraction sphere" that can be used to explore diffraction from any scattering vector from the unit cell, as well as the ability to perform band profile analysis. This diffraction sphere approach enables us to further probe specific differences between the methods, including for example thickness effects in TKD that can result in the generation of diffraction spots, as well as electron scattering path length effects that result in excess and deficiency variations, as well as inversion of bands in experimental patterns. Scanning electron microscope ; Diffraction ; Kikuchi line ; Electron microscope ; Materials science ; Electron diffraction ; Electron ; Optics ; Reflection high-energy electron diffraction ; Electron backscatter diffraction ; Physics ; Nuclear physics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Microstructure and mechanical properties