jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Asokan Ajith | Mohanachandran Nair Sindhu Swapna | Humberto Cabrera | Sankaranarayana Iyer Sankararaman
Source: RUNG (article, 2023-04-25)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Comprehensive analysis of copper plasma The emergence of diversified applications of laser-induced breakdown spectroscopy in the biomedical field, electronics, space physics, and material processing necessitates a comprehensive understanding of plasma parameters. The present work delineates the structure and evolution of copper plasma under different ambient pressures (0.01 mbar to 100 mbar) along with other plasma parameters. The study reveals the role of ambient pressure in the increase of plasma temperature (Te), electron density (Ne), number of particles in the Debye sphere, plasma frequency, inverse bremsstrahlung absorption coefficient, electron thermal velocity, electron–ion collision frequency and in the decrease of Debye length (λD) and plasma skin depth (PSD). The experimental techniques and the theoretical explanations for the variation of plasma parameters and their applications are also detailed. As the ambient pressure increases, the motion of plasma species becomes restricted, resulting in the increase of Te, calculated using the Boltzmann plot. From the values of λD, PSD, and Ne, it is understood that the copper plasma under investigation is thermally non-relativistic and satisfies McWhirter’s criterion, thus, revealing the local thermodynamic equilibrium condition of plasma. The effects of Debye shielding and stark broadening on the spectral lines are also investigated. Thus, the study helps bring newfangled dimensions to the application of plasma by exploring the possibility of tailoring plasma parameters. Plasma ; Bremsstrahlung ; Dense plasma focus ; Copper ; Plasma diagnostics ; Debye length ; Plasma parameters ; Boltzmann constant ; Debye ; Electron density Copper Interconnects and Reliability ; Vacuum and Plasma Arcs ; Laser-induced spectroscopy and plasma
Authors: Ikram Kouidri | Djilali Kaidameur | Mehdi Zahraoui
Source: Acta periodica technologica (article, 2023-01-01)
Field: Materials Science — Biomaterials

Experimental and statistical analysis on the effects of fouling and effective parameters on performance of heat exchanger Increasing the performance of heat exchangers is one of the main objectives of researchers and engineers in the industry. In this paper an experimental work is carried out aiming at modeling the efficiency of shell and tube heat exchanger under the influence of the most contributing factors on performance as fouling resistance, the inlet temperatures and the flow rate of the fluids. An experimental design method of type 31.24 was used for the studies, requiring 48 tests with three repeats. The following factors are taken into account: the inlet temperature and flow rate of crude oil fluid and TEG fluid on two levels, and the fouling resistance on three levels. Regression analysis was produced a mathematical model for the efficiency based on the influential variables. The response surface and contour plots were allowed the selected from the optimum and predicted the behaviors of parameters. The effectiveness decreases considerably with the increase in fouling resistance and the decrease of inlet temperatures and flow rates. Fouling ; Heat exchanger ; Inlet ; Volumetric flow rate ; Work (physics) ; Flow resistance ; Dynamic scraped surface heat exchanger ; Shell and tube heat exchanger ; Flow (mathematics) ; Mechanics ; Materials science ; Environmental science ; Process engineering ; Petroleum engineering ; Chemistry ; Mechanical engineering ; Engineering ; Heat transfer ; Heat transfer coefficient ; Physics Calcium Carbonate Crystallization and Inhibition ; Magnetic and Electromagnetic Effects ; Freezing and Crystallization Processes
Authors: Devin Seay | I. P. Fernando | D. M. Keller
Source:  (article, 2023-03-15)
Field: Chemistry — Spectroscopy

Polarization Measurements with Deep Learning Analysis of Nuclear Magnetic Resonance Constant current continuous wave Nuclear Magnetic Resonance (NMR) has been an essential tool for polarized target experiments in Nuclear and High-energy physics. Q-meter based phase- sensitive detection can provide accurate monitoring of the polarization over the course of a scattering experiment with limitations due to some operational parameters. In this talk, we present recent studies of improved signal to noise in NMR-based Spin-1 polarization measurements as well as reliable measurements outside of the designated range of the Q-meter’s operational parameters with the use of machine learning (ML). This approach will allow for real time online polarization monitoring and offline polarization data analysis for improved overall figure of merit for experiments using solid state polarized targets. Polarization (electrochemistry) ; Hyperpolarization (physics) ; Physics ; Scattering ; Nuclear magnetic resonance ; Computer science ; Computational physics ; Optics ; Nuclear magnetic resonance spectroscopy ; Chemistry Advanced NMR Techniques and Applications ; Nuclear Physics and Applications ; Superconducting Materials and Applications
Authors: Pei Xiong | Daniel K. Nikolov | Fei Cheng | Jannick P. Rolland | A. Nick Vamivakas
Source: arXiv (Cornell University) (preprint, 2023-10-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

All-dielectric hybrid VIS-NIR dual-function metasurface Metasurfaces are a promising technology that can serve as a compact alternative to conventional optics while providing multiple functions depending on the properties of the incident light, such as the wavelength, polarization, and incident angle. Here, we demonstrate a hybrid VIS-NIR dielectric metasurface that can reflect 940 nm light into a specified direction while transmitting visible light (450-750 nm). The dual functionality is realized by combining an aperiodic distributed Bragg reflector with dielectric meta-tokens. Experimental demonstration is also reported, showing an anomalous reflection of near-infrared (NIR) light within a 20o full field-of-view (FOV) and the transmission of wavelengths from 450 nm to 750 nm. Optics ; Dielectric ; Aperiodic graph ; Wavelength ; Polarization (electrochemistry) ; Optoelectronics ; Materials science ; Ray ; Reflector (photography) ; Reflection (computer programming) ; Visible spectrum ; Physics ; Computer science ; Light source Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Optical Imaging Technologies
Authors: W.E. Ryan | Dirk Husmeier | Olaf J. Rolinski | Vladislav Vyshemirsky
Source: Proceedings of the International Conference on Statistics, Theory and Applications (ICSTA ...) (article, 2023-08-01)
Field: Chemistry — Analytical Chemistry

Bayesian Model Selection and Emulation for Protein Fluorescence Fluorescence decay of amino acids in protein is a complex process for which multiple models have been proposed.Likelihood function evaluation for certain models can be computationally expensive, and as such surrogate models may be introduced to speed up inference.In this paper, Gaussian processes are implemented in likelihood estimation of a range of models defined by convolutions of an initial excitation input and a decay function using both synthetic and real world data.Parameter inference and model selection using the surrogate models are performed and compared against the exact results.Model selection when incorporating surrogate models into the inference process is shown to be consistent. Emulation ; Computer science ; Selection (genetic algorithm) ; Bayesian probability ; Model selection ; Artificial intelligence ; Machine learning Spectroscopy and Chemometric Analyses ; Gene expression and cancer classification
Authors: Rhowel M. Dellosa
Source: International Journal of Biosciences (IJB) (article, 2023-07-08)
Field: Chemistry — Analytical Chemistry

Determining the classification of dry beans using WEKA The significant variety in bean shape and size makes dry bean classification a difficult task.Traditional categorization procedures, such as hand sorting, are time-consuming and labor-intensive.Machine learning approaches appear to be a potential option for dry bean classification.A machine learning classification approach for dry beans using WEKA was offered in this research.The approach employs Multilayer Perceptron (MLP), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Decision Tree (DT) machine learning algorithms.The method was evaluated on a dataset of 13,611 dry beans from seven different varieties shared by Koklu, M. and Ozkan, I.A., (2020) extracted from the UCI machine learning repository.The approaches attained an accuracy of 90.30%, 90.83%, 92.23% and 92.49% for k-nearest neighbor, decision tree, support vector machine and multilayer perceptron respectively.The multilayer perceptron has the highest accuracy while the k-nearest neighbor has the lowest accuracy performance.The suggested method offers various advantages over conventional dry bean classification methods.It is more accurate, faster, and requires less labor.The method can also be used to classify dry beans that are difficult to identify visually.According to the findings of this study, machine learning approaches provide a potential strategy for dry bean classification.The proposed method can be utilized to automate the dry bean classification process, which could result in considerable efficiency and accuracy gains and the algorithm that performs the best accuracy may be used for classifications of Dry Beans in the Philippines. Mathematics ; Agronomy ; Biology Spectroscopy and Chemometric Analyses
Authors: Madson Poltronieri Zanoni | Pedro Henrique Pereira da Cunha | Gabriely S. Folli | Paulo R. Filgueiras
Source: Revista Ifes Ciência (article, 2023-10-01)
Field: Chemistry — Analytical Chemistry

O USO DO REDGIM PARA CARACTERIZAR E DISTINGUIR AZEITES EXTRAVIRGEM DE OLIVA ADULTERADOS COM DIFERENTES ÓLEOS VEGETAIS A aplicação de diversos softwares que são capazes de analisar imagens, mais especificamente os pixels, e discriminar a presença e a concentração de diversos compostos tem crescido nos últimos anos. O REDGIM como ferramenta de análise é capaz de avaliar a presença de adulterantes em diversos alimentos. Portanto, este trabalho teve como objetivo validar o potencial de análise do REDGIM em misturas de óleos vegetais (OVs) em óleos de azeites extravirgens (EVOOs). Fez-se uso de smartphone, uma bateria portátil e uma lâmpada LED para auxiliar durante as análises dos conjuntos amostrais de EVOO e OV via REDGIM e assim minimizar um possível erro externo como a variação da intensidade de luz no ambiente. As amostras preparadas e analisadas via REDGIM tinham teores de 1/99; 3/97; 5/95; 35/65; 55/45 e 80/20 % (OV/EVOO) e delas produzidos modelos de PCA e PLS pelo próprio software. Os valores de RMSEP obtidos pela curva de calibração para as amostras adulteradas com soja (2,2 % v/v), girassol (5,4 % v/v), canola (0,3 % v/v), algodão (2,4 % v/v), milho (0,7 % v/v) e blend (2,0 % v/v) mostraram boa acuraria na determinação dos adulterantes em EVOO. A dois EVOOs adulterados com OVs via REDGIM demonstrou que o software para análise in loco é eficiente e traz resultados concretos, além de fornecer informações satisfatórias sobre as amostras adulteradas demonstrando sua alta aplicabilidade em campo. Humanities ; Physics ; Philosophy Spectroscopy and Chemometric Analyses ; Dye analysis and toxicity ; Identification and Quantification in Food
Authors: Chen Chen | Sai Chen | Yibo Ni | Yibao Xu | Yuanmu Yang
Source: arXiv (Cornell University) (preprint, 2023-11-21)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ultrathin liquid crystal metasurface for on-demand terahertz beam forming over 110° field-of-view The terahertz spectral region, which bridges between electronics and optics, is poised to play an important role in the development of transformative wireless communication and imaging systems with unprecedented functionality. Currently, a major challenge in terahertz technology is to develop high-performance terahertz beam-forming devices that can dynamically shape the terahertz radiation in a flexible manner. Existing terahertz beam-forming devices have limited coding bits, field-of-view, and beam gain. Here, we experimentally demonstrate a reconfigurable liquid crystal-integrated terahertz metasurface, with each metasurface unit cell being independently addressable. The metasurface has a 260° continuous phase tuning range with a device thickness of only 1% of the free-space wavelength. We show that the terahertz wave diffracted from the metasurface can be steered towards a wide range of directions, covering a record-large 110° field-of-view with a peak gain of 25 dBi. The metasurface also features a low power consumption and sub-second switching time. Furthermore, we demonstrate the formation of multiple terahertz beams, with the direction of each beam and the power ratio between beams adjustable on demand. The proposed liquid crystal metasurface possesses compelling prospects for future terahertz communication and imaging applications. Terahertz radiation ; Terahertz gap ; Optics ; Beam (structure) ; Beam steering ; Optoelectronics ; Materials science ; Electronics ; Physics ; Far-infrared laser ; Terahertz metamaterials ; Electrical engineering ; Laser ; Engineering Metamaterials and Metasurfaces Applications ; Millimeter-Wave Propagation and Modeling ; Terahertz technology and applications
Authors: Jonas Brown | Maedeh Taheri | Kargar, Fariborz | Ruben Salgado | Tekwam Geremew | Sergey Rumyantsev | Roger K. Lake | Alexander A. Balandin
Source: arXiv (Cornell University) (preprint, 2023-07-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Conductance Fluctuations and Domain Depinning in Quasi-2D Charge-Density-Wave 1T-TaS$_2$ Thin Films We investigated the temperature dependence of the conductance fluctuations in thin films of the quasi-two-dimensional 1T-TaS$_2$ van der Waals material. The conductance fluctuations, determined from the derivative current-voltage characteristics of two-terminal 1T-TaS$_2$ devices, appear prominently at the electric fields that correspond to the transitions between various charge-density-wave macroscopic quantum condensate phases and at the onset of the depinning of the charge density wave domains. The depinning threshold field, $E_D$, monotonically increases with decreasing temperature within the nearly commensurate charge-density-wave phase. The $E_D$ value increases with the decreasing 1T-TaS$_2$ film thickness, revealing the surface pinning of the charge density waves. Our analysis suggests that depinning is absent in the commensurate phase. It is induced by the electric field but facilitated by local heating. The measured trends for $E_D$ of the domain depinning are important for understanding the physics of charge density waves in quasi-two-dimensional crystals and for developing electronic devices based on this type of quantum materials. Condensed matter physics ; Charge density wave ; Conductance ; Electric field ; Charge density ; van der Waals force ; Phase (matter) ; Physics ; Charge (physics) ; Density wave theory ; Field (mathematics) ; Materials science ; Quantum mechanics ; Superconductivity Organic and Molecular Conductors Research ; Quantum and electron transport phenomena ; 2D Materials and Applications
Authors: André McDonald | Emine Bakan | Jan Čížek | Šárka Houdková | Heli Koivuluoto | Yuk-Chiu Lau | Hua Li | Filofteia-Laura Toma
Source: Journal of Thermal Spray Technology (article, 2023-03-01)
Field: Materials Science — Polymers and Plastics

Special Issue Featuring Papers from the International Thermal Spray Conference (ITSC) 2022 Thermal spraying ; Materials science ; Systems engineering ; Nuclear engineering ; Nanotechnology ; Engineering Flame retardant materials and properties
Authors: Woo Kang | Soo‐Hyun Cho | Dae-Hyun Lee | Kyung-Chul Kim
Source: Korean Journal of Agricultural Science (article, 2023-09-01)
Field: Chemistry — Analytical Chemistry

Localization of ripe tomato bunch using deep neural networks and class activation mapping In this study, we propose a ripe tomato bunch localization method based on convolutional neural networks, to be applied in robotic harvesting systems.Tomato images were obtained from a smart greenhouse at the Rural Development Administration (RDA).The sample images for training were extracted based on tomato maturity and resized to 128 128 pixels for use in the classification model.The model was constructed based on four-layer convolutional neural networks, and the classes were determined based on stage of maturity, using a Softmax classifier.The localization of the ripe tomato bunch region was indicated on a class activation map.The class activation map could show the approximate location of the tomato bunch but tends to present a local part or a large part of the ripe tomato bunch region, which could lead to poor performance.Therefore, we suggest a recursive method to improve the performance of the model.The classification results indicated that the accuracy, precision, recall, and F1-score were 0.98, 0.87, 0.98, and 0.92, respectively.The localization performance was 0.52, estimated by the Intersection over Union (IoU), and through input recursion, the IoU was improved by 13%.Based on the results, the proposed localization of the ripe tomato bunch area can be incorporated in robotic harvesting systems to establish the optimal harvesting paths. Class (philosophy) ; Deep neural networks ; Artificial neural network ; Cartography ; Artificial intelligence ; Geology ; Computer science ; Geography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Shunan Feng | Jing Shang | Tao Tan | Qingchun Wen | Qinglong Meng
Source: Research Square (preprint, 2023-07-03)
Field: Chemistry — Analytical Chemistry

Nondestructive quality assessment and maturity classification of loquat based on hyperspectral imaging Abstract Hyperspectral imaging technology was used to nondestructively predict and visualise the colour, firmness, and soluble solids content (SSC) of loquats and discriminate maturity. On comparison of the performance of different feature variables selection methods and the calibration models, the results indicated that the multiple linear regression (MLR) models combined with the competitive adaptive reweighting algorithm (CARS) yielded the best prediction performance for loquat quality. Particularly, CARS-MLR models with optimal prediction performance were obtained for the colour ( R 2 P = 0.96, RMSEP = 0.45, RPD = 5.38), firmness ( R 2 P = 0.87, RMSEP = 0.23, RPD = 2.81), and SSC ( R 2 P = 0.84, RMSEP = 0.51, RPD = 2.54). Subsequently, distribution maps of the colour, firmness, and SSC of loquats were obtained based on the optimal CARS-MLR models combined with pseudo-colour technology. Finally, on comparison of different classification models for loquat maturity, the partial least square discrimination analysis model demonstrated the best performance, with classification accuracies of 98.19% and 97.99% for calibration and prediction sets, respectively. This study demonstrated that the hyperspectral imaging technique is promising for loquat quality assessment and maturity classification. Hyperspectral imaging ; Calibration ; Mathematics ; Artificial intelligence ; Feature selection ; Pattern recognition (psychology) ; Partial least squares regression ; Feature (linguistics) ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Postharvest Quality and Shelf Life Management
Authors: Éric Bertin | F. Ladieu
Source: arXiv (Cornell University) (preprint, 2023-12-07)
Field: Materials Science — Materials Chemistry

Nonlinear dielectric response in glasses: restoring forces and avoided spin-glass criticality Experimental measurements of nonlinear dielectric response in glassformers like supercooled glycerol or propylene carbonate have been interpreted as providing evidence for a growing thermodynamic length scale when lowering temperature. A heuristic picture based on coherently flipping `superdipoles' with disordered internal structure has been argued to capture the essence of the experimentally reported behavior, pointing to the key role of effectively disordered interactions in structural glasses. We test these ideas by devising an explicit one-dimensional model of interacting spins incorporating both the spin-glass spirit of the superdipole argument, and the necessary long-time decorrelation of structural disorder, encoded here in a slow dynamics of the coupling constants. The frequency-dependent third-order response of the model qualitatively reproduces the typical humped shape reported in experiments. The temperature dependence of the maximum value is also qualitatively reproduced. In contrast, the humped shape of the third-order response is not reproduced by a simple kinetically constrained spin model with non-interacting spins. To rationalize these results, we propose a two-length-scale scenario by distinguishing between the characteristic length of dynamical heterogeneities and a coherence length that monitors the effect of interactions. We show that both length scales are identical in the kinetically constrained spin model, while they have significantly different dynamics in the model of interacting spins. Spins ; Physics ; Nonlinear system ; Length scale ; Supercooling ; Condensed matter physics ; Spin (aerodynamics) ; Frustration ; Statistical physics ; Spin glass ; Spin model ; Dielectric ; Quantum mechanics ; Thermodynamics Material Dynamics and Properties ; Spectroscopy and Quantum Chemical Studies ; Theoretical and Computational Physics
Authors: Florent Purnode | François Henrotte | Gilles Louppe | Christophe Geuzaine
Source:  (article, 2023-05-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Fast and Accurate Modelling of Laminated Cores in Electrical Machines using Homogenization and Neural Networks Eddy currents induced in the individual laminations of ferromagnetic laminated cores are usually disregarded in conventional electrical machine simulations, and magnetic losses are then only evaluated a posteriori, by means of Steinmetz-like formulas. This approach yields however seriously inaccurate computed fields and losses whenever the operating frequency increases, or in the presence of higher harmonics, which is an issue of growing importance in industrial R&D. In this contribution we introduce a significantly improved and effective approach based on homogenization and neural networks. The method can be easily implemented in standard finite element packages. Homogenization (climate) ; Eddy current ; Harmonics ; Finite element method ; Artificial neural network ; A priori and a posteriori ; Computer science ; Converters ; Electronic engineering ; Mechanical engineering ; Materials science ; Engineering ; Voltage ; Electrical engineering ; Structural engineering ; Artificial intelligence Magnetic Properties and Applications ; Advanced Mathematical Modeling in Engineering ; Electromagnetic Simulation and Numerical Methods