jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Steffen Seitz | Thomas Götz | Christopher Lindenberg | Ronald Tetzlaff | Stephan Schlegel
Source: arXiv (Cornell University) (preprint, 2023-07-17)
Field: Materials Science — Materials Chemistry

Generalizable Classification of UHF Partial Discharge Signals in Gas-Insulated HVDC Systems Using Neural Networks Undetected partial discharges (PDs) are a safety critical issue in high voltage (HV) gas insulated systems (GIS). While the diagnosis of PDs under AC voltage is well-established, the analysis of PDs under DC voltage remains an active research field. A key focus of these investigations is the classification of different PD sources to enable subsequent sophisticated analysis. In this paper, we propose and analyze a neural network-based approach for classifying PD signals caused by metallic protrusions and conductive particles on the insulator of HVDC GIS, without relying on pulse sequence analysis features. In contrast to previous approaches, our proposed model can discriminate the studied PD signals obtained at negative and positive potentials, while also generalizing to unseen operating voltage multiples. Additionally, we compare the performance of time- and frequency-domain input signals and explore the impact of different normalization schemes to mitigate the influence of free-space path loss between the sensor and defect location. Partial discharge ; Normalization (sociology) ; Voltage ; Electrical conductor ; Computer science ; Insulator (electricity) ; Electronic engineering ; Ultra high frequency ; Frequency domain ; Artificial neural network ; Electrical engineering ; Engineering ; Artificial intelligence ; Telecommunications High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Power Line Communications and Noise
Authors: Siamak Mirfendereski | Jae Sung Park
Source: arXiv (Cornell University) (preprint, 2023-11-15)
Field: Chemistry — Physical and Theoretical Chemistry

Rheology of dense suspensions of ideally conductive particles in an electric field The rheological behaviour of dense suspensions of ideally conductive particles in the presence of both electric field and shear flow is studied using large-scale numerical simulations. Under the action of an electric field, these particles are known to undergo dipolophoresis, which is the combination of two nonlinear electrokinetic phenomena -- induced-charge electrophoresis and dielectrophoresis. For ideally conductive particles, induced-charge electrophoresis is predominant over dielectrophoresis, resulting in transient pairing dynamics. The shear viscosity and first and second normal stress differences $N_1$ and $N_2$ of such suspensions are examined over a range of volume fractions $15\% \leqslant ϕ\leqslant 50\%$ as a function of Mason number $Mn$, which measures the relative importance of viscous shear stress over electrokinetic-driven stress. For $Mn &lt; 1$ or low shear rates, the dipolophoresis is shown to dominate the dynamics, resulting in a relatively low-viscosity state. The positive $N_1$ and negative $N_2$ are observed at $ϕ&lt; 30\%$, which is similar to Brownian suspensions, while their signs are reversed at $ϕ\ge 30\%$. For $Mn \ge 1$, the shear thickening starts to arise at $ϕ\ge 30\%$, and an almost five-fold increase in viscosity occurs at $ϕ= 50\%$. Both $N_1$ and $N_2$ are negative for $Mn \gg 1$ at all volume fractions considered. We illuminate the transition in rheological behaviours from dipolophoresis to shear dominance around $Mn = 1$ in connection to suspension microstructure and dynamics. Lastly, our findings reveal the potential use of nonlinear electrokinetics as a means of active rheology control for such suspensions. Electrokinetic phenomena ; Rheology ; Electric field ; Dielectrophoresis ; Viscosity ; Dilatant ; Materials science ; Shear stress ; Electrophoresis ; Chemistry ; Analytical Chemistry (journal) ; Composite material ; Nanotechnology ; Physics ; Chromatography Electrostatics and Colloid Interactions ; Material Dynamics and Properties ; Rheology and Fluid Dynamics Studies
Authors: Makoto Fukumoto | Ryunosuke Akai | Yume Yoshida | Shin-nosuke Sakuma | Hayato Ono | Rintaro Mori | Masahito Sano
Source: Scientific Reports (article, 2023-03-20)
Field: Materials Science — Materials Chemistry

Synchronized oscillations of carbon nanotubes dispersed in solution Although synchronized oscillations are found in a variety of systems and living organisms in nature, there has been no report on technologically important materials. We have observed by a fluorescence microscope that a large number of carbon nanotubes (CNTs) dispersed in an aqueous mixture of the surfactant and dye execute synchronized oscillations spontaneously. The movement was quantified to give a power spectrum, revealing a single, sharp synchronization peak at 20 Hz. It was found not to be affected nor created by external vibrations. The surfactant concentration dependence demonstrates that the Kuramoto model is applicable to describe the CNT synchronization. It is always associated with the power-law noise, indicating the presence of complex heterogeneous networks. These results suggest a highly cooperative form of the sparse CNT network connected with variable linkages. Carbon nanotube ; Nanotechnology ; Materials science Carbon Nanotubes in Composites ; Nonlinear Dynamics and Pattern Formation ; Mechanical and Optical Resonators
Source: NanoWorld Journal (article, 2023-12-01)
Field: Materials Science — Materials Chemistry

Nanoscale Text Classification with Bi-LSTM: Enhancing Precision Shaik Mohammed Basha, Anusha Balemla, Saniya Anjum and A. Ramesh Vast volumes of data are produced from numerous sources, including websites and social media. It is necessary to extract significant information from text data, categorize it, and forecast end-user behavior or emotions. Nanoscopic scale ; Computer science ; Natural language processing ; Artificial intelligence ; Nanotechnology ; Materials science Machine Learning in Materials Science ; Machine Learning in Bioinformatics
Authors: Qing-Yue Li | Pin‐Tian Lyu | Bin Kang | Hong‐Yuan Chen | Jing‐Juan Xu
Source: arXiv (Cornell University) (preprint, 2023-12-27)
Field: Chemistry — Electrochemistry

Label-free optical imaging of ion channel activity on living cells Deciphering ion channel activity and signaling interactions within cells is one of the key tasks of neuroscience. Currently, measuring this electrophysiological activity is done using patch-clamp1-4 or voltage-sensitive imaging5-8. Unfortunately, these techniques are unable to balance between single-channel sensitivity and highthroughput detection. Here we introduce a label-free electrochemical-modulated interferometric scattering microscope (EM-iSCAT) to measure ion channel activity on living cells at both whole-cell and single-channel levels. We visualize the cellular responses dynamics to osmotic stimulation, and record open-close trajectories of single N-methyl-D-aspartate receptors channels with a frame rate of 1.5 kHz. Furthermore, we localize and distinguish different kinds of ion channels (Na+, K+, Ca2+) on cell membrane and monitor spatio-temporal heterogeneous responses between different cells in a network. The high-throughput and single-channel sensitive nature of EMiSCAT microscopy allows monitoring simultaneously the activity of individual channels, their localization, and clustering in the cellular community. Our imaging concept opens the possibility to study any kind of ion channels, and more broadly, cell communication mediated by ion channels. Ion channel ; Electrophysiology ; Channel (broadcasting) ; Biophysics ; Membrane potential ; Chemistry ; Ligand-gated ion channel ; Nanotechnology ; Neuroscience ; Computer science ; Materials science ; Biology ; Receptor ; Biochemistry ; Telecommunications Electrochemical Analysis and Applications ; Analytical Chemistry and Sensors ; Force Microscopy Techniques and Applications
Authors: Asep Bayu Dani Nandiyanto | Irine Sofianty | Adani Gina Puspita Sari | Rofi Fadilah Madani | Fitri Febrianti | Risti Ragadhita | Teguh Kurniawan | Rizky Jumansyah | E S Soegoto | Senny Luckyardi | Muhammad Aziz
Source: Mathematical Modelling and Engineering Problems (article, 2023-04-28)
Field: Materials Science — Materials Chemistry

Computational Calculation on the Shell and Tube-Type Heat Exchanger for Lanthanum Oxide (La2O3) Nanoparticle Production Process for Energy-Related Material Application This paper introduced a design of a heat exchanger to get an optimum heat transfer enhancement technique that can be used for the production of lanthanum oxide (La2O3).The shell and tube type was selected since this type is one of the effective types for making excellent heat transfer, which was then compared to the Tubular Exchanger Manufacturers Association (TEMA) standard to obtain the dimensional specifications of the heat exchanger device.Several parameters were calculated to evaluate the performance of the designed heat exchanger.Numerical calculation obtained from the heat exchanger containing 138 tubes can be used to maintain the temperature in the reactor (prospective temperature can change from 40 to 60℃ with rapid heating) using heating liquid (controlling by transferring heat from 100 to 70℃) with the effective value of 96%.This study can be used as a reference for supporting information in the current issue of the need for the large production of La2O3 particles. Lanthanum ; Lanthanum oxide ; Shell (structure) ; Tube (container) ; Materials science ; Nanoparticle ; Shell and tube heat exchanger ; Heat exchanger ; Process (computing) ; Production (economics) ; Oxide ; Chemical engineering ; Nuclear engineering ; Process engineering ; Composite material ; Nanotechnology ; Mechanical engineering ; Metallurgy ; Chemistry ; Inorganic chemistry ; Computer science ; Engineering Catalytic Processes in Materials Science ; Injection Molding Process and Properties ; Additive Manufacturing and 3D Printing Technologies
Authors: Mattia Perrone | Riccardo Capelli | Charly Empereur‐mot | Ali Hassanali | Giovanni M. Pavan
Source: ChemRxiv (preprint, 2023-07-26)
Field: Materials Science — Materials Chemistry

Lessons learned from multi-objective automatic optimizations of classical three-site rigid water models using microscopic and macroscopic target experimental observables The development of accurate water models is of primary importance for molecular simulations. Despite their intrinsic approximations, three-site rigid water models are still ubiquitously used to simulate a variety of molecular systems. Automatic optimization approaches have been recently used to iteratively optimize three-site water models to fit macroscopic (average) thermodynamic properties, providing “state-of-the-art” three-site models that still present some deviations from the liquid water properties. Here we show results obtained by automatically optimizing three-site rigid water models to fit a combination of microscopic and macroscopic experimental observables. We use Swarm-CG, a multi-objective particle-swarm-optimization algorithm, for training the models to reproduce the experimental radial distribution functions of liquid water at various temperatures (rich in microscopic-level information on, e.g., the local orientation and interactions of the water molecules). We systematically analyze the agreement of these models with experimental observables and the effect of adding macroscopic information into the training-set. Our results demonstrate how adding microscopic-rich information in the training of water models allows achieving state-of-art accuracy in an efficient way. Limitations in the approach and in the approximated description of water in these three-site models are also discussed, providing a demonstrative case useful for the optimization of approximated molecular models in general. Observable ; Statistical physics ; Computer science ; Water model ; Particle swarm optimization ; Biological system ; Set (abstract data type) ; Orientation (vector space) ; Algorithm ; Mathematical optimization ; Physics ; Molecular dynamics ; Mathematics ; Geometry Machine Learning in Materials Science ; Protein Structure and Dynamics ; Block Copolymer Self-Assembly
Authors: Seunghun Lee | Jaewon Chu | Sihyeon Kim | Juyeon Ko | Hyunwoo J. Kim
Source: arXiv (Cornell University) (preprint, 2023-10-31)
Field: Materials Science — Materials Chemistry

Advancing Bayesian Optimization via Learning Correlated Latent Space Bayesian optimization is a powerful method for optimizing black-box functions with limited function evaluations. Recent works have shown that optimization in a latent space through deep generative models such as variational autoencoders leads to effective and efficient Bayesian optimization for structured or discrete data. However, as the optimization does not take place in the input space, it leads to an inherent gap that results in potentially suboptimal solutions. To alleviate the discrepancy, we propose Correlated latent space Bayesian Optimization (CoBO), which focuses on learning correlated latent spaces characterized by a strong correlation between the distances in the latent space and the distances within the objective function. Specifically, our method introduces Lipschitz regularization, loss weighting, and trust region recoordination to minimize the inherent gap around the promising areas. We demonstrate the effectiveness of our approach on several optimization tasks in discrete data, such as molecule design and arithmetic expression fitting, and achieve high performance within a small budget. Bayesian optimization ; Regularization (linguistics) ; Computer science ; Optimization problem ; Bayesian probability ; Weighting ; Space (punctuation) ; Artificial intelligence ; Mathematical optimization ; Generative model ; Machine learning ; Algorithm ; Mathematics ; Generative grammar Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Machine Learning and Data Classification
Authors: Elizma van Wyngaard | Erna Blancquaert | H.H. Nieuwoudt | José Luis Aleixandre-Tudó
Source: Biosystems Engineering (article, 2023-07-25)
Field: Chemistry — Analytical Chemistry

A novel approach to upgrade infrared spectroscopy calibrations for nutritional contents in fresh grapevine organs Residual ; Calibration ; Mean squared error ; Root mean square ; Reference data ; Coefficient of determination ; Predictive modelling ; Mathematics ; Environmental science ; Statistics ; Chemistry ; Computer science ; Data mining ; Algorithm ; Physics Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Martina Varga | Tanja Žuna Pfeiffer | Lidija Begović | Selma Mlinarić | Janja Horvatić | Tihana Miloloža | Ivna Štolfa Čamagajevac
Source: Plants (article, 2023-03-19)
Field: Materials Science — Materials Chemistry

Physiological Response of Nutrient-Stressed Lemna gibba to Pulse Colloidal Silver Treatment Wastewater is a source of many environmental pollutants and potentially high concentrations of essential plant nutrients. Site-specific nutrient levels may influence the response of exposed plants to a chemical stressor. In the present study, we focused on the responses of model aquatic macrophyte swollen duckweed (<i>Lemna gibba</i> L.) to a short pulse exposure and a commercially available colloidal silver product as a potential environmental chemical stressor, combined with two levels of total nitrogen and phosphorus nutrition. Treatment with the commercially available colloidal silver product caused oxidative stress in <i>L. gibba</i> plants under both high and low nutrient levels. Plants grown and treated under high nutrient levels showed lower levels of lipid peroxidation and hydrogen peroxide accumulation, as well as higher levels of photosynthetic pigment content in comparison to treated plants under low nutrient levels. Higher free radical scavenging activity for plants treated with silver in combination with high nutrient levels resulted in better overall protection from silver-induced oxidative stress. The results showed that external nutrient levels significantly affected the <i>L. gibba</i> plant's response to the colloidal silver presence in the environment and that nutrient levels should be considered in the assessment of potential environmental impact for contaminants. Lemna gibba ; Nutrient ; Biology ; Ecology ; Aquatic plant Nanoparticles: synthesis and applications ; Constructed Wetlands for Wastewater Treatment ; Heavy metals in environment
Authors: Addison Marie Arave
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2023-10-25)
Field: Materials Science — Materials Chemistry

Nuclear Science &amp; Technology April 2023 Highlights Highlight-Improving accuracy of thermal-hydraulics models of the reactor core by mapping high-fidelity models into lower-fidelity models. Future goals are to:-Build an integral modeling and simulation tool for improving the design and safety of MSRs.-Create a digital twin for MSRs. Environmental science Graphite, nuclear technology, radiation studies
Authors: Jiawei Huang | Changming Ke | Zhuang Qian | Shi Liu
Source: arXiv (Cornell University) (preprint, 2023-11-14)
Field: Materials Science — Materials Chemistry

Competing charge transfer and screening effects in two-dimensional ferroelectric capacitors Two-dimensional (2D) ferroelectrics offer the potential for ultrathin flexible nanoelectronics, typically utilizing a metal-ferroelectric-metal sandwich structure as the functional unit. Electrodes can either contribute free carriers to screen the depolarization field, enhancing nanoscale ferroelectricity, or they can induce charge doping, disrupting the long-range crystalline order. Here, we explore the dual roles of electrodes in 2D ferroelectric capacitors, supported by extensive first-principles calculations covering a range of electrode work functions. Our results reveal volcano-type relationships between ferroelectric-electrode binding affinity and work function, which are further unified by a quadratic scaling between the binding energy and the transferred interfacial charge. At the monolayer limit, the charge transfer dictates the ferroelectric stability and switching properties. This is a general characteristic confirmed in various 2D ferroelectrics including $α$-In$_2$Se$_3$, CuInP$_2$S$_6$, and SnTe. As the ferroelectric layer's thickness increases, the stability of the capacitor evolves from a charge transfer-dominated to a screening-dominated state. The delicate interplay between these two effects will have important implications for the applications of 2D ferroelectric capacitors. Ferroelectricity ; Materials science ; Capacitor ; Ferroelectric capacitor ; Optoelectronics ; Condensed matter physics ; Electrode ; Charge (physics) ; Nanotechnology ; Dielectric ; Voltage ; Electrical engineering ; Chemistry ; Physics Ferroelectric and Piezoelectric Materials ; Ferroelectric and Negative Capacitance Devices ; 2D Materials and Applications
Authors: Ryo Murakami | Yoshitaka Matsushita | Kenji Nagata | Hayaru Shouno | Hideki Yoshikawa
Source: arXiv (Cornell University) (preprint, 2023-09-26)
Field: Materials Science — Materials Chemistry

Bayesian inference to identify crystalline structures for XRD Crystalline phase structure is essential for understanding the performance and properties of a material. Therefore, this study identified and quantified the crystalline phase structure of a sample based on the diffraction pattern observed when the crystalline sample was irradiated with electromagnetic waves such as X-rays. Conventional analysis necessitates experienced and knowledgeable researchers to shorten the list from many candidate crystalline phase structures. However, the Conventional diffraction pattern analysis is highly analyst-dependent and not objective. Additionally, there is no established method for discussing the confidence intervals of the analysis results. Thus, this study aimed to establish a method for automatically inferring crystalline phase structures from diffraction patterns using Bayesian inference. Our method successfully identified true crystalline phase structures with a high probability from 50 candidate crystalline phase structures. Further, the mixing ratios of selected crystalline phase structures were estimated with a high degree of accuracy. This study provided reasonable results for well-crystallized samples that clearly identified the crystalline phase structures. Diffraction ; Phase (matter) ; Materials science ; Sample (material) ; Inference ; Bayesian probability ; Crystal structure ; X-ray crystallography ; Bayesian inference ; Crystallography ; Computer science ; Artificial intelligence ; Optics ; Physics ; Chemistry ; Thermodynamics X-ray Diffraction in Crystallography ; X-ray Spectroscopy and Fluorescence Analysis ; Nuclear Physics and Applications
Authors: Irina Piyanzina | Alexander Evseev | Kirill V. Evseev | Р. Ф. Мамин | Oleg V. Nedopekin | D. A. Tayurskiı̆ | V. V. Kabanov
Source: Materials (article, 2023-10-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advantages of Ferroelectrics as a Component of Heterostructures for Electronic Purposes: A DFT Insight The main advantage of using ferroelectric materials as a component of complex heterostructures is the ability to tune various properties of the whole system by means of an external electric field. In particular, the electric field may change the polarization direction within the ferroelectric material and consequently affect the structural properties, which in turn affects the electronic and magnetic properties of the neighboring material. In addition, ferroelectrics allow the electrostriction phenomenon to proceed, which is promising and can be used to affect the magnetic states of the interface state in the heterostructure through a magnetic component. The interfacial phenomena are of great interest, as they provide extended functionality useful for next-generation electronic devices. Following the idea of utilizing ferroelectrics in heterostructural components in the present works, we consider 2DEG, the Rashba effect, the effect of magnetoelectric coupling, and magnetostriction in order to emphasize the advantages of such heterostructures as components of devices. For this purpose, model systems of LaMnO3/BaTiO3, La2CuO4/BaTiO3, Bi/BaTiO3, and Bi/PbTiO3, Fe/BaTiO3 heterostructures are investigated using density functional theory calculations. Heterojunction ; Ferroelectricity ; Electrostriction ; Materials science ; Component (thermodynamics) ; Electric field ; Condensed matter physics ; Magnetostriction ; Magnetic field ; Dielectric ; Nanotechnology ; Optoelectronics ; Piezoelectricity ; Physics Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials ; Electronic and Structural Properties of Oxides