jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qidong Xu | Meiting Guo | Lingchao Xia | Zheng Li | Qijiao He | Dongqi Zhao | Keqing Zheng | Meng Ni
Source: Transactions of Tianjin University (article, 2022-08-10)
Field: Materials Science — Materials Chemistry

Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol Abstract Thermal management in solid oxide fuel cells (SOFC) is a critical issue due to non-uniform electrochemical reactions and convective flows within the cells. Therefore, a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled SOFC. Results show that unlike the low-temperature condition of 873 K, where the peak temperature gradient occurs at the cell center, it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current density. Despite the large heat convection capacity, excessive air could not effectively eliminate the harmful temperature gradient caused by the large current density. Thus, optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral state. Interestingly, the maximum axial temperature gradient could be reduced by about 18% at 973 K and 20% at 1073 K when the air with a 5 K higher temperature is supplied. Additionally, despite the higher electrochemical performance observed, the cell with a counter-flow arrangement featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal durability. Overall, this study could provide insightful thermal information for the operating condition selection, structure design, and stability assessment of realistic SOFCs combined with their internal reforming process. Temperature gradient ; Materials science ; Convection ; Current density ; Solid oxide fuel cell ; Current (fluid) ; Thermal ; Oxide ; Durability ; Thermodynamics ; Ceramic ; Methanol ; Operating temperature ; Nuclear engineering ; Chemical engineering ; Chemistry ; Composite material ; Meteorology ; Electrode ; Engineering Advancements in Solid Oxide Fuel Cells ; Electrocatalysts for Energy Conversion ; Fuel Cells and Related Materials
Authors: Olivia Pfeiffer | Haihao Liu | Luca Montanelli | Marat I. Latypov | Fatih G. Sen | V. Hegadekatte | Elsa Olivetti | Eric R. Homer
Source: Scientific Data (article, 2022-03-30)
Field: Materials Science — Materials Chemistry

Aluminum alloy compositions and properties extracted from a corpus of scientific manuscripts and US patents Researchers continue to explore and develop aluminum alloys with new compositions and improved performance characteristics. An understanding of the current design space can help accelerate the discovery of new alloys. We present two datasets: 1) chemical composition, and 2) mechanical properties for predominantly wrought aluminum alloys. The first dataset contains 14,884 entries on aluminum alloy compositions extracted from academic literature and US patents using text processing techniques, including 550 wrought aluminum alloys which are already registered with the Aluminum Association. The second dataset contains 1,278 entries on mechanical properties for aluminum alloys, where each entry is associated with a particular wrought series designation, extracted from tables in academic literature. Aluminium ; Alloy ; Materials science ; Space (punctuation) ; Metallurgy ; Computer science ; Information retrieval Machine Learning in Materials Science ; Microstructure and Mechanical Properties of Steels ; Metallurgy and Cultural Artifacts
Authors: K. S. Cujia | Konstantin Herb | Jonathan Zopes | John M. Abendroth | Christian L. Degen
Source: Nature Communications (article, 2022-03-10)
Field: Materials Science — Materials Chemistry

Parallel detection and spatial mapping of large nuclear spin clusters Nuclear magnetic resonance imaging (MRI) at the atomic scale offers exciting prospects for determining the structure and function of individual molecules and proteins. Quantum defects in diamond have recently emerged as a promising platform towards reaching this goal, and allowed for the detection and localization of single nuclear spins under ambient conditions. Here, we present an efficient strategy for extending imaging to large nuclear spin clusters, fulfilling an important requirement towards a single-molecule MRI technique. Our method combines the concepts of weak quantum measurements, phase encoding and simulated annealing to detect three-dimensional positions from many nuclei in parallel. Detection is spatially selective, allowing us to probe nuclei at a chosen target radius while avoiding interference from strongly-coupled proximal nuclei. We demonstrate our strategy by imaging clusters containing more than 20 carbon-13 nuclear spins within a radius of 2.4 nm from single, near-surface nitrogen-vacancy centers at room temperature. The radius extrapolates to 5-6 nm for <sup>1</sup>H. Beside taking an important step in nanoscale MRI, our experiment also provides an efficient tool for the characterization of large nuclear spin registers in the context of quantum simulators and quantum network nodes. Spins ; Quantum ; Physics ; Spin (aerodynamics) ; RADIUS ; Quantum sensor ; Diamond ; Context (archaeology) ; Nuclear magnetic resonance ; Materials science ; Quantum computer ; Quantum network ; Computer science ; Condensed matter physics ; Quantum mechanics Diamond and Carbon-based Materials Research ; Ion-surface interactions and analysis ; High-pressure geophysics and materials
Authors: Yongtao Liu | Kyle P. Kelley | Rama K. Vasudevan | Wanlin Zhu | John Hayden | Jon‐Paul Maria | Hiroshi Funakubo | Maxim Ziatdinov | Susan Trolier‐McKinstry | Sergei V. Kalinin
Source: Small (article, 2022-10-17)
Field: Materials Science — Materials Chemistry

Automated Experiments of Local Non‐Linear Behavior in Ferroelectric Materials An automated experiment in multimodal imaging to probe structural, chemical, and functional behaviors in complex materials and elucidate the dominant physical mechanisms that control device function is developed and implemented. Here, the emergence of non-linear electromechanical responses in piezoresponse force microscopy (PFM) is explored. Non-linear responses in PFM can originate from multiple mechanisms, including intrinsic material responses often controlled by domain structure, surface topography that affects the mechanical phenomena at the tip-surface junction, and the presence of surface contaminants. Using an automated experiment to probe the origins of non-linear behavior in ferroelectric lead titanate (PTO) and ferroelectric Al<sub>0.93</sub> B<sub>0.07</sub> N films, it is found that PTO shows asymmetric nonlinear behavior across a/c domain walls and a broadened high nonlinear response region around c/c domain walls. In contrast, for Al<sub>0.93</sub> B<sub>0.07</sub> N, well-poled regions show high linear piezoelectric responses, when paired with low non-linear responses regions that are multidomain show low linear responses and high nonlinear responses. It is shown that formulating dissimilar exploration strategies in deep kernel learning as alternative hypotheses allows for establishing the preponderant physical mechanisms behind the non-linear behaviors, suggesting that automated experiments can potentially discern between competing physical mechanisms. This technique can also be extended to electron, probe, and chemical imaging. Piezoresponse force microscopy ; Ferroelectricity ; Nonlinear system ; Materials science ; Piezoelectricity ; Domain (mathematical analysis) ; Surface (topology) ; Nanotechnology ; Biological system ; Physics ; Optoelectronics ; Geometry ; Composite material ; Mathematics ; Mathematical analysis ; Dielectric Ferroelectric and Piezoelectric Materials ; Force Microscopy Techniques and Applications ; Acoustic Wave Resonator Technologies
Authors: Navid Rasekh | Jun Wang | Xibo Yuan
Source: IEEE Open Journal of Power Electronics (article, 2022-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Artificial Neural Network Aided Loss Maps for Inductors and Transformers The non-linear property of magnetics poses challenges for their loss modelling in power electronics due to lacking full physical models. As a practical approach for their loss estimation, the manufacturers can pre-measure the losses in standalone rigs and distribute the "loss maps" as interpolated look-up tables/curves for the end users. However, with more factors discovered that impact the losses, e.g., DC bias and load conditions, the dimensions of the loss maps cannot be solved by conventional surface/curve fitting methods. This paper addresses this problem by applying the Artificial Neural Network (ANN). For both inductors and transformers, Neural Network-aided loss maps (NNALMs) are designed and evaluated with comparisons against conventional loss maps to reveal the limitations of the latter caused by physically intercoupled input variables. The NNALMs not only show superior accuracy throughout the whole datasets, but also enable the loss maps to expand the dimensions to account for more factors (e.g., load conditions in transformers) and generate multiple outputs (e.g., both the winding loss and core loss). The ANN-aided loss maps can be distributed as digitized datasheets of standardized magnetics, enabling rapid, accurate and user-friendly loss estimations for power electronics engineers. Transformer ; Artificial neural network ; Inductor ; Power loss ; Computer science ; Power electronics ; Electronic engineering ; Electrical engineering ; Engineering ; Artificial intelligence ; Voltage Magnetic Properties and Applications ; Silicon Carbide Semiconductor Technologies ; Power Transformer Diagnostics and Insulation
Authors: C. Colliex
Source: The European Physical Journal Applied Physics (article, 2022-01-01)
Field: Materials Science — Surfaces, Coatings and Films

From early to present and future achievements of EELS in the TEM This paper reviews the implementation of Electron Energy Loss Spectroscopy (EELS) in a Transmission Electron Microscope (TEM), as an essential tool for advanced analytical studies, exhibiting a unique level of performance in terms of spatial resolution down to the interatomic distances for imaging and sensitivity down to the single atom for elemental identification. In terms of spectral resolution, it offers access with a resolution as good as a few meV, to a very broad spectral domain extending from tens of meV (in the IR) up to a few keV (in the X-ray). This new generation of instrument (EELS+(S)TEM) is now routinely used to investigate the structural, spectral, electronic and chemical properties of a wide range of materials and to broaden spectacularly the field of novel information which it provides. A first part of the paper describes the major progress in advanced instrumentation brought by the novel pieces of equipment (spectrometers, monochromators, aberration correctors and detectors) together with the newly elaborated tools for the acquisition and processing of huge data collections. The second part is devoted to the description of the information contained in a global EELS spectrum: (i) from the core-loss domain implying excitations from inner-shell atomic electrons and its application in elemental, chemical and electronic mapping; (ii) from the low-energy domain exhibiting individual or collective excitations of the valence and conduction electron gas, with its most recent developments in band gap mapping and nanoplasmonics; (iii) in the ultra-low energy domain, which is now in its infancy, the surface collective electron excitations, molecular bonds and the vibrations of phonons at surfaces and in the bulk of nanostructures. The third part is devoted to the exploration of unconventional domains of applications, which in many cases associate the EELS acquisition with the generation and the capture of other signals in various environments, in situ operation (temperature, pressure...), absorption or generation of photons (cathodoluminescence, X-ray emission), acquisition and handling of multidimension data (space, energy, momentum, time). In conclusion, EELS fifty years after its first recognition as a useful actor in the development and promotion of the analytical microscopy, has nowadays become an essential tool for the acquisition of many physical parameters with ultimate resolution, thus opening new routes in nanophysics to be explored. Electron energy loss spectroscopy ; Spectrometer ; Resolution (logic) ; Spectral resolution ; Electron ; Materials science ; Physics ; Optics ; Nanotechnology ; Spectral line ; Transmission electron microscopy ; Computer science ; Nuclear physics Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Ion-surface interactions and analysis
Authors: Benhour Amirian | H. Jafarzadeh | Bilen Emek Abali | Alessandro Reali | James D. Hogan
Source: Computational Mechanics (article, 2022-07-27)
Field: Materials Science — Biomaterials

Phase-field approach to evolution and interaction of twins in single crystal magnesium Crack initiation and propagation as well as abrupt occurrence of twinning are challenging fracture problems where the transient phase-field approach is proven to be useful. Early-stage twinning growth and interactions are in focus herein for a magnesium single crystal at the nanometer length-scale. We demonstrate a basic methodology in order to determine the mobility parameter that steers the kinetics of phase-field propagation. The concept is to use already existing molecular dynamics simulations and analytical solutions in order to set the mobility parameter correctly. In this way, we exercise the model for gaining new insights into growth of twin morphologies, temporally-evolving spatial distribution of the shear stress field in the vicinity of the nanotwin, multi-twin, and twin-defect interactions. Overall, this research addresses gaps in our fundamental understanding of twin growth, while providing motivation for future discoveries in twin evolution and their effect on next-generation material performance and design. Magnesium ; Phase (matter) ; Field (mathematics) ; Crystal twinning ; Materials science ; Physics ; Mathematics ; Metallurgy ; Microstructure ; Quantum mechanics ; Pure mathematics Magnesium Alloys: Properties and Applications ; Solidification and crystal growth phenomena ; Intermetallics and Advanced Alloy Properties
Authors: Luis Suárez | Zaida Ortega | Francisco Romero | Rubén Paz | María Dolores Marrero-Alemán
Source: Journal of Polymers and the Environment (article, 2022-09-01)
Field: Materials Science — Polymers and Plastics

Influence of Giant Reed Fibers on Mechanical, Thermal, and Disintegration Behavior of Rotomolded PLA and PE Composites Abstract This paper assesses the modifications in the properties of rotomolded polyethylene (PE) and polylactic acid (PLA) composites obtained with 5 and 10% giant reed fibers, mainly focusing on the alterations due to a bio-disintegration process. Thermal properties (melting temperature and crystallinity degree), morphology (via optical and scanning electron microscopy), and chemical changes (by Fourier Transformed Infrared spectroscopy) were studied. Composites with untreated and NaOH-treated fibers were obtained, finding that this treatment does not improve the mechanical performance of composites due to increased porosity. The introduction of natural fibers into a PE matrix does not significantly modify the thermal and bio-disintegration properties of the rotomolded material. Regarding mechanical properties, PE-composites show increased tensile modulus and reduced impact and tensile strength than the matrix. On the other hand, PLA composites show lower impact and flexural strength than neat PLA, remaining the rest of the mechanical properties unchanged regardless of the fibers' addition. The incorporation of Arundo fibers modifies to a great extent the thermal and degradation behavior of the PLA matrix. Materials science ; Composite material ; Ultimate tensile strength ; Crystallinity ; Polylactic acid ; Flexural strength ; Scanning electron microscope ; Izod impact strength test ; Fourier transform infrared spectroscopy ; Polyethylene ; Porosity ; Flexural modulus ; Polymer ; Chemical engineering Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution
Authors: Rania Jradi | Christophe Marvillet | Mohamed Razak Jeday
Source: Scientific Reports (article, 2022-11-28)
Field: Materials Science — Biomaterials

Analysis and estimation of cross-flow heat exchanger fouling in phosphoric acid concentration plant using response surface methodology (RSM) and artificial neural network (ANN) The production of phosphoric acid by dehydrated process leads to the precipitation of unwanted insoluble salts promoting thus the crystallization fouling build-up on heat transfer surfaces of the exchangers. During the acid concentration operation, the presence of fouling in heat exchangers results in reducing the performance of this equipment, in terms of heat transfer, while increasing energy losses and damaging the apparatus. To mitigate these adverse effects of fouling, it is necessary to forecast the thermal resistance of fouling to schedule and perform exchanger cleaning. In this context, artificial neural network and response surface methodology were used to estimate thermal resistance of fouling in a cross-flow heat exchanger by using the operating data of the concentration loop. The absolute average relative deviations, mean squared errors, root mean squared errors and correlation coefficients were used as indicators error between the experimental and estimated values for both methods. The best fitted model derived from response surface methodology method was second order polynomial while the best architecture topology, for the artificial neural network method, consists of three layers: input layer with six input variables, hidden layer with six hidden neurons and an output layer with single output variable. The interactive influences of operating parameters which have significant effects on the fouling resistance were illustrated in detail. The value of correlation coefficient for the output parameter from the response surface methodology is 0.9976, indicating that the response surface methodology as an assessment methodology in estimating fouling resistance is more feasible compared with the artificial neural network approach. Fouling ; Response surface methodology ; Heat exchanger ; Artificial neural network ; Mean squared error ; Correlation coefficient ; Context (archaeology) ; Heat transfer coefficient ; Process engineering ; Biological system ; Mathematics ; Heat transfer ; Materials science ; Environmental science ; Computer science ; Machine learning ; Engineering ; Chemistry ; Thermodynamics ; Mechanical engineering ; Statistics Calcium Carbonate Crystallization and Inhibition ; Freezing and Crystallization Processes ; Magnetic and Electromagnetic Effects
Authors: Monica T. Dayao | Maigan A. Brusko | Clive Wasserfall | Ziv Bar‐Joseph
Source: Nature Communications (article, 2022-04-14)
Field: Chemistry — Spectroscopy

Membrane marker selection for segmenting single cell spatial proteomics data The ability to profile spatial proteomics at the single cell level enables the study of cell types, their spatial distribution, and interactions in several tissues and conditions. Current methods for cell segmentation in such studies rely on known membrane or cell boundary markers. However, for many tissues, an optimal set of markers is not known, and even within a tissue, different cell types may express different markers. Here we present RAMCES, a method that uses a convolutional neural network to learn the optimal markers for a new sample and outputs a weighted combination of the selected markers for segmentation. Testing RAMCES on several existing datasets indicates that it correctly identifies cell boundary markers, improving on methods that rely on a single marker or those that extend nuclei segmentations. Application to new spatial proteomics data demonstrates its usefulness for accurately assigning cell types based on the proteins expressed in segmented cells. Convolutional neural network ; Proteomics ; Computer science ; Segmentation ; Pattern recognition (psychology) ; Computational biology ; Artificial intelligence ; Cell type ; Cell ; Bioinformatics ; Biology ; Genetics ; Gene Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Cell Image Analysis Techniques
Authors: Loukas Petrou | Kypros M. Kossifos | Marco A. Antoniades | Julius Georgiou
Source: Scientific Reports (article, 2022-04-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The first family of application-specific integrated circuits for programmable and reconfigurable metasurfaces Reconfigurable metasurfaces are man-made surfaces, which consist of sub-wavelength periodic elements-meta-atoms-that can be reconfigured to manipulate incoming electromagnetic waves. However, reconfigurable metasurfaces developed to-date, have limitations in terms of loading impedance range, reconfiguration delay and power consumption. Also, these systems are costly and they require bulky electronics and complex control circuits, which makes them unattractive for commercial use. Here, we report the first family of CMOS application-specific integrated circuits that enable microsecond and microwatt reconfiguration of complex impedances at microwave frequencies. Our approach utilizes asynchronous digital control circuitry with chip-to-chip communication capabilities, allowing simple and fast reconfiguration via digital devices and user-friendly software. Our solution is low-cost and can cover arbitrary board-to-board metasurfaces, with different sizes and shapes. Control reconfiguration ; Electronic circuit ; Computer science ; Field-programmable gate array ; Asynchronous communication ; CMOS ; Chip ; Microwave ; Electronics ; Integrated circuit ; Digital electronics ; Printed circuit board ; High impedance ; Change control board ; Electronic engineering ; Embedded system ; Electrical impedance ; Electrical engineering ; Telecommunications ; Engineering Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis