jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sergio González-Serrud | Nacarí Marín-Calvo | Aristides Quintero | Adalberto Nieto | Rolando Carvajal | J. L. González Solís
Source:  (article, 2024-01-01)
Field: Chemistry — Spectroscopy

Advances in the development of thermal insulators based on natural fibers and recycled paper In Panama, at the Universidad Tecnolgica de Panam, as part of the research lines in Manufacturing, Materials, Energy and Environment, several projects have been developed to assess the thermal insulation potential of different materials based on ASTM C-177 standards, for thermal conductivity coefficients determination. The studied materials are rice straw (0.050 W/mK), rice husk (0.073 W/mK), cellulose (obtained from recycled newspaper) (0.041 W/mK), and coconut fiber (0.025 W/mK). The obtained results have demonstrated the potential of these materials as thermal insulators. Although there is a need to improve manufacturing processes and specimen acquisition, the conducted studies have strengthened local capacities in developing new materials from waste. Overall, these investigations lay the groundwork for the development of materials as a sustainable alternative that can be used in environmentally friendly building contexts, contributing to the reduction of carbon footprint and enhancing thermal comfort. Thermal ; Materials science ; Natural (archaeology) ; Engineering physics ; Composite material ; Architectural engineering ; Environmental science ; Engineering ; Physics ; Geology ; Meteorology Aerogels and thermal insulation ; Thermal properties of materials ; Transition Metal Oxide Nanomaterials
Authors: Sean Lawrie
Source: OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (article, 2024-10-30)
Field: Materials Science — Materials Chemistry

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration The DI BCA document also identifies specific, digitally enabled WRO categories for further study. These were selected as most relevant by Reference Plant personnel from a larger list of WRO areas identified across the nuclear industry as captured INL/RPT-21-64134, “Process for Significant Nuclear Work Function Innovation Based on Integrated Operations Concepts.” This ION WRO demonstration report was developed to provide illustrative, specific, and actionable direction for intertwined PTPG changes associated with digital modernization efforts. The coordinated changes in these areas are intended to maximize safe plant operational and economic performance. This includes enabling WROs associated with detailed configuration, implementation, and use of digital systems and how they are supported over their lifecycle. Illustrating this direction through a minimum set of advanced technology examples establishes a model PTPG framework that can be leveraged across the spectrum of nuclear plant digital modernization efforts going forward. This document addresses many related concepts. To promote an integrated understanding of the topics that make up this work, this document contains an extensive set of internal hyperlinks. This set includes hyperlinks to page numbers in the table of contents, section numbers, items in lists, figures, tables, and references to other documents within the report. When hovering the cursor above hyperlinked text in Adobe, the cursor will change from “ ” to “ .” When the “ ” appears, a left mouse click will take the reader to the referenced location in the document. To return to the original location in the document, the reader need only press and hold the “alt” button on the keyboard and then simultaneously press the “<” directional key on the keyboard. Reduction (mathematics) ; Work (physics) ; Computer science ; Engineering ; Mathematics ; Mechanical engineering Graphite, nuclear technology, radiation studies ; Nuclear reactor physics and engineering ; Nuclear and radioactivity studies
Authors: Guojun Zheng | Shengfeng Long | Guanghu Zhu | Qinlong Wang | Ting Luo | Hairong Huang | Lu Liu | Hui Fang | Pengcheng Ma | Yaoyang Shen | Zeping Wang
Source: Agriculture (article, 2024-10-31)
Field: Chemistry — Analytical Chemistry

Spatiotemporal Dynamic Relationship of Meteorological Factors and Sugar Content of Sugarcane by Vector Autoregression Model Sugarcane is a globally significant economic crop, and sugar content is a key determinant of its financial and industrial value. This study utilized sugar content information from spring-planted and ratoon sugarcane in six research regions across Guangxi, China from 2008 to 2023 along with concurrent meteorological data. By conducting statistical tests, the critical meteorological factors influencing the sugar content of sugarcane (effective cumulative temperature and rainfall) were identified. These factors were then used as independent variables to construct a vector autoregression (VAR) model, which was employed to analyze the spatiotemporal dynamic relationships between sugar content and meteorological variables across different planting periods. The empirical results demonstrated that the influence of effective cumulative temperature on sugar content across various regions and planting periods shifted from positive to negative in the short-term, eventually reverting to a positive effect after a period of alternating influences. The impact of rainfall mirrored effective cumulative temperature, though it was relatively less pronounced. The sugarcane in Nanning and Baise was less influenced by effective cumulative temperature and rainfall, with the short-term impact changing from positive to negative and diminishing over time. Our findings provide scientific insights for guiding the ecosystem management of sugarcane in China. Vector autoregression ; Sugar ; Bayesian vector autoregression ; Econometrics ; Mathematics ; Environmental science ; Biology ; Statistics ; Food science Spectroscopy and Chemometric Analyses ; Sugarcane Cultivation and Processing ; Remote Sensing in Agriculture
Authors: Jiaqin Xu | Shuhei Shinzato | Shihao Zhang | Fan-Shun Meng | Shigenobu Ogata
Source: International Conference on Computational & Experimental Engineering and Sciences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Theoretical Study on Hydrogen Diffusion Influenced Screw Dislocation Motion in Body-Centered Cubic Iron Hydrogen has the potential to be the clean energy solution to achieve the sustainable development goals (SDGs). However, from preparation to utilization, the hydrogen embrittlement can not be neglected. Hydrogen embrittlement... | Find, read and cite all the research you need on Tech Science Press Dislocation ; Cubic crystal system ; Diffusion ; Materials science ; Hydrogen ; Crystallography ; Condensed matter physics ; Chemistry ; Physics ; Thermodynamics ; Organic chemistry Microstructure and mechanical properties ; Microstructure and Mechanical Properties of Steels ; Metallurgy and Material Forming
Authors: D. P. Becker | Konrad Steiner | Stefan Rief
Source: Transport in Porous Media (article, 2024-07-01)
Field: Materials Science — Biomaterials

An Efficient Method to Compute Capillary Pressure Functions and Saturation-Dependent Permeabilities in Porous Domains Spanning Several Length Scales Abstract A method for calculating capillary pressure functions and saturation-dependent permeabilities of geometries containing several length scales is presented. The method does not require the exact geometries of the smaller length scales. Instead, it requires the effective two-phase flow parameters. It does this by generating phase distributions that form static equilibria at a selected capillary pressure value, similar to pore-morphology methods. Within a porous material, the effective parameters are used to obtain the corresponding phase saturation. It is shown how these phase distributions can be used in geometries spanning several length scales to calculate the capillary pressure function and saturation-dependent permeabilities. The method is tested on a geometry containing a simple isotropic porous material and it is applied to a complex textile stack geometry from a liquid composite molding process. In this geometry, three different length scales can be distinguished. The effective two-phase flow parameters of the textile stack are calculated by the proposed method, avoiding expensive simulations. Capillary pressure ; Saturation (graph theory) ; Capillary action ; Isotropy ; Materials science ; Porous medium ; Porosity ; Mechanics ; Capillary length ; Geometry ; Capillary number ; Mathematics ; Composite material ; Optics ; Physics Advanced Cellulose Research Studies ; Pickering emulsions and particle stabilization ; Material Properties and Processing
Authors: Juan Morcillo | Pablo Sanchis | Jorge O. Parra
Source:  (preprint, 2024-07-26)
Field: Materials Science — Polymers and Plastics

On-chip electro-optical spiking VO₂/Si device with an inhibitory leaky integrate-and-fire response Integrated photonic neuromorphic computing has emerged as an appealing technology to replicate human brain functionalities by leveraging the benefits of integrated photonics. In this context, spiking neural networks (SNNs) offer a highly energy-efficient artificial neural network due to the event-based information processing. In this work, we propose an electro-optical spiking device for the silicon photonics platform based on a VO₂/Si waveguide and a meander-shaped microheater. A leaky integrate-and-fire (LIF) response with inhibitory optical spiking is achieved by harnessing the temperature-driven insulator-metal transition (IMT) of VO₂ combined with thermal dynamics. Hence, our proposal would not require complex electronic circuitry bottlenecking the neural network. Our numerical simulations demonstrate firing upon milliwatt and nanosecond range postsynaptic pulses and adjustable spike characteristics in the time domain with sub-microsecond values. Therefore, our spiking device could enable scalable and energy-efficient photonic-based SNNs. Inhibitory postsynaptic potential ; Chip ; Optoelectronics ; Materials science ; Electrical engineering ; Neuroscience ; Engineering ; Biology Transition Metal Oxide Nanomaterials ; Thin-Film Transistor Technologies ; Silicon Nanostructures and Photoluminescence
Authors: Enesi Asizehi Yahaya | E.C. Ejiogu
Source: Bulletin of Electrical Engineering and Informatics (article, 2024-04-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Development of stability charts for double salience reluctance machine modeled using hill’s equation The paper presents a novel algorithm for the development of stability charts. The second-order differential homogeneous equation describing a double salient reluctance machine with a capacitance connected to its stator winding is transformed into hill’s equation. The circuit components are the stator coil time-varying inductance of a double salient reluctance machine, capacitance and resistance. All these are modeled by hill’s equation. The double salient reluctance machine acts as an energy conversion system. The maximum and minimum inductance of the energy conversion system is measured in laboratory by inductance, capacitance, and resistance (LCR) meter. These values help to determine the inductance modulation index. The inductance modulation indetx, the characteristic constant and the characteristic parameter obtained from modeling equations are used in the MATLAB/Simulink model. The MATLAB/Simulink simulations generate stable and unstable oscillations to form stability charts. The proposed stability charts are in good agreement with the Ince-Stritt stability chart, which is widely applied in physics, mechanics and in electrical engineering, especially where the state of stability of a system or an electric oscillatory circuit is to be determined. Inductance ; Magnetic reluctance ; MATLAB ; Control theory (sociology) ; Stator ; Capacitance ; LCR meter ; Electromagnetic coil ; Engineering ; Mathematics ; Computer science ; Physics ; Voltage ; Magnet ; Mechanical engineering ; Electrical engineering ; Artificial intelligence Magnetic Properties and Applications ; Electric Motor Design and Analysis ; Model Reduction and Neural Networks
Authors: Victor Rong | J. Chen | Sherwin Bahmani | Kiriakos N. Kutulakos | David B. Lindell
Source: arXiv (Cornell University) (preprint, 2024-09-19)
Field: Materials Science — Polymers and Plastics

GStex: Per-Primitive Texturing of 2D Gaussian Splatting for Decoupled Appearance and Geometry Modeling Gaussian splatting has demonstrated excellent performance for view synthesis and scene reconstruction. The representation achieves photorealistic quality by optimizing the position, scale, color, and opacity of thousands to millions of 2D or 3D Gaussian primitives within a scene. However, since each Gaussian primitive encodes both appearance and geometry, these attributes are strongly coupled--thus, high-fidelity appearance modeling requires a large number of Gaussian primitives, even when the scene geometry is simple (e.g., for a textured planar surface). We propose to texture each 2D Gaussian primitive so that even a single Gaussian can be used to capture appearance details. By employing per-primitive texturing, our appearance representation is agnostic to the topology and complexity of the scene's geometry. We show that our approach, GStex, yields improved visual quality over prior work in texturing Gaussian splats. Furthermore, we demonstrate that our decoupling enables improved novel view synthesis performance compared to 2D Gaussian splatting when reducing the number of Gaussian primitives, and that GStex can be used for scene appearance editing and re-texturing. Geometry ; Gaussian ; Computer science ; Computer graphics (images) ; Mathematics ; Physics Textile materials and evaluations ; 3D Shape Modeling and Analysis
Authors: Yuchao Liao | Tosiron Adegbija | Roman Lysecky
Source: arXiv (Cornell University) (preprint, 2024-08-19)
Field: Materials Science — Surfaces, Coatings and Films

Are LLMs Any Good for High-Level Synthesis? The increasing complexity and demand for faster, energy-efficient hardware designs necessitate innovative High-Level Synthesis (HLS) methodologies. This paper explores the potential of Large Language Models (LLMs) to streamline or replace the HLS process, leveraging their ability to understand natural language specifications and refactor code. We survey the current research and conduct experiments comparing Verilog designs generated by a standard HLS tool (Vitis HLS) with those produced by LLMs translating C code or natural language specifications. Our evaluation focuses on quantifying the impact on performance, power, and resource utilization, providing an assessment of the efficiency of LLM-based approaches. This study aims to illuminate the role of LLMs in HLS, identifying promising directions for optimized hardware design in applications such as AI acceleration, embedded systems, and high-performance computing. Business Electron and X-Ray Spectroscopy Techniques ; Radiopharmaceutical Chemistry and Applications ; Machine Learning in Materials Science
Authors: Yasuhiko Otsuki | Wataru Takarada | Takeshi Kikutani
Source: Seikei-Kakou (article, 2024-02-20)
Field: Materials Science — Materials Chemistry

Utilization of Machine Learning for the Determination of Parameters for Crystallization Models Materials science ; Crystallization ; Process engineering ; Machine learning ; Chemical engineering ; Computer science ; Engineering Crystallization and Solubility Studies ; Mineral Processing and Grinding
Authors: S. Rajabathar
Source: International Journal of Engineering in Computer Science (article, 2024-07-01)
Field: Chemistry — Analytical Chemistry

An innovative method for finding out the glycemic index of raw food items based on two layer feed forward neural networks Nowadays, Artificial Neural Networks play a vital role in diverse fields of applications. New researches are evolving in Artificial Neural Networks now and then in the past few decades. Researches in Artificial Neural Networks have grown rapidly over the past few years. This research work deals with an innovative approach for finding out the Glycemic Index of raw food items using two layers feed forward Neural Networks. This is an innovative theoretical idea by which two layer feed forward Neural Networks are imparted training to learn for some known GI values of some of food items called training set. After training, the two layers feed forward Neural Networks system will be used to find out the GI value of new raw food items which were not trained. In this research work, some of the GI values for some raw food items are taken, their contents, amount of nutrients are given as inputs, weight adjustments are given based on their amount of nutrients and the network is trained. After training, the network will be used for finding out GI values of food items which were not trained. Glycemic index ; Artificial neural network ; Index (typography) ; Layer (electronics) ; Computer science ; Artificial intelligence ; Food science ; Glycemic ; Medicine ; Internal medicine ; Chemistry ; Nanotechnology ; Materials science ; World Wide Web Spectroscopy and Chemometric Analyses ; Food composition and properties ; Advanced Scientific Research Methods
Authors: Majid Azizi | Resta A. Susilo | Darwin Sebayang | Muhamad Fitri
Source: Austenit. (article, 2024-10-31)
Field: Materials Science — Polymers and Plastics

DESIGN CONCEPT FOR THE DEVELOPMENT OF NATURAL PLANT FIBER EXTRACTOR AS A RAW MATERIAL FOR NATURAL FIBER COMPOSITES The design concept is used for the development of natural plant fiber extractors as raw materials for making natural fiber composites. The extractor is a tool used to extract natural plant fibers which are expected to produce natural fibers as raw materials for making natural fiber composites. In the previous tool, there are still several shortcomings that can be redeveloped, both for the sake of the tool itself and in terms of the fiber produced. In this journal, it is focused on making design concepts before the development of the extractor tool, including identifying problems in previous tools, determining the functional structure, finding solutions to existing problems, determining development specifications on the tool and also evaluating from the technical and economic side. In the process of this design concept, There are several things that are highlighted in the previous tools to be developed, including the mobility of the tool, the quality and quantity of fiber produced, production time and safety aspects and also environmentally friendly. Thus, in the end, all of it will be narrowed down to the choice of specifications needed to support this with the consideration of the objective tree. Natural fiber ; Composite material ; Fiber ; Natural (archaeology) ; Materials science ; Extractor ; Raw material ; Process engineering ; Engineering ; Geology ; Chemistry Natural Fiber Reinforced Composites
Authors: Silvana V Croope | Frank Broen | Chris Huffman | Viviane Coêlho de Séllos Knoerr
Source: Gestão e Planejamento (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

INVESTIMENTO EM RESILIÊNCIA PARA INFRAESTRUTURAS E CONTINUIDADE DAS FUNÇÕES CRÍTICAS envolvem vrios nveis hierrquico do poder pblico com o setor privado e ONGs.Os negcios para resilincia resultam de processos escalveis visando o planejamento intermedirio e a longo prazo pela fuso da inteligncia multidisciplinar e auxlio de IA. Theology ; Philosophy Graphite, nuclear technology, radiation studies
Authors: Abhishek Shukla | Boo Carmans | Mihail Petrov | Daan Vrancken | Miloš Nesládek
Source: arXiv (Cornell University) (preprint, 2024-08-23)
Field: Materials Science — Materials Chemistry

High fidelity quantum state tomography of electron-$^{14}$N nuclear hybrid spin register in diamond using Rabi oscillations We report on a new quantum state characterisation method, which we call Rabi-based Quantum State Tomography (RQST), that we have validated on single-qubit quantum states, in particular on the electron and nuclear spins of a single nitrogen-vacancy (NV) centre in diamond, demonstrating high fidelities. The difference of RQST with conventional tomography methods is in the implementation of rotation operators and construction of density matrix from the measured data sets. We demonstrate efficient quantum state control of the electron spin at room temperature with an average fidelity of 0.995 over more than 40 measurements on different states on the Bloch sphere with a maximum fidelity of 0.99992. Also, we apply the methodology to the dark NV nuclear spin state. The state is read via the electron spin using the C-NOT two-qubit entanglement gate and demonstrate fidelities of the same order. Diamond ; Physics ; Electron ; Fidelity ; Rabi cycle ; Register (sociolinguistics) ; Spin (aerodynamics) ; State (computer science) ; Quantum ; Condensed matter physics ; Materials science ; Nuclear physics ; Quantum mechanics ; Computer science ; Algorithm Diamond and Carbon-based Materials Research ; Force Microscopy Techniques and Applications ; Advanced Electron Microscopy Techniques and Applications
Authors: Dominik Lux | Katrin Marcus | Martin Eisenacher | Julian Uszkoreit
Source: Briefings in Bioinformatics (article, 2024-11-22)
Field: Chemistry — Spectroscopy

ProtGraph: a tool for the quick and comprehensive exploration and exploitation of the peptide search space derived from protein sequence databases using graphs Due to computational resource limitations, in mass spectrometry based proteomics only a limited set of peptide sequences is used for the matching against measured spectra. We present an approach to represent proteins by graphs and allow not only the canonical sequences but also known isoforms and annotated amino acid variations, e.g. originating from genomic mutations, and further common protein sequence features contained in Uniprot KB or other protein databases. Our C++ and Python implementation enables a groundbreaking comprehensive characterization of the peptide search space, encompassing for the first time all available annotations in a protein database (in combination more than $10^{200}$ possibilities). Additionally, it can be used to quickly extract the relevant subset of the search space for peptide to spectrum matching, e.g. filtering by the peptide mass. We demonstrate the advantages and innovative findings of our implementation compared to previous workflows by re-analysing publicly available datasets. UniProt ; Sequence database ; Computer science ; Python (programming language) ; Workflow ; Computational biology ; Protein sequencing ; Database ; Peptide ; Database search engine ; Peptide sequence ; Proteogenomics ; Matching (statistics) ; Mascot ; Sequence (biology) ; Data mining ; Information retrieval ; Biology ; Genome ; Genomics ; Search engine ; Genetics ; Programming language ; Gene ; Mathematics ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies