jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: I. B. Olenych
Source: Electronics and Information Technologies (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

FIELD-EFFECT TRANSISTOR BASED ON REDUCED GRAPHENE OXIDE Graphene field-effect transistors are recognized as a potential alternative to metal-oxide-semiconductor transistors and can become a new element base in the post-silicon epoch. Increasing the efficiency of graphene electronic devices and simplifying their manufacturing technology are important R&amp;D areas. New technical solutions related to the development of graphene field-effect transistors are proposed in the paper. A reduced graphene oxide (RGO) film was used as the conducting channel of the field-effect transistor. A film-forming suspension of RGO obtained by the chemical reduction of graphene oxide with hydrazine monohydrate was deposited on the silicon substrate with a SiO 2 layer and air-dried at room temperature. A comparative analysis of ultraviolet and visible absorbance spectra of the graphene oxide and RGO films on a glass substrate indicates the high degree of graphene nanosheet reduction. The electrical properties of the field-effect transistor based on RGO were studied in DC and AC modes. The nonlinear character of the I D - V D curves of the obtained field-effect transistor was revealed. A significant influence of electrically active defects in the SiO 2 layer on the bipolar electrical conductivity of the RGO film was established based on the analysis of current-voltage characteristics and the dependence of the resistance of the field-effect transistor conductive channel on the gate voltage. An analysis of the switching characteristics revealed sections of linear dependence of the drain current I D on the gate voltage V G with an I on / I off ratio of more than two orders of magnitude. The high sensitivity of the RGO film conductivity near the point of charge neutrality to the local electric field can be used to create photo- and gas-sensitive sensor devices based on the RGO field-effect transistor. Key words : graphene field-effect transistor, reduced graphene oxide, current-voltage characteristic, switching characteristic. Graphene ; Materials science ; Transistor ; Field-effect transistor ; Optoelectronics ; Oxide ; Substrate (aquarium) ; Gate oxide ; Nanotechnology ; Voltage ; Electrical engineering Graphene research and applications
Authors: Nguyễn Duy Lưu | Tran Duong Duy | Tran Thuc Binh
Source: MOJ Applied Bionics and Biomechanics (article, 2023-05-29)
Field: Chemistry — Analytical Chemistry

Simultaneous determination of paracetamol and codeine phosphate in pharmaceuticals using molecular absorption spectroscopy and classical least squares method In this article, a combined method of molecular absorption spectroscopy and classical least squares is used to simultaneously determine paracetamol (PAR) and codeine phosphate (COP) in pharmaceutical samples without the need for prior separation or extraction steps. The absorption spectra of standard solutions and samples were measured in the wavelength range of 210 to 290 nm with a step size of 0.5 nm. The concentrations of PAR and COP in the sample solutions were calculated using a self-made program written in Microsoft Excel 2016 and Visual Basic for Applications (VBA). The reliability of the method was verified through the accuracy and reproducibility of the measurements when analyzing PAR and COP in Effer-Paralmax® Codeine tablets, and comparing the average values of their concentrations in the samples with the standard HPLC method. Reproducibility ; Chromatography ; Analytical Chemistry (journal) ; Chemistry ; Absorption spectroscopy ; Absorption (acoustics) ; Materials science ; Optics ; Physics Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Sensors ; Advanced Chemical Sensor Technologies
Authors: Al Ichlas Imran | Jenny Delly | Samhuddin Samhuddin | Janviter Manalu | Johni Jonathan Numberi | Apolo Safanpo
Source: Journal of Innovation and Technology (article, 2023-12-01)
Field: Materials Science — Polymers and Plastics

A Review of Banana Fiber: Impact of Treatment, Filler Materials, Hybrid Composite, and Application This review paper examines the significance of comprehending the attributes of banana fibers and their initial processing in influencing the mechanical, thermal, and morphological aspects of composites. The study's findings indicated that the application of alkaline solutions or other chemicals to banana fibers had a substantial influence on the performance of the composite material. Modifications in fiber treatment parameters have the potential to modify composite characteristics, such as the interplay between fibers and matrix. Incorporating filler elements significantly affects the composite by enhancing its rigidity and grip while also altering physical characteristics like heat conduction and resistance to corrosion. The utilization of banana fiber components, in conjunction with other fiber and filler materials, showcases ingenuity in creating sustainable composites for various industrial applications. The study emphasizes the necessity of creating more robust, less weighty, and ecologically conscious composites across several industrial domains. The study also emphasizes the potential of banana's fiber-enhancing composites in several industries, such as automotive, construction, aerospace, electronics, and sports. Filler (materials) ; Composite number ; Composite material ; Materials science ; Fiber Natural Fiber Reinforced Composites ; Advanced Cellulose Research Studies ; Nanocomposite Films for Food Packaging
Authors: Ramoni Tirimisiyu Amosa | Adebanjo Adekiigbe | Fabiyi Aderanti Alifat | Olorunlomerue Adam Biodun | Oni Esther Kemi | Adejola Aanu Adeyinka | Adigun Olajide Israel | Joseph Babatunde Isaac
Source: International Journal of Computer Science and Engineering (article, 2023-05-25)
Field: Chemistry — Analytical Chemistry

Investigating Tree-Based Classifiers and Selected Ensemble Learning on Iris Flower Species Classification Eloquence, hope, knowledge, the ability to communicate effectively, and faith are some of the meanings associated with the iris flower in the language of flowers. Iris has different species types, and each type has its own medicinal purpose. Classifying the flower has become a serious task for researchers due to the high volume of datasets (big data), hence the introduction of machine learning algorithms for accurate and reliable classification. This paper focuses on the classification of the Iris flower using five tree-based algorithms; Best First Tree (BFTree), Least Absolute deviation Tree (LADTree), Cost-Sensitive Decision Forest (CSForest), Functional Tree (FT) and Random Tree (RT). Three selected ensemble learning (Bagging, Dagging and cascade generalisation) were equally implemented in the algorithm. The dataset that was utilised in this investigation is open source and may be downloaded without cost from a public repository (kaggle.com). The result of the classification showed that the FT classifiers outperform other tree-based classifiers with an accuracy of 96.67% and an AUC of 1.00. The ensemble algorithm has a significant impact on the performance of single classifiers (tree-based). Outperform tree based. AUC/ROC (Area Under Curve/Receiver Operating Characteristics) was used to evaluate the algorithm's performance. Bagging ensemble outperforms other ensembles (Dagging and Cascade) with an accuracy of 96.00% and AUC of 1.00. Random forest ; Artificial intelligence ; Machine learning ; Computer science ; Tree (set theory) ; Decision tree ; Ensemble learning ; Cascading classifiers ; Pattern recognition (psychology) ; Random subspace method ; Support vector machine ; Mathematics Spectroscopy and Chemometric Analyses
Authors: Muhammad Ansarullah | Putri Viani | Nibras Zuhra | Dylla Putri | Budiana Budiana
Source:  (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Study of Corrosion Rate at Aluminum Duralumin with YCbCr Filter Method Corrosion is a process of damage to metal materials that occurs due to the reaction of the metal with the surrounding environment. Corrosion can threaten structural safety, life safety, environmental protection, and economic development. The cost that must be incurred to carry out corrosion testing Corrosion ; Aluminium ; Materials science ; Metallurgy ; Filter (signal processing) ; Metal ; Environmental science ; Computer science Corrosion Behavior and Inhibition ; Anodic Oxide Films and Nanostructures ; Material Selection and Properties
Authors: Zhangzhi Xue | Tiansheng Zhu | Fangfei Zhang | Cheng Zhang | Nan Xiang | Liujia Qian | Xiao Yi | Yaoting Sun | Wei Liu | Xue Cai | Linyan Wang | Xizhe Dai | Liang Yue | Lu Li | Thang V. Pham | Sander R. Piersma | Qi Xiao | Meng Luo | Cong Lu | Jiang Zhu | Yongfu Zhao | Guangzhi Wang | Junhong Xiao | Tong Liu | Zhiyu Liu | Yi He | Qi‐Jun Wu | Ting‐Ting Gong | Jianqin Zhu | Zhiguo Zheng | Juan Ye | Yan Li | Connie R. Jiménez | A. S. Jun | Tiannan Guo
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-01-08)
Field: Chemistry — Spectroscopy

DPHL v2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins Summary A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v1, a previous pan-human library built from 1096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying 10,943 proteins. However, a major limitation of DPHL v1 is the lack of semi-tryptic peptides and protein isoforms, which are abundant in clinical specimens. Here, we generated DPHL v2 from 1608 DDA-MS data acquired using Orbitrap mass spectrometers. The data included 586 DDA-MS newly acquired from 17 tissue types, while 1022 files were derived from DPHL v1. DPHL v2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v2 to include semi-tryptic peptides and protein isoforms. DPHL v2 was then applied to a publicly available colorectal cancer dataset with 286 DIA-MS files. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v1. Our findings show that the increased human proteome coverage of DPHL v2 provides larger pools of potential protein biomarkers. Human proteome project ; Biomarker discovery ; Proteomics ; Biomarker ; Computational biology ; Human Protein Atlas ; Human breast ; Orbitrap ; Proteome ; Gene isoform ; Mass spectrometry ; Cancer ; Bioinformatics ; Biology ; Computer science ; Chemistry ; Breast cancer ; Biochemistry ; Chromatography ; Genetics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Atthasit Tawai | Malinee Sriariyanun | Chanin Panjapornpon
Source: Green Processing and Synthesis (article, 2023-01-01)
Field: Materials Science — Biomaterials

Optimization-based control strategy for a large-scale polyhydroxyalkanoates production in a fed-batch bioreactor using a coupled PDE–ODE system Abstract Control strategy development for fed-batch bioreactor (FBBR) plays an important role in the improvement of polyhydroxyalkanoate (PHA) production. To develop a feeding strategy for PHA production in a large-scale FBBR, an optimization-based control scheme that considers nutrient dispersion is proposed in this work. A coupled partial differential equations and ordinary differential equation model is proposed to describe the axial-dispersed nutrient and well-dispersed microbial dynamics with process constraints. An analytical model predictive control (AMPC) method that applies integrated variables of nutrients is employed to develop the real-time control system. The control objective is to regulate the PHA concentration at the updated set points by adjusting the nutrient feed rates; a process disturbance is introduced to evaluate the control robustness. Simulation experiments of a fed-batch operation are conducted to investigate the performance of the developed controller; the controlled output is designed to track the updated set points corresponding to the biomass concentration. Results of closed-loop and regulatory systems showed that the proposed control strategy could provide more productivity (33–38%) compared to the applied PI controller. The performance test demonstrates that the developed control system could apply the biomass concentration for updating set points, provide the optimal control actions that promote PHB accumulation and handle the disturbance effectively. Polyhydroxyalkanoates ; Bioreactor ; Control theory (sociology) ; Controller (irrigation) ; Process control ; Computer science ; Optimal control ; Ode ; Process engineering ; Process (computing) ; Mathematical optimization ; Mathematics ; Engineering ; Control (management) ; Chemistry ; Biology biodegradable polymer synthesis and properties ; Microbial Metabolic Engineering and Bioproduction ; Enzyme Catalysis and Immobilization
Authors: Benjamin A. Jasperson | Michael G. Wood | Harley T. Johnson
Source:  (article, 2023-07-01)
Field: Materials Science — Polymers and Plastics

Inverse Design and Fabrication of a Vanadium Dioxide Optical Device using a Dual Neural Network Topology Optimization Approach Can we find a pixelated Vanadium dioxide ; Dual (grammatical number) ; Fabrication ; Topology (electrical circuits) ; Inverse ; Topology optimization ; Computer science ; Materials science ; Artificial neural network ; Electronic engineering ; Nanotechnology ; Physics ; Engineering ; Artificial intelligence ; Electrical engineering ; Mathematics Transition Metal Oxide Nanomaterials
Authors: Zhaina Sakhanova | Zhenisgul Rakhmetullina | Roza Mukasheva | Raushan Mukhamedova | Indira Uvaliyeva | G. A. Vityuk
Source: Eastern-European Journal of Enterprise Technologies (article, 2023-12-14)
Field: Materials Science — Materials Chemistry

Identification of the regularities of the thermohydraulic processes of the cooling system of an experimental device based on a mathematical model The article is devoted to the study of a nitrogen supply system for cooling an experimental device designed for testing in a pulsed reactor with a graphite moderator. To analyze emergency situations caused by disruption of the nitrogen supply system in the cooling paths of the fuel assembly cover and the experimental device power housing, a mathematical model has been developed to describe thermodynamic processes in a system of interconnected tanks that simulate individual sections of the experimental device hydrodynamic cooling system in a pulsed graphite reactor and implemented in the mathematical interactive package for engineering calculations in MATLAB/Simulink. To study the normal operation of the system and analyze possible emergencies, the cooling system of the experimental device was presented in the form of groups of interconnected sections of the hydrodynamic system-tanks, with specified volumes and hydraulic resistances of pipelines connecting these tanks. Verification of the model, calculations of the experimental device cooling system normal operation mode, calculations of emergency situations caused by a violation of the nitrogen supply system normal operation in the cooling paths of the fuel assembly cover were carried out, in particular, it was found that for the cooling system of the experimental device WF-2, the breakdown of the gearbox P-12 can cause depressurization of the fuel assembly cover and an increase in pressure in the power housing, the opening of the safety valve prevents exceeding the pressure limit in the housing, the device maintains integrity even in emergency situations, without being subjected to destruction of the power elements of the structure at a pressure of up to 8 MPa Water cooling ; Cabin pressurization ; Nuclear engineering ; Power (physics) ; Mechanical engineering ; Engineering ; Automotive engineering ; Thermodynamics ; Physics Graphite, nuclear technology, radiation studies ; Nuclear reactor physics and engineering ; Advanced Data Processing Techniques
Authors: Silviu‐Marian Udrescu | Diego A. Torres | R. F. García Ruíz
Source: arXiv (Cornell University) (preprint, 2023-04-25)
Field: Chemistry — Spectroscopy

Precision Spectroscopy of Fast, Hot Exotic Isotopes Using Machine Learning Assisted Event-by-Event Doppler Correction We propose an experimental scheme for performing sensitive, high-precision laser spectroscopy studies on fast exotic isotopes. By inducing a step-wise resonant ionization of the atoms travelling inside an electric field and subsequently detecting the ion and the corresponding electron, time- and position-sensitive measurements of the resulting particles can be performed. Using a Mixture Density Network (MDN), we can leverage this information to predict the initial energy of individual atoms and thus apply a Doppler correction of the observed transition frequencies on an event-by-event basis. We conduct numerical simulations of the proposed experimental scheme and show that kHz-level uncertainties can be achieved for ion beams produced at extreme temperatures ($&gt; 10^8$ K), with energy spreads as large as $10$ keV and non-uniform velocity distributions. The ability to perform in-flight spectroscopy, directly on highly energetic beams, offers unique opportunities to studying short-lived isotopes with lifetimes in the millisecond range and below, produced in low quantities, in hot and highly contaminated environments, without the need for cooling techniques. Such species are of marked interest for nuclear structure, astrophysics, and new physics searches. Spectroscopy ; Millisecond ; Atomic physics ; Computational physics ; Ionization ; Ion ; Isotope ; Physics ; Event (particle physics) ; Leverage (statistics) ; Doppler effect ; Plasma ; Electron ; Nuclear physics ; Computer science ; Astrophysics Mass Spectrometry Techniques and Applications ; Nuclear Physics and Applications ; Isotope Analysis in Ecology
Authors: Akio Tomiya | Yuki Nagai
Source: arXiv (Cornell University) (preprint, 2023-10-20)
Field: Materials Science — Materials Chemistry

Equivariant Transformer is all you need Machine learning, deep learning, has been accelerating computational physics, which has been used to simulate systems on a lattice. Equivariance is essential to simulate a physical system because it imposes a strong induction bias for the probability distribution described by a machine learning model. This reduces the risk of erroneous extrapolation that deviates from data symmetries and physical laws. However, imposing symmetry on the model sometimes occur a poor acceptance rate in self-learning Monte-Carlo (SLMC). On the other hand, Attention used in Transformers like GPT realizes a large model capacity. We introduce symmetry equivariant attention to SLMC. To evaluate our architecture, we apply it to our proposed new architecture on a spin-fermion model on a two-dimensional lattice. We find that it overcomes poor acceptance rates for linear models and observe the scaling law of the acceptance rate as in the large language models with Transformers. Extrapolation ; Equivariant map ; Transformer ; Monte Carlo method ; Homogeneous space ; Computer science ; Lattice (music) ; Architecture ; Artificial intelligence ; Statistical physics ; Mathematics ; Physics ; Pure mathematics ; Mathematical analysis ; Quantum mechanics ; Geometry Machine Learning in Materials Science ; Topic Modeling ; Quantum many-body systems
Authors: Dr.M.Srinivasa Rao | Sabbisetti Vamsi | T - DINESHKUMAR | R.Someswara Rao | V.Viswanath Ganesh | P.Mohan Thulasiram
Source: International Journal of Research Publication and Reviews (article, 2023-03-28)
Field: Materials Science — Polymers and Plastics

Preparation, Characterization and Optimization of a Novel Natural Fibre Based Composites using GRA and Topsis Technique Over the years, the natural fiber reinforced Composite materials are gaining a supreme demand in the fabrication industry of various materials owing to their low cost, biodegradable and good mechanical, electrical and thermal properties.The goal of this study was to enhance the Mechanical performance of composites made from Pineapple leaf fiber, Coconut shell powder, and Tectonasgrandis leaf powder as a reinforcement and Epoxy resin as their matrix using the Hand layup technique.The composites were reinforced with 0-30 wt% fiber and 0-30 wt% coconut shell and Tectonasgrandis and their combinations respectively.Mechanical tests like Tensile, Compression, Impact and Hardness tests are conducted on the specimens.The composites produced good results like 14.74 MPa Tensile, 29.51 Compression MPa, 0.046 J/mm 2 Impact Strength for Hybrid Composite material.The same results were optimized using various analyzing Techniques.Through the use of Taguchi-based grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods, The best conditions for achieving the best mechanical properties in the developed composites were identified.The results showed that the hybrid reinforced composite material outperformed other combinations in terms of mechanical properties. Composite material ; Characterization (materials science) ; TOPSIS ; Materials science ; Mathematics ; Operations research ; Nanotechnology Natural Fiber Reinforced Composites ; Scientific and Engineering Research Topics ; Aluminum Alloys Composites Properties
Authors: Juefei Wu | Bangshuai Zhu | Chi Ding | Dexi Shao | Cuiying Pei | Qi Wang | Jian Sun | Yanpeng Qi
Source: arXiv (Cornell University) (preprint, 2023-12-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Enhancement of superconducting transition temperature and exotic stoichiometries in Lu-S system under high pressure Binary metal sulfides are potential material family for exploring high Tc superconductors under high pressure. In this work, we study the crystal structures, electronic structures and superconducting properties of the Lu-S system in the pressure range from 0 GPa to 200 GPa, combining crystal structure predictions with ab-initio calculations. We predict 14 new structures, encompassing 7 unidentified stoichiometries. Within the S-rich structures, the formation of S atom cages is beneficial for superconductivity, with the superconducting transition temperature 25.86 K and 25.30 K for LuS6-C2/m at 70 GPa and LuS6-R-3m at 90 GPa, respectively. With the Lu/(Lu+S) ratio increases, the Lu-d electrons participate more in the electronic properties at the Fermi energy, resulting in the coexistence of superconductivity and topological non-triviality of LuS2-Cmca, as well as the superconductivity of predicted Lu-rich compounds. Our calculation is helpful for understanding the exotic properties in transition metal sulfides system under high pressure, providing possibility in designing novel superconductors for future experimental and theoretical works. Superconductivity ; Condensed matter physics ; Stoichiometry ; Atom (system on chip) ; Crystal structure ; Superconducting transition temperature ; Transition temperature ; Electronic structure ; Fermi level ; Materials science ; Chemistry ; Electron ; Physics ; Crystallography ; Physical chemistry ; Quantum mechanics Iron-based superconductors research ; High-pressure geophysics and materials ; Rare-earth and actinide compounds