jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fatemeh Tavangar | Ramin Abghari | Mohammad Mirjalili | Hamidreza Amiri
Source: Autex Research Journal (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Optimization of fabric’s tensile strength and bagging deformation using surface response and finite element in stenter machine Abstract Optimization of fabric’s mechanical properties, such as strength and bagging deformation of worsted fabrics, is considered one of the most important cases in relation to the use of stenter machine. Because, in this machine, for providing fabric’s dimensional stability with drying and stretching operations, fundamental changes would occur in these properties. Therefore, in the present study, the mechanical properties of the fabric in stenter machine were optimized through simulation of laboratory conditions as well as simulation by the finite element method. First, using laboratory stenter, the experiments were performed on six common worsted fabric samples by the Design Expert software through changing temperature, percentage of fibers, and weight of the fabric, which were considered as the most effective factors. Then, the changed conditions were determined by the central composite design for optimization. For performing the finite element simulation, the initial design was first created using TexGen software and then, the strength and bagging deformation model was investigated by Abaqus software. The results of the simulation showed a statistically acceptable relationship between actual and practical conditions. Finite element method ; Ultimate tensile strength ; Materials science ; Deformation (meteorology) ; Response surface methodology ; Composite material ; Structural engineering ; Surface (topology) ; Mechanical engineering ; Computer science ; Engineering ; Mathematics ; Geometry ; Machine learning Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Additive Manufacturing and 3D Printing Technologies
Authors: Hasan Mahmood Kaedhi | Luqman Khaleel Hyder Alatrushi | Emad Toma Karash | Mohammad Takey Elias Kassim | Jamal Nayief Sultan
Source: Annales de Chimie Science des Matériaux (article, 2024-12-31)
Field: Materials Science — Materials Chemistry

Comparison of a Medium Carbon Steel Microscopic and Hardness Properties Following Different Heat-Treatments This article investigates how medium carbon steel's microstructure and hardening strength are affected by repeated heat treatment. Finding out the impact of repeatedly heat-treating medium carbon steel is the primary goal of this investigation. In this study, four different heat treatment techniques were used: first quenching, first tempering, second quenching, and second tempering. During the first quenching process, the samples were heated at 870 and left in the oven for 45 minutes. The samples were then quenched in distilled water at different temperatures (0, 5, 10, 15, 20). The first tempering step, which lasted 25 minutes at 350, came after the first quenching step. The samples were heated to 850 and placed in the oven for 45 minutes in order to undergo the second quenching process. After that, the samples were quenched at various temperatures (0, 10, 20, and 30) in a medium containing distilled water. The second tempering procedure came after the second quenching step, which lasted 25 minutes at 450. All samples underwent microscopic inspections and hardness tests following the various heat treatment processes. Each sample's five surface areas underwent hardness testing and microscopy, and the results were compared and analyzed. Research has shown that the steel has undergone various heat treatment procedures, resulting in varying microstructure and hardness values. The hardness of the models that underwent repeated hardening procedures has been shown to significantly increase. In addition, the specimens obtained after the first and second quenching and tempering exhibit a good combination of mechanical properties due to their microstructure. This is because the specimens become more ductile and tough as a result of the quenching and tempering processes, which decrease fragility. Materials science ; Carbon fibers ; Carbon steel ; Composite material ; Metallurgy ; Heat treating ; Composite number ; Corrosion Metal Alloys Wear and Properties ; Microstructure and Mechanical Properties of Steels ; Metal and Thin Film Mechanics
Authors: Alperay Altıkat | Mehmet Hakkı Alma
Source: Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi (article, 2024-11-22)
Field: Chemistry — Analytical Chemistry

Advanced Predictive Analytics in Agriculture: Case Study on Wheat Kernel Weight This research, was aimed at modeling the thousand-grain weight of 13 different wheat varieties using five different input parameters. We used multiple linear regression (MLR), artificial neural networks (ANN), principal component analysis (PCA), and two different hybrid models consisting of PCA + MLR and PCA + ANN for this purpose. The MLR models were tested with various input configurations, demonstrating moderate explanatory power, with R² values ranging from 0.37 to 0.44. Increasing the number of independent variables increased prediction accuracy but also increased the risk of overlearning. ANN models showed significantly higher performance in prediction accuracy. The best performance was achieved in the ANN20 architecture with an R2 value of 0.866. In this architecture, a combination of the gradient descent training function, the hyperbolic tangent sigmoid transfer function, the linear transfer function, and 18 neurons were used. The PCA+MLR hybrid model was not effective in predicting thousand-grain weight. The fact that R² values obtained with different input configurations vary between 0.24 and 0.31 shows that the prediction accuracy of the model is low. In contrast, the PCA+ANN hybrid model significantly improved the prediction accuracy, and the best model achieved an R2 value of 0.981, an RMSE of 0.0829, and an MAE of 0.0359. The PCA+ANN model, which preserved the necessary variance by reducing the complexity of the input data, enabled the ANN to focus on the most critical components for accurate prediction. This study demonstrates that whereas ANN and PCA+ANN models give significantly increased accuracy in predicting wheat varieties' thousand-kernel weights, MLR models only offer moderate prediction capabilities. Principal component analysis ; Mathematics ; Artificial neural network ; Statistics ; Predictive modelling ; Linear regression ; Sigmoid function ; Artificial intelligence ; Explained variation ; Principal component regression ; Pattern recognition (psychology) ; Machine learning ; Computer science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Statistical Methods and Applications
Authors: T. Suhasaria | S. M. Wee | Romain Basalgète | Serge A. Krasnokutski | Christian Jäger | Giulia Perotti | Th. Henning
Source: arXiv (Cornell University) (preprint, 2024-10-16)
Field: Chemistry — Analytical Chemistry

Infrared Spectra of Solid-State Ethanolamine: Laboratory Data in Support of JWST Observations Ethanolamine (NH$_2$CH$_2$CH$_2$OH, EA) has been identified in the gas phase of the ISM within molecular clouds. Although EA has not been directly observed in the molecular ice phase, a solid state formation mechanism has been proposed. However, the current literature lacks an estimation of the infrared band strengths of EA ices. We conducted an experimental investigation of solid EA ice at low temperatures to ascertain its infrared band strengths, phase transition temperature, and multilayer binding energy. The commonly used laser interferometry method was not applied. Infrared band strengths were determined using three distinct methods. The obtained lab spectrum of EA was compared with the publicly available MIRI MRS James Webb Space Telescope observations toward a low mass protostar. The phase transition temperature for EA ice falls within the range of 175 to 185 K. Among the discussed methods, the simple pressure gauge method provides a reasonable estimate of band strength. We derive a band strength value of about $1\times10^{-17}$ cm molecule$^{-1}$ for the NH$_2$ bending mode in the EA molecules. Additionally, temperature-programmed desorption analysis yielded a multilayer desorption energy of 0.61$\pm$0.01 eV. By comparing the laboratory data documented in this study with the JWST spectrum of the low mass protostar IRAS 2A, an upper-limit for the EA ice abundances was derived. Solid-state ; Spectral line ; Ethanolamine ; State (computer science) ; Infrared ; Environmental science ; Physics ; Analytical Chemistry (journal) ; Chemistry ; Environmental chemistry ; Astronomy ; Computer science ; Engineering physics ; Organic chemistry ; Algorithm Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Spectroscopy and Laser Applications
Authors: Warude Chetan P | Patil Harshada R
Source: International Journal of Science and Research (IJSR) (article, 2024-05-05)
Field: Chemistry — Analytical Chemistry

Advancements in Pharmaceutical Quality Assurance: Innovations, Technologies, and Future Perspectives Pharmaceutical quality assurance practices are constantly changing due to new technologies, and trends coming to the market. This paper reviewed the most recent developments in QA. Advanced analytical tools, such as high -resolution mass spectrometry, nuclear magnetic resonance spectroscopy, and next -generation sequencing are powerful tools suitable for drug substance characterization. Quality by Design and Process Analytical Technology systems allow for proactively optimizing the manufacturing process and producing robust, repeatable manufacturing processes resulting in high -quality products. Digital transformation technologies, such as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT), revolutionize QA through real -time monitoring and predictive analytics. Challenges such as globalization and counterfeit drug threats are addressed, emphasizing the need for continuous innovation to meet evolving regulatory standards and patient needs. By embracing emerging technologies and prioritizing patient -centric approaches, the pharmaceutical industry is poised to enhance QA practices and deliver safe, effective medications globally. Quality assurance ; Business ; Engineering management ; Pharmaceutical industry ; Engineering ethics ; Process management ; Engineering ; Medicine ; Marketing ; Pharmacology Analytical Methods in Pharmaceuticals
Authors: Phước Lộc Nguyễn | Văn Sử Dương | Nhựt Thanh Trần | Chi-Ngon Nguyen | Chanh-Nghiem Nguyen
Source: Can Tho University Journal of Science (article, 2024-08-30)
Field: Chemistry — Analytical Chemistry

Dự đoán độ ngọt của xoài trên cơ sở dữ liệu phổ thu thập từ cảm biến đa phổ giá thành thấp Nhiều nghiên cứu gần đây cho thấy cảm biến đa phổ giá thành thấp được quan tâm nhiều trong việc phát triển các ứng dụng trong nông nghiệp. Nghiên cứu này đánh giá tiềm năng sử dụng cảm biến đa phổ giá thành thấp trong việc dự đoán độ ngọt của xoài, loại trái cây có giá trị xuất khẩu cao. Để phát triển được mô hình dự đoán chính xác, một số giải thuật tiền xử lý và lựa chọn bước sóng đã được áp dụng. Kết quả cho thấy dữ liệu phổ không qua tiền xử lý trích xuất từ mười bốn bước sóng được chọn bởi giải thuật “hệ số hồi quy” là phù hợp để xây dựng mô hình hồi quy bình phương tối thiểu từng phần có hệ số tương quan bằng 0,703 và sai số RMSE là 1,439 °Brix. Kết quả này có thể so sánh được với các nghiên cứu gần đây sử dụng cùng loại cảm biến đa phổ vì thế khẳng định tiềm năng sử dụng cảm biến đa phổ giá thành thấp trong việc phát triển ứng dụng và thiết bị cầm tay để đánh giá chất lượng trái cây. Chemistry ; Stereochemistry Spectroscopy and Chemometric Analyses ; Essential Oils and Antimicrobial Activity ; Water Quality Monitoring and Analysis
Authors: Fan Yang | Xiangjun Liang | Heng Zhang
Source: Applied and Computational Engineering (article, 2024-07-31)
Field: Materials Science — Materials Chemistry

Wear prediction study considering TBM hob slip Aiming at the problem of serious tool wear and untimely tool change affecting the construction efficiency when TBM is digging in microfractured tuff strata, the hob wear prediction study is carried out based on engineering examples. By analysing the rock-breaking mechanism of hob wear, a linear wear rate model and a life prediction model considering hob slip are derived based on the CSM model and the abrasive wear theory; the wear rate and the wear amount at the tool change point are further calculated by the prediction model in comparison with the measured value, and the furthest digging distance of the hob is calculated by the life prediction model. The results show that: the relative error between the measured average wear rate and the calculated linear wear rate considering the hob slip is 5.3%; the life prediction model predicts that the longest digging distance of the positive hob is 857 rings and the shortest distance is 198 rings. The results of the study are of guiding significance for the prediction of tool wear and the selection of the timing of opening and changing the hob in TBM tunneling. Slip (aerodynamics) ; Engineering ; Structural engineering ; Aerospace engineering Metal Alloys Wear and Properties ; Tunneling and Rock Mechanics ; Mechanical stress and fatigue analysis
Authors: Koki Ryo | Xi Yang | Yvan Llave | Shingo Matsukawa
Source: Journal of Biorheology (article, 2024-01-01)
Field: Materials Science — Biomaterials

Study on gelatinization of wheat starch paste by localized heating using laser irradiation and subsequent water migration The laser heating in 3D food printings can give a formativeness to food inks by the laser-controlled gelatinization of the paste which improves the handling of the food ink materials. We have elucidated the gelatinization behavior of wheat starch paste by a laser heating. The localized heating by laser irradiation caused the gelatinization of the paste in a millimeter order width which caused a subsequent water migration from the ungelatinized region by the water demand associated with the gelatinization. Polarized microscopy, scanning electron microscope (SEM) observation and magnetic resonance imaging (MRI) have been carried out for the elucidation. The cross-section observation by a polarized microscope showed the melting of starch granule crystals in the laser heated region, and SEM observation indicated the collapse of starch granules to give the gelatinized lumps engulfing the water. MRI measurements gave the distribution of water content in the laser heated paste suggesting the water migration from the ungelatinized region where the gelatinization by the following laser heating was restrained because of the low water content. The water migration was reproduced in a model paste sheet with one side heating where the side was gelatinized with the increase of water content and another side decreased in the water content. The results of this study provide useful information on developing laser cooking techniques, allowing laser heating to find potential applications in the food processing industry including 3D food printing. Starch ; Starch gelatinization ; Irradiation ; Materials science ; Food science ; Composite material ; Chemical engineering ; Chemistry Collagen: Extraction and Characterization
Authors: Ubah Pandapotan | Mulyadi Mulyadi
Source: Innovative Technologica Methodical Research Journal (article, 2024-02-20)
Field: Materials Science — Materials Chemistry

Pengaruh Media Pendingin terhadap Porositas dan Kekuatan Tarik menggunakan Pengelasan SMAW DCSP pada Material Pipa Baja Karbon SCH40 Pada penelitian ini bertujuan untuk mengetahui pengaruh media pendinginan terhadap kekuatan tekan setelah dilakukan pengelasan SMAW pada material pipa baja karbon SCH 40 dan pengaruh pendingin terhadap cacat porositas setelah dilakukan pengelasan SMAW pada material pipa baja karbon SCH 40. Media pendinginan menggunakan Udara, Oli Bekas, Coolant, Air Sumur. Metode pengelasan yang digunakan SMAW DCSP, hasil pengelasan dilakukan pengujian tekan dan porositas. Dari hasil penelitian diperoleh material dengan media pendinginan air mempunyai nilai tegangan tarik tertinggi 61,33 Kgf/mm2, Coolant 50,21 Kgf/mm2, Oli bekas 44,33 Kgf/mm2,Udara 40,18 Kgf/mm2. Dari hasil penelitian ini diketahui material setelah dilakukan pengelasan dengan perbedaan media pendinginan (quenching) berpengaruh terhadap kekuatan tarik, dengan media pendinginan air mempunyai nilai tegangan tarik tertinggi dan regangan tertinggi dari media lainnya seperti oli bekas, coolant, udara. Materials science Material Selection and Properties ; Metallurgical Processes and Thermodynamics ; Materials Engineering and Processing
Authors: Roni Kusnowo | Hanif Azis Budiarto | Cecep Ruskandi | Sophiadi Gunara | Ery Hidayat | Muhammad Nahrowi | Emma Dwi Ariyani
Source: Journal of Applied Engineering and Technological Science (JAETS) (article, 2024-12-15)
Field: Materials Science — Materials Chemistry

Optimizing Low-Pressure Die Casting of A356 Aluminum Alloy Wheel Rims: A Novel Side Core With Integrated Cooling System This study explores the development of a novel side core design with an integrated cooling system for the low-pressure die casting (LPDC) of A356 aluminum alloy wheel rims in Indonesia. The objective is to reduce cycle time and minimize casting defects. The methodology involves 3D modeling using SolidWorks and simulations performed with MAGMAsoft to evaluate filling and solidification behavior, air pressure, and air entrapment. Notably, this is the first application of a cooling system in Side cores within the Indonesian automotive industry, motivated by the need to improve production efficiency and product quality, as current manufacturing processes suffer from long cycle times and high defect rates. Simulation results show a significant reduction in cycle time by 72 seconds, improving both efficiency and product quality. This study demonstrates the effectiveness of integrating cooling systems into side cores to enhance the LPDC process. Die casting ; Core (optical fiber) ; Die (integrated circuit) ; Alloy ; Materials science ; Aluminium ; Casting ; Metallurgy ; Water cooling ; Mechanical engineering ; Composite material ; Engineering Metallurgy and Material Science ; Aluminum Alloy Microstructure Properties ; Metallurgy and Material Forming
Authors: Matthew S. Johnson | S. Kim | Trevor Price | Judit Zádor
Source:  (article, 2024-04-01)
Field: Materials Science — Materials Chemistry

Pynta: Using Machine Learning to Improve High Throughput Discovery of Transition States and Calculation of Surface and Gas-Surface Kinetics Throughput ; Kinetics ; Surface (topology) ; Computer science ; Transition state ; Materials science ; Chemical physics ; Chemistry ; Physics ; Mathematics ; Catalysis ; Operating system ; Quantum mechanics Machine Learning in Materials Science
Authors: Amanjot Kaur | Nirmal Kaur
Source: ShodhKosh Journal of Visual and Performing Arts (review, 2024-01-31)
Field: Chemistry — Analytical Chemistry

A REVIEW ON ROLE OF METAHEURISTIC AND MACHINE LEARNING IN WHEAT DISEASE DETECTION Wheat is one of the highest cultivated and important crops to mankind but diseases are known to reduce grain yield potential and quality and have historically caused major crop losses. Diseases detection is very important for increasing the livelihood of crops. The early detection of diseases can be very helpful in curing the disease completely. Many techniques have been developed to detect the diseases in wheat crop at an early stage. In this paper we have surveyed the meta heuristic and machine learning techniques used for the detection of wheat diseases. Both the techniques have shown the better results in increasing the efficiency and accuracy of the algorithms used for the detection the wheat crop disease. Metaheuristic ; Machine learning ; Computer science ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Thomas Ginnis | Rebecca J. Nicholls | D. J. Armstrong
Source: BIO Web of Conferences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Structure Prediction using Data Derived Potentials and EELS The EDDP method has enabled rapid random structure searching systems which were previously too large to search efficiently.This has opened up a workflow in which EELS can be used on a wider range of materials, including those which do not have high quality reference standards or even known crystal structures in large databases.The usefulness of this workflow was demonstrated on silicised BN, and further work could use a similar workflow to understand how the composition and ELNES of these materials changes as a result of environmental degradation. Neuroscience ; Computer science ; Biological system ; Biology Machine Learning in Materials Science ; Advanced Data Processing Techniques
Authors: Chi, Hanbin | Hu, Yueqiang | Ou, Xiangnian | Jiang, Yuting | Yu, Dian | Lou, Shaozhen | Wang, Quan | Xie, Qiong | Qiu, Cheng-Wei | Duan, Huigao
Source: arXiv (Cornell University) (preprint, 2024-06-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Neural Network-Assisted End-to-End Design for Dispersive Full-Parameter Control of Meta-Optics Flexible control light field across multiple parameters is the cornerstone of versatile and miniaturized optical devices. Metasurfaces, comprising subwavelength scatterers, offer a potent platform for executing such precise manipulations. However, the inherent mutual constraints between parameters of metasurfaces make it challenging for traditional approaches to achieve full-parameter control across multiple wavelengths. Here, we propose a universal end-to-end inverse design framework to directly optimize the geometric parameter layout of meta-optics based on the target functionality of full-parameter control across multiple wavelengths. This framework employs a differentiable forward simulator integrating a neural network-based dispersive full-parameter Jones matrix and Fourier propagation to facilitate gradient-based optimization. Its superiority over sequential forward designs in dual-polarization channel color holography with higher quality and tri-polarization three-dimensional color holography with higher multiplexed capacity is showcased. To highlight the universality, we further present polarized spectral multi-information processing with six arbitrary polarizations and three wavelengths. This versatile, differentiable, system-level design framework is poised to expedite the advancement of meta-optics in integrated multi-information display, imaging, and communication, extending to multi-modal sensing applications. Holography ; Multiplexing ; Inverse ; Matrix (chemical analysis) ; Control (management) ; Channel (broadcasting) ; Field (mathematics) Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Plasmonic and Surface Plasmon Research