jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ashwin Bale | Sachin M. B. Gautham | Tarak K. Patra
Source: Journal of Polymer Science (article, 2022-04-25)
Field: Materials Science — Materials Chemistry

Sequence‐defined Pareto frontier of a copolymer structure Abstract The correlations between the sequence of monomers in a macromolecule and its three‐dimensional (3D) structure is a grand challenge in polymer science. The properties and functions of macromolecules depend on their 3D shape that has appeared to be dictated by their monomer sequence. However, the progress towards understanding the sequence–structure‐property correlations and their utilization in materials engineering are slow because it is almost impossible to characterize an astronomically large number of possible sequences of a copolymer using traditional experimental and simulation methods. To address this problem, here, we combine evolutionary computing and coarse‐grained molecular dynamics (CGMD) simulation and study the sequence‐structure correlations of a model AB‐type copolymer in a solution and assess the impact of sequence on the packing density in its bulk phase. The CGMD‐based evolutionary algorithm (EA) screens the sequence space of a single chain copolymer efficiently and identifies a wide range of single‐molecule structures including extremal radii of gyration. The data are utilized to estimate the Pareto front of the structure‐space of a binary copolymer as a function of its composition. The monomer packings in single‐molecule solution phase and multimolecular bulk phase are found to be identical. The work highlights the opportunities of sequence‐specific control of macromolecular structure for designing target materials. Copolymer ; Sequence (biology) ; Macromolecule ; Gyration ; Monomer ; Materials science ; Sequence space ; Polymer ; Molecule ; Phase (matter) ; Molecular dynamics ; Computational chemistry ; Statistical physics ; Thermodynamics ; Chemistry ; Mathematics ; Physics ; Geometry ; Organic chemistry Block Copolymer Self-Assembly ; Protein Structure and Dynamics ; Polymer crystallization and properties
Authors: Austin Ladshaw | Sreshtha Sinha Majumdar | Josh A. Pihl
Source: Applied Catalysis B: Environmental (article, 2022-12-09)
Field: Materials Science — Materials Chemistry

Experiments and modeling to evaluate global reaction kinetics of three-way catalyst light off for net-zero carbon fuels and selected fuel blends Combustion ; Catalysis ; Work (physics) ; Carbon fibers ; Cold start (automotive) ; Process engineering ; Internal combustion engine ; NOx ; Environmental science ; Chemistry ; Chemical engineering ; Waste management ; Materials science ; Engineering ; Mechanical engineering ; Automotive engineering ; Organic chemistry ; Composite number ; Composite material Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Advanced Combustion Engine Technologies
Authors: Michał Rogala | Wojciech Tuchowski | Dorota Czarnecka‐Komorowska | K. Gawdzińska
Source: Advances in Science and Technology – Research Journal (article, 2022-09-11)
Field: Materials Science — General Materials Science

Analysis and Assessment of Aluminum and Aluminum-Ceramic Foams Structure The paper presents an analysis of the aluminum porous structure serving as a structural material used in the automotive or marine industry. The subject of the research is the analysis of the mechanical properties of the aluminum porous structure, in particular its ability to absorb energy in comparison with quality of manufactured porous structures. The paper presents a description of the manufacturing process, quality control in the form of a statistical capture of geometric parameters of the foam made, as well as an X-ray microanalysis of the chemical composition of EPMA-EDS and the dispersion of components within the structure. In addition, results of static axial compression analysis of aluminum and composite foam specimens are presented. Aluminium ; Materials science ; Ceramic ; Composite material ; Metal foam Material Properties and Applications
Authors: Ali Khumaidi | Yohanes Aris Purwanto | Heru Sukoco | Sony Hartono Wijaya
Source: Sensors (article, 2022-12-11)
Field: Chemistry — Analytical Chemistry

Using Fuzzy Logic to Increase Accuracy in Mango Maturity Index Classification: Approach for Developing a Portable Near-Infrared Spectroscopy Device Grading is a decisive step in the successful distribution of mangoes to customers according to their preferences for the maturity index. A non-destructive method using near-infrared spectroscopy has historically been used to predict the maturity of fruit. This research classifies the maturity indexes in five classes using a new approach involving classification modeling and the application of fuzzy logic and indirect classification by measuring four parameters: total acidity, soluble solids content, firmness, and starch. These four quantitative parameters provide guidelines for maturity indexes and consumer preferences. The development of portable devices uses a neo spectra micro development kit with specifications for the spectrum of 1350-2500 nm. In terms of computer technology, this study uses a Raspberry Pi and Python programming. To improve the accuracy performance, preprocessing is carried out using 12 spectral transformation operators. Next, these operators are collected and combined to achieve optimal performance. The performance of the classification model with direct and indirect approaches is then compared. Ultimately, classification of the direct approach with preprocessing using linear discriminant analysis offered an accuracy of 91.43%, and classification of the indirect approach using partial least squares with fuzzy logic had an accuracy of 95.7%. Fuzzy logic ; Preprocessor ; Linear discriminant analysis ; Maturity (psychological) ; Mathematics ; Artificial intelligence ; Computer science ; Data mining ; Pattern recognition (psychology) ; Algorithm Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Leaf Properties and Growth Measurement
Authors: С. А. Зелепугин | Nadezhda V. Pakhnutova | О. А. Шкода | E. N. Boyangin
Source: Metals (article, 2022-12-19)
Field: Materials Science — Materials Chemistry

Experimental Study of the Microhardness and Microstructure of a Copper Specimen Using the Taylor Impact Test One commonly used method for characterizing the dynamic characteristics of materials is the Taylor impact test. This method measures the dynamic yield strength of cylindrical specimens and determines material model constants required for the numerical simulation of the behavior of materials subjected to high-velocity deformation. The purpose of this work is to investigate the microhardness and microstructure of copper specimens at different impact velocities using the Taylor impact test. This paper describes experiments performed on copper specimens (OFHC 99.9%, M1) using a single-stage light-gas gun with impact velocities in the range of 150–450 m/s. After impact, the specimens were cut along the symmetry axis to measure the microhardness and the grain size of the microstructure. Microhardness in the entire area exceeded the initial value for all investigated velocities. The averaged microhardness curves were obtained for each specimen to identify four deformation zones and determine their dimensions depending on the impact velocity. The average grain size in the entire deformed specimen became smaller than in the starting specimen. The study of the microstructure of the specimens has shown that the grain size distribution corresponds to the four deformation zones in the copper specimens. Indentation hardness ; Microstructure ; Materials science ; Grain size ; Deformation (meteorology) ; Composite material ; Copper ; Yield (engineering) ; Metallurgy High-Velocity Impact and Material Behavior ; Electromagnetic Launch and Propulsion Technology ; Metal and Thin Film Mechanics
Authors: Chenglong Zhao | Yan Qin | Xiaotian Wang | Han Xiao
Source: e-Polymers (article, 2022-01-01)
Field: Materials Science — Polymers and Plastics

Coefficient of thermal expansion and mechanical properties of modified fiber-reinforced boron phenolic composites Abstract Boron phenolic resin is widely used in the aerospace field because of its excellent thermal properties. In this article, nitrile rubber powder was added to phenolic resin to modify fiber-reinforced phenolic resin composites. The results showed that the tensile strength continued to decrease; the elongation ratio increased from 20.01% to 32.04%; and flexural strength and flexural modulus reached the highest values of 188 and 9,401 MPa, respectively. Thermal analysis showed that rubber had little effect on the heat resistance at low temperatures, especially below 350°C. Furthermore, the coefficient of thermal expansion of the composites increased from 8.9 × 10 −6 to 1.5 × 10 −5 K −1 , increasing by nearly 70%. The electron microscopy images showed a tortuous fracture path in modified composites, which indicated that rubber powder–modified phenolic composites had a ductile fracture. Composite material ; Materials science ; Flexural strength ; Ultimate tensile strength ; Thermal expansion ; Natural rubber ; Flexural modulus ; Boron ; Fiber ; Modulus ; Chemistry Natural Fiber Reinforced Composites ; Tribology and Wear Analysis ; Mechanical Behavior of Composites
Authors: Bishwa Chandra Adhikari | Ketan Bhotkar | Ju Sung Kim | Sung Tae Yoo | Eun Ha Choi | Kyu Chang Park
Source: Nanomaterials (article, 2022-12-05)
Field: Materials Science — Materials Chemistry

Beam Trajectory Analysis of Vertically Aligned Carbon Nanotube Emitters with a Microchannel Plate Vertically aligned carbon nanotubes (CNTs) are essential to studying high current density, low dispersion, and high brightness. Vertically aligned 14 × 14 CNT emitters are fabricated as an island by sputter coating, photolithography, and the plasma-enhanced chemical vapor deposition process. Scanning electron microscopy is used to analyze the morphology structures with an average height of 40 µm. The field emission microscopy image is captured on the microchannel plate (MCP). The role of the microchannel plate is to determine how the high-density electron beam spot is measured under the variation of voltage and exposure time. The MCP enhances the field emission current near the threshold voltage and protects the CNT from irreversible damage during the vacuum arc. The high-density electron beam spot is measured with an FWHM of 2.71 mm under the variation of the applied voltage and the exposure time, respectively, which corresponds to the real beam spot. This configuration produces the beam trajectory with low dispersion under the proper field emission, which could be applicable to high-resolution multi-beam electron microscopy and high-resolution X-ray imaging technology. Microchannel plate detector ; Field electron emission ; Materials science ; Microchannel ; Carbon nanotube ; Optics ; Optoelectronics ; Scanning electron microscope ; Triode ; Nanotechnology ; Electron ; Voltage ; Composite material ; Physics Carbon Nanotubes in Composites ; Diamond and Carbon-based Materials Research ; Advanced Electron Microscopy Techniques and Applications
Authors: Yao Liu | Fu Qiao | Lele Xu | Runtao Wang | Wei Jiang | Zhen Xu
Source: Frontiers in Marine Science (article, 2022-06-09)
Field: Chemistry — Analytical Chemistry

Fast Detection of Diarrhetic Shellfish Poisoning Toxins in Mussels Using NIR Spectroscopy and Improved Twin Support Vector Machines Diarrhetic shellfish poisoning (DSP) toxins are potent marine biotoxins. It can cause a severe gastrointestinal illness by the consumption of mussels contaminated by DSP toxins. New methods for effectively and rapidly detecting DSP toxins-contaminated mussels are required. In this study, we used near-infrared (NIR) reflection spectroscopy combined with pattern recognition methods to detect DSP toxins. In the range of 950-1700 nm, the spectral data of healthy mussels and DSP toxins-contaminated mussels were acquired. To select optimal waveband subsets, a waveband selection algorithm with a Gaussian membership function based on fuzzy rough set theory was applied. Considering that detecting DSP toxins-contaminated mussels from healthy mussels was an imbalanced classification problem, an improved approach of twin support vector machines (TWSVM) was explored, which is based on a centered kernel alignment. The influences of parameters of the waveband selection algorithm and regularization hyperparameters of the improved TWSVM (ITWSVM) on the performance of models were analyzed. Compared to conventional SVM, TWSVM, and other state-of-the-art algorithms (such as multi-layer perceptron, extreme gradient boosting and adaptive boosting), our proposed model exhibited better performance in detecting DSP toxins and was little affected by the imbalance ratio. For the proposed model, the F-measure reached 0.9886, and detection accuracy reached 98.83%. We explored the physical basis for the detection model by analyzing the relationship between the occurrence of overtone and combination bands and selected wavebands. This study supports NIR spectroscopy as an innovative, rapid, and convenient analytical method to detect DSP toxins in mussels. Support vector machine ; Artificial intelligence ; Pattern recognition (psychology) ; Diarrhetic shellfish poisoning ; Mytilus ; Digital signal processing ; Computer science ; Hyperspectral imaging ; Shellfish ; Biology ; Ecology ; Fishery Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Deng Ying | Srinivas Addimulam
Source: Asia Pacific Journal of Energy and Environment (article, 2022-11-25)
Field: Materials Science — Biomaterials

Innovative Additives for Rubber: Improving Performance and Reducing Carbon Footprint This study investigates how to improve performance and lessen environmental effects by integrating novel compounds into rubber. The principal aims of this study are to evaluate the potential of bio-based additives, sophisticated nanomaterials, and intelligent features to enhance rubber's mechanical, thermal, and chemical properties while reducing carbon emissions. The research assesses recent developments and potential future directions through an extensive secondary data analysis. Important discoveries show that carbon nanotubes and graphene considerably improve durability and tensile strength, while bio-based additives lessen reliance on fossil fuels. The automotive sector benefits significantly from these additives' lightweight and increased energy efficiency. The report also emphasizes the necessity of sustainable end-of-life management and enhanced recyclability. The analysis highlights the significance of policy interventions despite the high costs and scaling issues associated with these materials. To encourage the use of sustainable additives, governments must fund R&amp;D, set precise guidelines, and promote recycling. The rubber sector may make great strides and contribute to industrial performance and environmental sustainability by addressing these constraints through supporting legislation. This study highlights how cutting-edge additives can revolutionize rubber technology in the future. Carbon footprint ; Natural rubber ; Footprint ; Carbon fibers ; Pulp and paper industry ; Business ; Environmental science ; Materials science ; Composite material ; Engineering ; Greenhouse gas ; Geology ; Composite number biodegradable polymer synthesis and properties ; Polymer Nanocomposites and Properties ; Natural Fiber Reinforced Composites
Authors: Chunkang Liu | Kun-Zhe Wu | Huan Gao | Jianyang Li | Xiaohua Xu
Source: Diabetes Metabolic Syndrome and Obesity (review, 2022-08-01)
Field: Materials Science — Biomaterials

Current Strategies and Potential Prospects for Nanoparticle-Mediated Treatment of Diabetic Nephropathy Diabetic nephropathy (DN), a severe microvascular complication of diabetes mellitus (DM), is the most common form of chronic kidney disease (CKD) and a leading cause of renal failure in end-stage renal disease. No currently available treatment can achieve complete cure. Traditional treatments have many limitations, such as painful subcutaneous insulin injections, nephrotoxicity and hepatotoxicity with oral medication, and poor patient compliance with continual medication intake. Given the known drawbacks, recent research has suggested that nanoparticle-based drug delivery platforms as therapeutics may provide a promising strategy for treating debilitating diseases such as DN in the future. This administration method provides multiple advantages, such as delivering the loaded drug to the precise target of action and enabling early prevention of CKD progression. This article discusses the development of the main currently used nanoplatforms, such as liposomes, polymeric NPs, and inorganic NPs, as well as the prospects and drawbacks of nanoplatform application in the treatment of CKD. Medicine ; Kidney disease ; Intensive care medicine ; Diabetes mellitus ; Diabetic nephropathy ; Drug delivery ; Nephropathy ; Nephrotoxicity ; Disease ; Drug ; Pharmacology ; Kidney ; Internal medicine ; Nanotechnology ; Endocrinology Nanoparticle-Based Drug Delivery ; Dialysis and Renal Disease Management ; Advanced Glycation End Products research
Authors: Yawen Wu | Saba Jasim Aljumaili | Dhiya Al‐Jumeily | Haiyi Bian
Source: Sensors (article, 2022-11-09)
Field: Chemistry — Analytical Chemistry

Prediction of the Nitrogen Content of Rice Leaf Using Multi-Spectral Images Based on Hybrid Radial Basis Function Neural Network and Partial Least-Squares Regression This paper's novel focus is predicting the leaf nitrogen content of rice during growing and maturing. A multispectral image processing-based prediction model of the Radial Basis Function Neural Network (RBFNN) model was proposed. Moreover, this paper depicted three primary points as the following: First, collect images of rice leaves (RL) from a controlled condition experimental laboratory and new shoot leaves in different stages in the visible light spectrum, and apply digital image processing technology to extract the color characteristics of RL and the morphological characteristics of the new shoot leaves. Secondly, the RBFNN model, the General Regression Model (GRL), and the General Regression Method (GRM) model were constructed based on the extracted image feature parameters and the nitrogen content of rice leaves. Third, the RBFNN is optimized by and Partial Least-Squares Regression (RBFNN-PLSR) model. Finally, the validation results show that the nitrogen content prediction models at growing and mature stages that the mean absolute error (<i>MAE</i>), the Mean Absolute Percentage Error (<i>MAPE</i>), and the Root Mean Square Error (<i>RMSE</i>) of the RFBNN model during the rice-growing stage and the mature stage are 0.6418 (%), 0.5399 (%), 0.0652 (%), and 0.3540 (%), 0.1566 (%), 0.0214 (%) respectively, the predicted value of the model fits well with the actual value. Finally, the model may be used to give the best foundation for achieving exact fertilization control by continuously monitoring the nitrogen nutrition status of rice. In addition, at the growing stage, the RBFNN model shows better results compared to both GRL and GRM, in which <i>MAE</i> is reduced by 0.2233% and 0.2785%, respectively. Partial least squares regression ; Radial basis function ; Regression ; Artificial neural network ; Regression analysis ; Nitrogen ; Content (measure theory) ; Pattern recognition (psychology) ; Function (biology) ; Basis (linear algebra) ; Statistics ; Biological system ; Mathematics ; Artificial intelligence ; Computer science ; Chemistry ; Biology ; Mathematical analysis Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing and Land Use
Authors: Hiroki Matsuo | Masashi Utsunomiya | Yuji Noguchi
Source: NPG Asia Materials (article, 2022-10-06)
Field: Materials Science — Materials Chemistry

Utilizing ferrorestorable polarization in energy-storage ceramic capacitors Abstract A self-powered system with a long lifetime would represent an opportunity in the development of a next-generation, standalone Internet of Things. Ceramic capacitors are promising candidates for energy storage components because of their stability and fast charge/discharge capabilities. However, even the energy density of state-of-the-art capacitors needs to be increased markedly for this application. Improving the breakdown electric field represents a potential solution, but operations at such high fields relying on unchanged dielectric permittivity sacrifice the lifetime of the capacitor to some degree. Here, we report ferrorestorable polarization engineering capable of more than doubling the effective permittivity. Our experiments and ab initio calculations demonstrate that a defect dipole composed of Cu 3+ and oxygen vacancy in a prototypical ferroelectric BaTiO 3 ceramic is coupled with spontaneous polarization. The resultant ferrorestorable polarization delivers an extraordinarily large effective relative permittivity, beyond 7000, with a high energy efficiency up to 89%. Our work paves the way to realizing efficient ceramic capacitors for self-powered applications. Capacitor ; Materials science ; Permittivity ; Ceramic ; Energy storage ; Dielectric ; Polarization (electrochemistry) ; Dipole ; Ceramic capacitor ; Optoelectronics ; Ferroelectricity ; Engineering physics ; Voltage ; Electrical engineering ; Composite material ; Physics ; Engineering Ferroelectric and Piezoelectric Materials ; Dielectric materials and actuators ; Advanced Sensor and Energy Harvesting Materials
Authors: Andressa Brito Lira | Gabrieli L. Parrilha | Gabriela Tafaela Dias | Fernanda Samara de Sousa Saraiva | Gabriel Corrêa Veríssimo | Rayane Siqueira de Sousa | Teresinha Gonçalves da Silva | Abrahão Alves de Oliveira Filho | Adriano Francisco Alves | Elaine M. Souza‐Fagundes | Heloísa Beraldo | Maria Aparecida Gomes | Margareth de Fátima Formiga Melo Diniz
Source: Oxidative Medicine and Cellular Longevity (article, 2022-01-01)
Field: Chemistry — Organic Chemistry

Evaluation of Toxicity and Oxidative Stress of 2‐Acetylpyridine‐<i>N</i>(4)‐orthochlorophenyl Thiosemicarbazone Thiosemicarbazones are well known for their broad spectrum of action, including antitumoral and antiparasitic activities. Thiosemicarbazones work as chelating binders, reacting with metal ions. The objective of this work was to investigate the <i>in silico</i>, <i>in vitro</i>, and <i>in vivo</i> toxicity and oxidative stress of 2-acetylpyridine-<i>N</i>(4)-orthochlorophenyl thiosemicarbazone (TSC01). The <i>in silico</i> prediction showed good absorption by biological membranes and no theoretical toxicity. Also, the compound did not show cytotoxicity against Hep-G2 and HT-29 cells. In the acute nonclinical toxicological test, the animals treated with TSC01 showed behavioral changes of stimulus of the central nervous system (CNS) at 300 mg/kg. One hour after administration, a dose of 2000 mg/kg caused depressive signs. All changes disappeared after 24 h, with no deaths, which suggest an estimated LD50 of 5000 mg/kg and GSH 5. The group treated with 2000 mg/kg had an increase of water consumption and weight gain in the second week. The biochemical parameters presented no toxicity relevance, and the analysis of oxidative stress in the liver found an increase of lipid peroxidation and nitric oxide. However, histopathological analysis showed organ integrity was maintained without any changes. In conclusion, the results show the low toxicological potential of thiosemicarbazone derivative, indicating future safe use. Toxicity ; Oxidative stress ; Pharmacology ; Chemistry ; Semicarbazone ; In vivo ; Acute toxicity ; Glutathione ; Lipid peroxidation ; Nitric oxide ; Toxicology ; Biochemistry ; Biology ; Stereochemistry ; Enzyme Synthesis and Characterization of Heterocyclic Compounds ; Synthesis and biological activity ; Quinazolinone synthesis and applications