jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Byungki Ryu | Jaywan Chung | Masaya Kumagai | Tomoya Mato | Yukio Ando | Sakiko Gunji | Atsumi Tanaka | Dewi Yana | Masayuki Fujimoto | Y. Imai | Yukari Katsura | Su-Dong Park
Source: arXiv (Cornell University) (preprint, 2022-10-17)
Field: Materials Science — Materials Chemistry

Best Thermoelectric Efficiency of Ever-Explored Materials A thermoelectric device is a heat engine that directly converts heat into electricity. Many materials with a high figure of merit ZT have been discovered in anticipation of a high thermoelectric efficiency. However, there has been a lack of investigations on efficiency-based material evaluation, and little is known about the achievable limit of thermoelectric efficiency. Here, we report the highest thermoelectric efficiency using 12,645 published materials. The 97,841,810 thermoelectric efficiencies are calculated using 808,610 device configurations under various heat-source temperatures (T_h) when the cold-side temperature is 300 K, solving one-dimensional thermoelectric integral equations with temperature-dependent thermoelectric properties. For infinite-cascade devices, a thermoelectric efficiency larger than 33% (~1/3) is achievable when T_h exceeds 1400 K. For single-stage devices, the best efficiency of 17.1% (~1/6) is possible when T_h is 860 K. Leg segmentation can overcome this limit, delivering a very high efficiency of 24% (~1/4) when T_h is 1100 K. Thermoelectric effect ; Thermoelectric materials ; Thermoelectric generator ; Materials science ; Thermoelectric cooling ; Cascade ; Energy conversion efficiency ; Engineering physics ; Waste heat ; Limit (mathematics) ; Figure of merit ; Optoelectronics ; Thermodynamics ; Physics ; Mathematics ; Engineering ; Chemical engineering Advanced Thermoelectric Materials and Devices ; Advanced Thermodynamics and Statistical Mechanics ; Machine Learning in Materials Science
Authors: Yasmina Sebbane | A. Boubakeur | A. Mekhaldi
Source: ENP Engineering Science Journal (article, 2022-07-29)
Field: Materials Science — Materials Chemistry

Correlations between physico-chemical properties and dielectric behavior of thermally aged XLPE cables insulation The carried out investigations aim at clarifying the correlations between physico-chemical properties and the variation of dielectric losses of Cross-Linked Polyethylene (XLPE) as Medium Voltage cable insulation during thermal aging. The used cables were manufactured by ELSEWEDY CABLES. They have been installed in Algeria where they must resist high temperatures that could exceed 50 degrees in the south of the country. For this aim, thermal aging measurements were performed on XLPE cables samples at 80, 100 and 140 °C for aging time of 5000 hours. The chemical properties were evaluated through Fourier Transform Infrared Spectrum (FTIR). In addition, the effect of aging on the crystallinity ratio, the lamellar thickness and the melting peak temperature was assessed using Differential Scanning Calorimetry (DSC). Frequency domain dielectric spectroscopy has been conducted on the aged XLPE cables in order to study the evolution of the dielectric losses. The obtained results showed that the principal aging mechanism is thermal oxidation which heads to deteriorate the morphology and increase both the polarization and losses, principally at low frequencies. It has been found that the color changes caused by the chains scission indicate the increase of interfaces between the cable insulating and semi-conductive layers, which could head to increase the dielectric losses due to the interfacial polarization. Materials science ; Crystallinity ; Composite material ; Dielectric ; Fourier transform infrared spectroscopy ; Polyethylene ; Differential scanning calorimetry ; Cross-linked polyethylene ; Dielectric loss ; Accelerated aging ; Optics High voltage insulation and dielectric phenomena
Authors: Qingzu He | Chuan‐Qi Zhong | Xiang Li | Huan Guo | Yiming Li | Mingxuan Gao | Rongshan Yu | Xianming Liu | Fangfei Zhang | Tiannan Guo | Donghui Guo | Fangfu Ye | Jianwei Shuai | Jiahuai Han
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-08-29)
Field: Chemistry — Spectroscopy

Dear-DIA <sup>XMBD</sup> : deep autoencoder for data-independent acquisition proteomics Abstract Data-independent acquisition (DIA) technology for protein identification from mass spectrometry and related algorithms is developing rapidly. The spectrum-centric analysis of DIA data without the use of spectra library from data-dependent acquisition (DDA) data represents a promising direction. In this paper, we proposed an untargeted analysis method, Dear-DIA XMBD , for direct analysis of DIA data. Dear-DIA XMBD first integrates the deep variational autoencoder and triplet loss to learn the representations of the extracted fragment ion chromatograms, then uses the k-means clustering algorithm to aggregate fragments with similar representations into the same classes, and finally establishes the inverted index tables to determine the precursors of fragment clusters between precursors and peptides, and between fragments and peptides. We show that Dear-DIA XMBD performs superiorly with the highly complicated DIA data of different species obtained by different instrument platforms. Dear-DIA XMBD is publicly available at https://github.com/jianweishuai/Dear-DIA-XMBD . Autoencoder ; Computer science ; Cluster analysis ; Fragment (logic) ; Mass spectrometry ; Artificial intelligence ; Data acquisition ; Pattern recognition (psychology) ; Chemistry ; Data mining ; Algorithm ; Deep learning ; Chromatography Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: David Moss
Source: Research Square (preprint, 2022-04-18)
Field: Materials Science — Materials Chemistry

Ultrafast Carrier Dynamics in 2D NbTe2 Films Abstract As one of the representatives of emerging metallic transition metal dichalcogenides, niobium ditelluride (NbTe 2 ) has attracted intensive interest recently due to its distorted lattice structure and unique physical properties. Here, we report on the ultrafast carrier dynamics in NbTe 2 measured using time-resolved pump-probe transient reflection spectroscopy. A thickness-dependent carrier relaxation time is observed, exhibiting a clear increase in the fast and slow carrier decay rates for thin NbTe 2 flakes. In addition, pump power dependent measurements indicate that the carrier relaxation rates are power-independent, with the peak amplitude of the transient reflectivity increasing linearly with pump power. Isotropic relaxation dynamics in NbTe 2 is also verified by performing polarization-resolved pump-probe measurements. These results provide an insight into the light-matter interactions and charge carrier dynamics in NbTe 2 and will pave the way for its applications to photonic and optoelectronic devices. Ultrashort pulse ; Charge carrier ; Materials science ; Relaxation (psychology) ; Optoelectronics ; Carrier scattering ; Isotropy ; Spectroscopy ; Amplitude ; Carrier lifetime ; Photonics ; Condensed matter physics ; Optics ; Laser ; Scattering ; Physics ; Silicon 2D Materials and Applications ; Nanowire Synthesis and Applications ; Semiconductor Quantum Structures and Devices
Authors: Abdullah Tahir Şensoy
Source: Open Chemistry (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Numerical simulation and mathematical modeling of the casting process for pearlitic spheroidal graphite cast iron Abstract Fluidity, an essential parameter in casting operations, is influenced by the thermal properties of the alloy and the mold, pouring temperature, modification, and inoculation of the alloy. In this work, pearlitic spheroidal graphite cast iron (PSGI) was studied in terms of fluidity characteristics. The sand mold used had different section thicknesses. The alloy was cast at pouring temperatures changing between 1,360–1,480°C. Liquid metal quality ranged between 10 and 90% where the section thickness was changed from 1 to 5 mm. FlowCast simulation tool was used for the modeling of the tests. The analysis of variance results of the response surface model constructed between certain casting parameters and fluidity length have shown that the reduced regression equation is very accurate in terms of statistical indicators (predicted R 2 : 0.99). The sensitivity analysis has shown that the section thickness is the most dominant parameter on the fluidity, while metallurgical quality is the least. The proposed model was also compared with the studies in the literature and it was seen that the results are well-matched. Therefore, it was suggested to use the proposed equation in order to estimate the fluidity results of PSGI without the need for real casting operations. Cast iron ; Casting ; Graphite ; Mold ; Materials science ; Alloy ; Metallurgy ; Composite material Graphite, nuclear technology, radiation studies ; Metallurgical Processes and Thermodynamics ; Coal Combustion and Slurry Processing
Authors: Chibuike Ernest Ikwuka | Chukwuebuka Moses Asogwa | Ozioma Jennifer Ikwuka | Jude E. Ogbonna | Chinwe Mercy Onah | Christian Chukwuagozie Ohama | Charles O. Nnadi
Source: Journal of Pharmaceutical Research International (article, 2022-09-08)
Field: Chemistry — Organic Chemistry

Insights into the In-vivo Antiplasmodial Activity of Trisdimethylamino Pyrimidine Derivative in Plasmodium berghei: Infected Mouse Model Aims: To evaluate the antiplasmodial activity of a trisdimethylamino pyrimidine derivative synthesized by indirect methylation of p-nitrophenylacetic acid via a substituted amine or amide derivative against Plasmodium berghei NK65 strain in an in vivo Plasmodium berghei-Infected mouse model.&#x0D; Methodology: Plasmodium berghei-parasitized suppressive model in Albino mice was adopted for the antiplasmodial activity evaluation. The schizontocidal activity of the compound was evaluated by a 4-day suppressive test. All the treatments (test sample, standard control and blank) were administered intraperitoneally to the mice. Parameters such as rectal temperature, packed cell volume, survival time and parasitemia were measured.&#x0D; Results: The 10, 20 and 40 mg/kg doses of 2, 4, 6-trisdimethylamino-5-(4´-nitrophenyl) pyrimidine elicited a statistically significant reduction (p &lt; 0.01) in parasitemia level in treated mice. The 40 mg/kg dose caused 97.19% suppression of parasitemia and a mean survival time of 22 days compared with 97.64% and 24 days respectively in the standard control group (artemether-lumefantrine combination, 5 mg/kg). All the treatments restored the packed cell volume to the baseline (~39.8%). A dose-dependent decrease in the rectal temperature was observed in all the treatment groups. However, only the 10 and 20 mg/kg doses of 2, 4, 6-trisdimethylamino-5-(4´-nitrophenyl) pyrimidine caused a significant decrease (p &lt; 0.01) compared with the control.&#x0D; Conclusion: The strong suppression of Plasmodium berghei in the mice treated with 2, 4, 6-trisdimethylamino-5-(4´-nitrophenyl) pyrimidine has further provided insights into the potential of the compound as a lead in the discovery of antimalarial agents. Plasmodium berghei ; Parasitemia ; In vivo ; Pharmacology ; Pyrimidine ; Chemistry ; Biology ; Biochemistry ; Immunology ; Plasmodium falciparum ; Malaria Synthesis and Characterization of Heterocyclic Compounds ; Quinazolinone synthesis and applications ; Synthesis and biological activity
Authors: Saud S. Alotaibi
Source: Intelligent Automation & Soft Computing (article, 2022-07-19)
Field: Chemistry — Analytical Chemistry

Germination Quality Prognosis: Classifying Spectroscopic Images of the Seed Samples One of the most critical objectives of precision farming is to assess the germination quality of seeds. Modern models contribute to this field primarily through the use of artificial intelligence techniques such as machine learning, which present difficulties in feature extraction and optimization, which are critical factors in predicting accuracy with few false alarms, and another significant difficulty is assessing germination quality. Additionally, the majority of these contributions make use of benchmark classification methods that are either inept or too complex to train with the supplied features. This manuscript addressed these issues by introducing a novel ensemble classification strategy dubbed “Assessing Germination Quality of Seed Samples (AGQSS) by Adaptive Boosting Ensemble Classification” that learns from quantitative phase features as well as universal features in greyscale spectroscopic images. The experimental inquiry illustrates the significance of the proposed model, which outperformed the currently available models when performance analysis was performed. Computer science ; Artificial intelligence ; Boosting (machine learning) ; Germination ; Machine learning ; Benchmark (surveying) ; Pattern recognition (psychology) ; Grayscale ; Field (mathematics) ; Quality (philosophy) ; Feature extraction ; Pixel ; Mathematics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Agricultural Engineering and Mechanization
Authors: Sergey Korchagin | Ekaterina Romanova | П. В. Никитин | Denis Serdechnyy | K. V. Bublikov | Irina Bystrenina
Source: Mathematics (article, 2022-02-15)
Field: Materials Science — General Materials Science

Mathematical Modeling of Dielectric Permeability and Volt-Ampere Characteristics of a Semiconductor Nanocomposite Conglomerate Mathematical computer models of the permittivity of silicon-based nanostructures upon interaction with electromagnetic radiation in a wide frequency range have been developed. To implement computer models for studying the electrophysical properties of the structures under study, algorithms and a set of programs have been developed. The results of the study of materials will not only provide fundamental information about the physical effects occurring in composite nanostructures but will also be useful for solving problems related to calculations for given electrophysical problems. For a nanocomposite based on ceramics and semiconductor oxides of zinc grains, resonant bursts of permittivity are observed within a wavelength of 300–400 nm; it has been found that this is due to the presence of electronic polarization of the nanocomposite core. The paper presents the results of modeling the current-voltage characteristics of a nanocomposite based on ceramics and semiconductor grains of zinc oxide. The obtained results show that the geometrical parameters, such as the number of layers and sample width, affect the CVC of the nanocomposite, and the operating point of the CVC shifts. This may be of interest in the development of materials with desired electrical characteristics for the creation of varistors. Nanocomposite ; Materials science ; Semiconductor ; Dielectric ; Permittivity ; Silicon ; Ceramic ; Engineering physics ; Optoelectronics ; Relative permittivity ; Electronic engineering ; Composite material ; Nanotechnology ; Physics ; Engineering Material Properties and Applications ; Structural mechanics and materials ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry
Authors: Tarun Chaudhary | Bhawani Datt Joshi
Source: Journal of Institute of Science and Technology (article, 2022-06-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Electronic, Thermodynamic Properties, Nonlinear Optical Responses, and Molecular Docking Studies on Cephalexin The topology analysis of electron localization function (ELF), localized orbital locator (LOL), the study of nonlinear optical properties, thermal properties, and biological activities of cephalexin have been performed using DFT/B3LYP and employing 6-311++G(d,p) basis sets. The Mulliken atomic charge on atoms has been calculated. The quantities describing nonlinear optical (NLO) properties like molecular polarizability (α), first hyperpolarizability (β), and second hyperpolarizability (γ) were comparable to the values of urea. The computed value of the second hyperpolarizability was found to be negative, which is an important feature for the system of controllable NLO devices. The thermodynamic properties like heat capacity (S), enthalpy (H), and entropy (S) are positively correlated with the temperature. Further, the title molecule shows good potentiality for binding with the selected target protein matrix metalloproteinase-2. Hyperpolarizability ; Polarizability ; Chemistry ; Enthalpy ; Heat capacity ; Computational chemistry ; Mulliken population analysis ; Nonlinear optical ; Molecule ; Thermodynamics ; Materials science ; Nonlinear system ; Density functional theory ; Physics ; Quantum mechanics ; Organic chemistry Nonlinear Optical Materials Research ; Metal complexes synthesis and properties ; Synthesis and biological activity
Authors: YI Qian | LIU Yijun | ZHUO Junkang | LI Congbo | YI Shuping
Source: Journal of Mechanical Engineering (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

BRBP-MOSOA Hybrid Data-driven Optimization Method for Low Carbon Heat Treatment Process 摘要： 热处理工艺数据蕴含企业长期运行的经验，可揭示工艺条件、参数与碳排放量的关联关系，但实际生产中常常被割裂放置，为此，提出一种基于历史工艺数据集的BRBP-MOSOA融合数据驱动方法实现热处理工艺参数优化以降低碳排放量。构建热处理工艺历史数据库；根据热处理工艺的碳排放运行特点识别碳排放源，构建碳排放模型；用历史数据集训练BRBP神经网络建立热处理工艺参数与硬度、碳排放之间的关系模型，实现对特定工艺条件下碳排放和硬度的预测；利用MOSOA算法建立工艺过程低碳优化模型，通过碳效率评估，输出满足低碳排放量的最优热处理工艺参数。案例研究表明所提方法可提升热处理综合碳效率6.57%，为热处理工艺的低碳运行提供了一种使能工具。 Process (computing) ; Carbon fibers ; Process engineering ; Materials science ; Computer science ; Algorithm ; Engineering ; Composite number Catalytic Processes in Materials Science ; Advanced Control Systems Optimization ; Radiative Heat Transfer Studies
Authors: Daniyal Nazir
Source: Quaid-e-Awam University Research Journal of Engineering Science & Technology (article, 2022-12-28)
Field: Chemistry — Analytical Chemistry

Meta-Analysis of Machine Learning Methods for Fruit Quality Prediction Considering the intentions towards diminishing fruit spoilage and the rising need for fruit spoilage detections; many of the models have been suggested which has been possible with the current rise of machine intelligence and computer vision. Nonetheless, the effectiveness of these suggested models is controversial once disclosed to unseen datasets and their adaptability is unsure when faced with diverse fruit types. The benefaction of this paper is to identify the ideal model for classifying defective fruits using a unified dataset and modifications to the existing models for better fruit spoilage detection for real-life implementations. Machine learning models like Support Vector Machine (SVM), Artificial Neural Networks (ANNs), and Convolutional Neural Networks (CNNs) are examined and fairly trained along with their processing phases, whereas their performances were estimated and analyzed in both binary and multiclass classification issues. Consequently, after the proposed modifications CNN-based models are the perfect solution. The suggested modifications to the CNN architecture improve the classification accuracy, precision, recall, and F1 score metrics. The experiment results show that the CNN1 ¬method outperformed the other four state-of-art compared models in the prediction of fruit quality. Artificial intelligence ; Machine learning ; Computer science ; Convolutional neural network ; Support vector machine ; Implementation ; Artificial neural network ; Food spoilage ; Adaptability ; Binary classification ; Precision and recall ; Quality (philosophy) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Postharvest Quality and Shelf Life Management
Source: Journal of Food Chemistry and Nanotechnology (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Morula Leaf Extract Mediated Synthesis of Silver Nanoparticles and their Application in the Analysis of SCN− Based on Inhibition of the Nanozyme Activity on 3,3’,5,5’-Tetramethylbenzidine (TMB) by the Silver Nanoparticles Oratile Semong and Bareki Shima Batlokwa The monitoring of thiocyanate (SCN−) in food is of consumer health and safety relevance. In this work, a colorimetric method for the detection of SCN− in milk using a silver nanoparticles (AgNPs) nanozyme is presented. Chemistry ; Nanoparticle ; Silver nanoparticle ; Nuclear chemistry ; Combinatorial chemistry ; Nanotechnology ; Materials science Advanced Nanomaterials in Catalysis ; Biosensors and Analytical Detection
Authors: Zeliang Liu | Huijian Li | Xiao Yang | Wei Luo
Source: Materials Today Communications (article, 2022-10-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Quadruple perovskite CaCu3Fe2Re2O12: A potential actuator based on a multiscale model In this study, the magnetic structure of CaCu3Fe2Re2O12 is analyzed combined on a macro to micro-scale. To combine first-principles calculations and finite element methods, the magnetic properties, Young's modulus and Poisson's ratio are used as input parameters in the finite element methods calculations. As a function of applied magnetic field and actuator structure, the energy loss and magnetostrictive coefficient of an magnetostrictive actuator are identified. When the voltage and frequency are specified, a small bar radius and narrow air gap are preferred for a high magnetostrictive coefficient. The total range of simulation parameters results in a large magnetostrictive coefficient of 2700 ppm, which is higher than the one for Tb-Dy-Fe alloys. According to our results, CaCu3Fe2Re2O12 can be designed to be used as actuators by controlling the structures and applying magnetic fields. Magnetostriction ; Materials science ; Finite element method ; Actuator ; Voltage ; Magnetic field ; RADIUS ; Poisson's ratio ; Condensed matter physics ; Bar (unit) ; Modulus ; Mechanics ; Poisson distribution ; Composite material ; Electrical engineering ; Thermodynamics ; Computer science ; Physics Magnetic and transport properties of perovskites and related materials ; Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials
Authors: Han Chen | Shen Lei | Ruoan Ren | Xu Han | Yanbing Liu
Source: Fibres and Textiles in Eastern Europe (article, 2022-07-01)
Field: Materials Science — Polymers and Plastics

Research and Design of Smart Care-Giving Clothing for Disabled Elderly Abstract In current society, smart clothing technology has become a critical way to improve the life quality of the elderly. This work conducted a category product evaluation and user demand system through the bibliometrics method, product evaluation analysis, focus group interviews and questionnaires. Based on the system, we designed smart clothing from the aspects of the clothing structure, hardware, software program and intelligent terminal platform to meet the needs of disabled elderly people and their caregivers in multiple scenarios. According to the test results of the smart clothing, the average error of temperature and humidity monitoring is 0.20°C and 2.88%RH. The time of putting on-taking off clothing in 6 representative daily scenarios was reduced by 51.67%. The daily body checking times, uncomfortable behaviours, and the anxiety of caregivers was decreased by 42.31%, 28.52% and 74.37%. Compared with ordinary clothing, six of the eight comfort performances are basically the same, and two are slightly worse. Clothing ; Product (mathematics) ; Architectural engineering ; Work (physics) ; Test (biology) ; Applied psychology ; Engineering ; Computer science ; Psychology ; Mathematics Textile materials and evaluations ; Color perception and design ; Digital Media and Visual Art