jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sharmin Abdullah | Xiaowang Zhou | Rodolfo Aguirre | David Zubía
Source: Journal of Applied Physics (article, 2024-02-15)
Field: Materials Science — Materials Chemistry

Exploring poly-crystallization in semiconductors through assumption-less growth simulations: CdTe/CdS case study Crystal growth is a complex process with far-reaching implications for high-performance materials across various fields. Recent advancements in structural analysis methods such as polyhedral template matching, which allows semiconductor-specific analysis, coupled with simulation technology, have enabled the comprehensive study of crystallization dynamics in semiconductors. However, the exploration of polycrystalline semiconductors created with minimal external intervention of the crystallization processes is relatively uncharted in comparison with metals. In this study, we employ molecular dynamics to simulate the growth of polycrystalline CdTe/CdS with the assumptions of classical mechanics, a Stillinger–Weber potential, an amorphous substrate, and common vapor growth conditions to allow the polycrystalline structures to evolve naturally. Post-simulation, we identify and analyze impactful structures and events, comparing them to theory and experiment to gain insight into various modes of crystallization dynamics. Two research questions guided the study: (1) How realistic are assumption-less simulated polycrystalline semiconductor structures? (2) To what extent can the approach provide insight into crystallization? The simulations, performed with minimal external control, yield polycrystalline structures mirroring experimental findings. The analysis reveals key crystallization insights, such as the role of amorphous atoms in the transition from nucleation to grain growth and the transformative impact of single events, such as dislocations, on crystallization dynamics. The method paves the way for reproducing and analyzing realistic polycrystalline semiconductor structures with minimal simulation assumptions across various growth modes. Crystallization ; Crystallite ; Nucleation ; Semiconductor ; Materials science ; Cadmium telluride photovoltaics ; Crystal growth ; Amorphous solid ; Molecular dynamics ; Chemical physics ; Nanotechnology ; Engineering physics ; Crystallography ; Chemistry ; Optoelectronics ; Physics ; Thermodynamics ; Computational chemistry ; Metallurgy Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Solidification and crystal growth phenomena
Authors: Favour Emoshoriemhe Akpaibor | Rasheed Ahmed | Gregory Omoruyi | Nosa Godwin Agbonze | Jeffrey Ifechukwu Enem | Ikechukwu Bismarck Owunna
Source: World Journal of Advanced Research and Reviews (article, 2024-10-22)
Field: Chemistry — Analytical Chemistry

Innovations in residue upgrading for the Niger delta by transforming heavy oil fractions into high-value products: A state of the art review This review discusses new innovations in residue upgrading technologies for the conversion of heavy oil fractions into high-value products, especially for Delta and Rivers States of the Niger Delta region. Recent works within the 2020-2024 period show that upgrading methods have been significantly developed; however, no prior work has been done regarding applying those upgrading techniques to the peculiar nature of crude oil from this region. The paper probes the environmental impacts of these technologies, emphasizing the need for localized assessment that would take into consideration the fragile ecosystems of Delta and Rivers States. It further assesses the economic viability of scaling up the implementation of advanced upgrading processes within the current refining infrastructure. The discussion covers variable quality heavy oil in these regions and what that does to upgrading efficiency, how to integrate these technologies into the current refining practices, underlines the potential socio-economic advantages for the local communities through the creation of jobs and enhancing the skills of those communities to underscore the importance of these innovations for sustainable development. The review establishes that in such siamese twin areas, further research is needed to ensure that heavy oil resources in Delta and Rivers States are utilized effectively while ensuring that there is a minimal environmental impact from the extraction process. Niger delta ; Residue (chemistry) ; Value (mathematics) ; Pulp and paper industry ; Environmental science ; Chemistry ; Business ; Delta ; Engineering ; Mathematics ; Organic chemistry ; Statistics Petroleum Processing and Analysis ; Reservoir Engineering and Simulation Methods ; Global Energy and Sustainability Research
Authors: Uğur Sorgucu
Source: Çukurova Üniversitesi Mühendislik Fakültesi Dergisi (article, 2024-10-03)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Düşük Karbonlu St52 Çeliğinin Elektromanyetik Kalkanlama Potansiyeli: 4900-6000 MHz Frekans Aralığında Performans İncelemesi Elektromanyetik alanların hayatın her alanında yaygınlaşmasıyla elektromanyetik kalkanlama da önemi artan bir disiplin olmuştur. Mühendislik, fizik ve malzeme bilimi gibi çeşitli disiplinleri bir araya getiren çok disiplinli araştırma yönüyle ve hızla gelişen teknolojilerle birlikte elektromanyetik kalkanlama, elektronik cihazların ve sistemlerin güvenliği için kritik bir öneme sahip olmaya devam etmektedir. Bu makale kapsamında, çok geniş bir kullanım sahasına sahip olan düşük karbonlu ST52 çeliğinin elektromanyetik kalkanlama potansiyeli 4900-6000 MHz frekans aralığında değerlendirmektedir. ST52 çeliğinin kolay erişilebilir ve birçok emsaline göre fiyat/performans avantajları sebebiyle, elektromanyetik kalkanlama açısından kullanılabileceği sorusuyla başlayan bu çalışma sonucunda, ST52 çeliğinin 4900-6000 MHz frekans aralığında 40-60 dB arasında etkili bir elektromanyetik kalkanlama performansına sahip olduğu görülmüştür. Bu değerler, ASTM düzenlemeleri tarafından belirlenen 40 dB'lik elektromanyetik kalkanlama kriterini başarıyla karşılamaktadır. Elde edilen bulgular, literatürdeki benzer çalışmalardan farklı olarak ST52 çeliğinin geniş bir frekans aralığında güçlü bir performans sergilediğini göstermektedir. ST52 çeliğinin elektromanyetik kalkanlama potansiyeli, özellikle 4900-6000 MHz frekans aralığında diğer malzemelerden ayrışmaktadır. Bu çalışmadan elde edilen bilgiler, telekomünikasyon, savunma sanayi ve elektronik üretimi gibi sektörlerde güvenilir elektromanyetik kalkanlama çözümleri arayan profesyoneller için önemlidir. Physics ; Humanities ; Political science ; Philosophy Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; Electromagnetic Compatibility and Noise Suppression
Authors: Gustavo Bernardes da Silva | Viviane Rodrigues Botelho | Carla Diniz Lopes Becker | Cassiana Viccari | Thatiane A. Pianoschi
Source: Brazilian Journal of Radiation Sciences (article, 2024-04-17)
Field: Materials Science — Materials Chemistry

Modeling of the mass attenuation coefficients of X ray beams using deep neural networks (DNN) and NIST database Attenuation coefficients are essential physical parameters for many applications, such as the calculation of photon penetration and energy deposition to evaluate biological shielding. Estimating these parameters is complex, making it necessary to apply more sophisticated methodologies. The objective of the present study was to propose a model for estimating the attenuation coefficients using artificial neural networks. The NIST database was used to estimate the attenuation coefficients in terms of energy and atomic number from a regression problem using two approaches: the proposition of an automated model using the framework Talos and a manual model using Keras. The characteristics of the best model proposed in Talos were applied in manual training via Keras with cross-validation to evaluate the learning curves. The following were also assessed: the comparison of the curves of the attenuation coefficients predicted by the model compared with the reference data and the general comparison of the vectors X and y of the two models discussed. The Talos framework reference model obtained the following values ​​of Loss and MSE error metric: 0.13 and 0.037, respectively. The best model of the manual approach received the following results: 0.19 and 0.08 for the loss function and MSE error metric, respectively. The absolute percentage error (MAE) of the difference in the results between the two models was: 0.065 and 0.044 for the Loss and MSE metrics. Despite applying two distinct propositions, both models had the same difficulties in predicting discontinuities in the physical behavior associated with the attenuation coefficients. Attenuation ; NIST ; Mean squared error ; Artificial neural network ; Computer science ; Classification of discontinuities ; Metric (unit) ; Algorithm ; Approximation error ; Electromagnetic shielding ; Applied mathematics ; Statistics ; Mathematics ; Artificial intelligence ; Materials science ; Physics ; Mathematical analysis ; Optics Radiation Shielding Materials Analysis ; Radiation Dose and Imaging ; Advanced X-ray and CT Imaging
Authors: László Győry | Szilveszter Gergely | Pál Péter Hanzelik
Source: Journal of Chemometrics (article, 2024-05-29)
Field: Chemistry — Analytical Chemistry

Generating realistic infrared spectra using artificial neural networks Abstract Artificial spectra were generated to match the different acid solubility properties of the rocks. The purpose of generating artificial spectra was to increase the number of samples available for future data processing with a convolutional neural network. The samples were collected from different geological matrices during targeted rock tests to support industrial applications. The inherent characteristics of the samples are their uneven distribution in the parameter space of the features and their limited availability for data‐intensive studies. Both data set characteristics constrain the prediction performance of the machine learning methods to estimate the unknown solubility of samples in the chosen acids. If the sample multiplication techniques are performed without considering the relationship between solubility of samples and their infrared spectra, the synthetic samples adversely impact the efficacy of the prediction method. By utilizing a dimensionality reduction technique (principal component analysis) and a neural network, we established a relationship between the solubility of the samples and their infrared spectra. Infrared spectra of the samples used for learning the model could be efficiently reproduced and infrared spectra of created samples could be generated. The reliability of the applied method has been shown by the comparison of the original and artificial spectra through a mean Pearson correlation coefficient and by comparing the closest neighbors to each other. This method can be used to create new samples and their infrared spectra, where different constraints must be met and the samples must be connected to the infrared spectrum. Principal component analysis ; Artificial neural network ; Infrared spectroscopy ; Infrared ; Spectral line ; Solubility ; Artificial intelligence ; Pattern recognition (psychology) ; Dimensionality reduction ; Computer science ; Biological system ; Correlation coefficient ; Chemistry ; Machine learning ; Physics ; Optics ; Physical chemistry Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Maziar Bahreini | Roozbeh Sabetvand
Source: Research Square (preprint, 2024-12-18)
Field: Materials Science — Biomaterials

Molecular Dynamics Simulation of the Atropine Drug Encapsulation inside Protein Origami Icosahedral Nanocages in Physiological Environment Nanocages ; Icosahedral symmetry ; Molecular dynamics ; Drug delivery ; Materials science ; Encapsulation (networking) ; Nanotechnology ; Computer science ; Chemistry ; Computational chemistry ; Crystallography Supramolecular Self-Assembly in Materials ; Graphene and Nanomaterials Applications ; Protein Structure and Dynamics
Authors: А. М. Айтуғанова | Abduvali Turdiboyev
Source: ТЕХНИКА ҒЫЛЫМДАРЫ ЖӘНЕ ТЕХНОЛОГИЯ (article, 2024-01-01)
Field: Chemistry — Electrochemistry

ELECTROCHEMICAL METHODS FOR WASTEWATER TREATMENT: THEORETICAL FOUNDATIONS AND APPLICATION EFFICIENCY Су – бұл адамның әл-ауқатын және Жер экожүйелерінің әртүрлілігін сақтау үшін алмастырылмайтын ресурс. Әртүрлі антропогендік қызмет түрлері, оның ішінде ауыл шаруашылығы, мал шаруашылығы, өндірістік процестер, энергия өндірісі және күнделікті тұрмыстық міндеттер, көбінесе белгілі бір сапа стандарттарына сәйкес келетін суға тәуелді. Жердегі су ресурстарының жалпы көлемі 1,4 миллиард текше километрді құраса да, олардың тек 0,5% ғана тұщы және оңай қол жетімді. Алайда, адамның қызметі табиғи су айналымын айтарлықтай бұзды, бұл судың сапасы мен саны жағынан жетіспеушілікке әкелді. Осылайша, қазіргі уақытта әлем халқының шамамен екі үштен бірі судың жетіспеушілігімен кездесуде, ал болжамдар бойынша 2030 жылға қарай жылдық суға деген сұраныс ұсыныстан 40% артық болады. Әлемде жыл сайын адам қажеттіліктерін қанағаттандыру үшін жеткілікті тұщы су болса да, суға деген қолжетімділік пен сұраныс арасындағы аймақтық және уақытша айырмашылықтар әлемнің әртүрлі бөліктерінде әртүрлі уақытта су жетіспеушілігін тудырады. Сондықтан су ресурстарын тұрақты пайдалану мен тұтынуға бағытталған тиімді тазарту әдістерін әзірлеу, су ресурстарының сарқылуы байқалатын аймақтарда ағынды суларды қайта пайдалану мәселелерін шешу, сондай-ақ ағынды суларды төгу мәселелерін шешу өте маңызды. Wastewater ; Electrochemistry ; Sewage treatment ; Computer science ; Process engineering ; Biochemical engineering ; Environmental science ; Environmental engineering ; Chemistry ; Engineering ; Electrode Electrochemical Analysis and Applications ; Membrane-based Ion Separation Techniques
Authors: Muhammad Bakrie | Muhrinsyah Fatimura | Rully Masriatini
Source: American Journal of Innovation in Science and Engineering (article, 2024-04-22)
Field: Materials Science — Polymers and Plastics

Simple Measurement of Conductivity of Colored Acrylic Sheets In many applications, colored acrylic sheets require information on thermal conductivity values. However, thermal conductivity data has not been found in the literature and research publications, especially colored acrylic sheets. The purpose of this study was to investigate the heat conductivity value of colored acrylic sheets including transparent, cloudy, white, black, green and blue colors found in the market. This research was done with the experimental method of measuring the thermal conductivity of colored acrylic in a closed room four rectangles 80 cm x 40 cm x 40cm of 9 mm plywood coated with black paper and divided into two compartments and test material 40 cm x 40 cm x 0.3cm as patisi room. The heat source used is a 75watt incandescent lamp placed on one side of the room. Acrylic thermal conductivity is calculated based on temperature data at each measurement point reaching a steady state which is obtained at the 30th minute and taking into account the convection heat and air radiation in the test chamber. The results showed that pigment additives greatly affect the thermal conductivity value of acrylic and its value is lower than the conductivity value of acrylic colorless sheet transfaran. Colored ; Simple (philosophy) ; Conductivity ; Materials science ; Biological system ; Composite material ; Chemistry ; Philosophy ; Biology ; Physical chemistry Textile materials and evaluations
Authors: Thanh Nhan Cao | Phạm Văn Tất | Minh Quang Nguyen
Source: Tập san Khoa học và kỹ thuật trường Đại học Bình Dương (article, 2024-01-03)
Field: Chemistry — Organic Chemistry

In silico study for discovering novel thiazole derivatives as anti-breast cancer agents (MCF-7) The work validated the pharmacokinetic characteristics and docking approach, and discovered novel thiazole compounds with MCF-7 breast anti-cancer efficacy using quantitative structure-activity relationships (QSAR) models. Using an experimental dataset of 53 thiazole derivatives with IC50 values, QSAR models were developed using multivariate linear regression (QSARMLR) and artificial neural networks (QSARANN). Eight descriptions, with statistical values of R2train = 0.875 and Q2LOO = 0.834, comprised the successfully developed QSARMLR model. Based on the descriptors of the QSARMLR model, which has statistical values of R2 = 0.918, Q2test = 0.934, and Q2CV = 0.916, the QSARANN neural network model with the architectural network of I(8)-HL(9)-O(1) has also been constructed. Using the AD and outliers analysis, the models were utilized to forecast 120 new design derivatives based on the thiazole framework, and the IC50 values of 10 new thiazole derivatives were determined. Additionally, the derivatives were assessed for resistance to estrogen-positive breast cancer by docking them onto the Polo-like kinases (Plk1) receptor and screening them for pharmacokinetic features in accordance with Lipinski and Ghose guidelines. Consequently, it was discovered that the thiazole TAZ5 had promising derivative activity against the primary MCF-7 breast cancer cell line. MCF-7 ; In silico ; Thiazole ; Cancer ; Breast cancer ; Computational biology ; Biology ; Medicine ; Chemistry ; Human breast ; Internal medicine ; Stereochemistry ; Gene ; Biochemistry Synthesis and biological activity ; Computational Drug Discovery Methods
Authors: Wenny Surya Murtius | Bambang Dwi Argo | Irnia Nurika | Sukardi Sukardi
Source: Journal of Applied Agricultural Science and Technology (article, 2024-02-24)
Field: Chemistry — Inorganic Chemistry

Identification of Availability and Lignocellulosic Properties in Coconut Dregs Waste Agricultural waste, including coconut pulp, contains lignocellulose and is a very important, renewable and sustainable industrial raw material. Many of the food, textile, pharmaceutical, paint and resin, agrochemical, oil processing, and other sectors utilize lignocellulosic derivatives. The objectives of this study were to determine the availability of coconut pulp in Padang City-West Sumatra, analyse the lignocellulosic components contained and cell surface morphology, and observe the chemical elements in coconut pulp waste. An exploratory approach was used in this study to achieve these objectives. The results showed that there were 98 coconut milk entrepreneurs spread across traditional markets in Padang City, West Sumatra. Every day the coconut milk squeeze business examined produces ± 1.18 tonnes of coconut pulp. Coconut waste also contains 47.18% cellulose, 10.58% lignin, and 12.10% hemicellulose. Based on the XRD results, the crystal size of coconut pulp obtained from XRD observation is 11.8 nm. Identification (biology) ; Pulp and paper industry ; Waste management ; Coconut oil ; Biotechnology ; Environmental science ; Chemistry ; Food science ; Biology ; Engineering ; Botany Coconut Research and Applications ; Biofuel production and bioconversion ; Agricultural and Food Sciences
Authors: Khalid Achbab Gueriguer
Source: e_Buah (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Desarrollo de una base de datos para aplicaciones de aprendizaje automático en la producción de hidrógeno En el presente proyecto se desarrolla una base de datos que recopila información sobre diversas propiedades de una amplia gama de compuestos de tipo perovskita. El objetivo principal de esta recopilación de datos es servir como insumo para entrenar algoritmos de aprendizaje automático, con el fin de predecir aquellos materiales de tipo perovskita que presenten las características óptimas para llevar a cabo eficientemente la conversión termoquímica de energía solar en combustibles renovables. Linea ; Base (topology) ; Principal component analysis ; Work (physics) Advancements in Solid Oxide Fuel Cells ; Machine Learning in Materials Science ; Solar-Powered Water Purification Methods
Authors: Rıfat Yakut
Source: European Mechanical Science (article, 2024-07-30)
Field: Materials Science — Materials Chemistry

The effect of niobium carbide coating on wear behavior of grey cast iron via thermo-reactive diffusion process Wear is the limit for grey cast iron (GCI), which is utilized extensively in today’s industries. Coating the surface of a material can enhance its ability to withstand wear. In this study, thermo-reactive diffusion (TRD) process was used to coat the surface of grey cast iron with niobium carbide (NbC). The coatings were applied for 2, 4 and 6 hours at 950ºC and 1050ºC. The coated samples were subjected to metallographic examination to investigate the microstructure of the coating zone. For this purpose, optical microscopy examinations were carried out. Microhardness tests were carried out to assess the mechanical properties of the samples. The coated surfaces were analyzed using energy-dispersive X-ray spectrometry (EDS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Wear tests were carried out on the coated surfaces to measure the volumetric wear loss, the wear rate and the changes in the coefficient of friction. Coating thickness rose as furnace waiting time increased, according to optical microstructures of coated surfaces. The hardness of the coated surfaces increased with a longer coating duration. Depending on the duration and temperature of the coating process, the layer thickness ranged from 6 to 52 µm. The lowest microhardness and the highest microhardness values of the coatings were determined at 950ºC for 2 hours and at 950ºC for 6 hours, respectively. Compared to the uncoated samples, the coated samples had a 6-9 times higher hardness value. In the abrasion tests, the loss of wear volume increased with increase in load. Materials science ; Indentation hardness ; Coating ; Microstructure ; Scanning electron microscope ; Niobium carbide ; Metallurgy ; Abrasion (mechanical) ; Optical microscope ; Cast iron ; Niobium ; Carbide ; Composite material ; Diffusion Metal Alloys Wear and Properties ; Metal and Thin Film Mechanics ; Advanced materials and composites
Authors: N. Smirnov | Elizaveta A. Krivko | Daria A. Moskaleva | Dmitry O. Moskalev | Anna Solovieva | Vladimir V. Echeistov | E. V. Zikiy | N. D. Korshakov | А. С. Иванов | Elizaveta I. Malevannaya | Aleksei R. Matanin | Victor I. Polozov | M. Teleganov | Nikolai M. Zhitkov | Ruslan V. Romashkin | Igor S. Korobenko | A. V. Yanilkin | A. Lebedev | Ilya A. Ryzhikov | A. V. Andriyash | Ilya A. Rodionov
Source: arXiv (Cornell University) (preprint, 2024-08-19)
Field: Materials Science — Materials Chemistry

Angstrom-scale ion-beam engineering of ultrathin buried oxides for quantum and neuro-inspired computing Multilayer nanoscale systems incorporating buried ultrathin tunnel oxides, 2D materials, and solid electrolytes are crucial for next-generation logics, memory, quantum and neuro-inspired computing. Still, an ultrathin layer control at angstrom scale is challenging for cutting-edge applications. Here we introduce a scalable approach utilizing focused ion-beam annealing for buried ultrathin oxides engineering with angstrom-scale thickness control. Our molecular dynamics simulations of Ne+ irradiation on Al/a-AlOx/Al structure confirms the pivotal role of ion generated crystal defects. We experimentally demonstrate its performance on Josephson junction tunning in the resistance range of 2 to 37% with a standard deviation of 0.86% across 25x25 mm chip. Moreover, we showcase +-17 MHz frequency control (+-0.172 A tunnel barrier thickness) for superconducting transmon qubits with coherence times up to 500 us, which is promising for useful fault-tolerant quantum computing. This work ensures ultrathin multilayer nanosystems engineering at the ultimate scale by depth-controlled crystal defects generation. Angstrom ; Scale (ratio) ; Ion ; Quantum ; Ion beam ; Beam (structure) ; Materials science ; Nanotechnology ; Engineering physics ; Computer science ; Physics ; Optics ; Chemistry ; Quantum mechanics ; Crystallography Diamond and Carbon-based Materials Research ; Electronic and Structural Properties of Oxides ; Ion-surface interactions and analysis