jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fredy Mamani Gonzalo | Maurício J. Piotrowski | Elvira Delgado | Carlos Armando Polo Bravo | Jesús Alfredo Chacaltana García | Jorge S. Ayala-Arenas | Efrácio Mamani Flores
Source: Scientific Reports (article, 2024-11-05)
Field: Materials Science — Materials Chemistry

Thermoelectric properties of XX- and XY-stacked GeS/GeSe van der Waals heterostructures from DFT and BTP calculations This study utilizes density functional theory (DFT) and the Boltzmann transport equation (BTE) to investigate the structural, electronic, and thermoelectric properties of germanium sulfide (GeS) and germanium selenide (GeSe) monolayers, along with their van der Waals (vdW) heterostructures. We analyzed XX-stacked and XY-stacked configurations, where the XX configuration features direct atomic stacking, while the XY configuration exhibits staggered stacking. Our first-principles calculations indicate that the formation of GeS/GeSe heterostructures results in a reduction of bandgaps compared to their bulk and monolayer counterparts, yielding bandgap values of 0.91 eV for the XX configuration and 0.84 eV for the XY configuration. Stability assessments reveal that the XY configuration is more stable, demonstrating a lattice thermal conductivity of 15.21 W/mK compared to 17.95 W/mK for the XX configuration T 300 K. The thermoelectric properties were systematically evaluated across a temperature range of 300-800 K, revealing high Seebeck coefficients of 1.51 mV/K for the XX heterostructure and 1.39 mV/K for the XY heterostructure. reflecting their excellent charge transport capabilities. Notably, the figure of merit (ZT) at 800 K was calculated to be 0.90 for the XX configuration and 1.01 for the XY configuration, underscoring the superior thermoelectric performance of the XY heterostructure. These findings contribute to a comprehensive understanding of 2D GeS/GeSe heterostructures for thermoelectric applications and provide a solid foundation for future research and technological advancements in this domain. van der Waals force ; Heterojunction ; Condensed matter physics ; Thermoelectric effect ; Materials science ; Physics ; Thermodynamics ; Quantum mechanics ; Molecule Advanced Thermoelectric Materials and Devices ; 2D Materials and Applications ; Chalcogenide Semiconductor Thin Films
Authors: Le Shu | Yujie Xia | Ben Li | Lei Peng | Hezhu Shao | Zengxu Wang | Yan Cen | Heyuan Zhu | Hao Zhang
Source: npj Computational Materials (article, 2024-01-02)
Field: Materials Science — Materials Chemistry

Full-landscape selection rules of electrons and phonons and temperature-induced effects in 2D silicon and germanium allotropes Abstract The electron-phonon (el-ph) and phonon-phonon interactions play crucial roles in determining the electronic and thermal transport properties of materials. Using the group theory and ab-initio calculations, we have derived the full-landscape selection rules for intravalley and intervalley scattering for carriers in 2D silicon and germanium allotropes with low buckled (LB) and large honeycomb dumbbell (LHD) structures, showing dominant role of optical modes in total el-ph coupling in LHD Si/Ge due to most el-ph scattering channels via acoustic modes blocked by symmetries. Remarkably, we show that due to the relatively large optical phonon bandwidth and “bunching effect" of acoustic phonon bands, the selection rules of three-phonon interactions reveal the dominant ooo and aoo channels in LHD and LB Si/Ge, respectively, and the temprature-induced effects significantly increase the ratio between mode-resolved four-phonon interactions and three-phonon interactions in most of the phonon-frequency region, finally leading to the low thermal conductivities in both LB and LHD Si/Ge. Furthermore, we observe the anomalous temperature-dependent thermal conductivities in LHD Ge, resulted from the vanishing quasi-acoustic-optical phonon gap under the temperature-induced effects. By considering full el-ph coupling and higher-order anharmonic phonon-phonon interactions, the maximal thermoelectric figures of merits in LHD Si and LB Ge are found to reach 1.06 and 0.66 at 700 K, respectively, significantly surpassing their bulk counterparts. Our work is poised to stimulate wide-ranging exploration into phonon transport across diverse materials, and benefits both fundamental knowledge and advanced technologies of 2D Si/Ge allotropes. Phonon ; Condensed matter physics ; Anharmonicity ; Germanium ; Materials science ; Phonon scattering ; Thermoelectric effect ; Scattering ; Coupling (piping) ; Silicon ; Physics ; Optoelectronics ; Optics ; Thermodynamics Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; 2D Materials and Applications
Authors: Lei Cai | Mei-Qi Zeng | Mengjie Liu | Jing-Yu Bao | Yuqian Ren | M. Bobby Kannan | Lan‐Yue Cui | Cheng‐Bao Liu | Fen Zhang | Shuo‐Qi Li | Rong‐Chang Zeng
Source: npj Materials Degradation (article, 2024-01-16)
Field: Materials Science — Biomaterials

Exfoliation of an extruded Mg-4Li-1Ca alloy in presence of glucose and bovine serum albumin Abstract Exfoliation corrosion (EFC) on extruded Mg-4Li-1Ca alloys as bone implant materials has not been reported. This study aimed to elucidate the degradation mechanism of a corrosion type-exfoliation occurred on an extruded Mg-4Li-1Ca alloy under the interaction of glucose (Glu) and bovine serum albumin (BSA) in Hank’s solution. The alloy microstructure, chemical composition, texture, stress distribution and Volta potential maps were characterized using metallographic microscopy, scanning electron microscopy and electron backscattered diffraction, and scanning Kelvin Probe. The alloy corrosion behavior was investigated via electrochemical testing and hydrogen evolution rate methods. X-ray diffraction, Fourier transform infrared spectrometry, X-ray photoelectron spectrometer, and fluorescence microscopy were used to analyze the corrosion products and the adsorption of the organic molecules. The experimental results indicated that the anodic second phase (Mg 2 Ca) were distributed in lamellar and rod-like patterns along the extrusion direction of the alloy, a lower Volta potential for Mg 2 Ca, texture and residual stresses also promote EFC. An increase in Glu concentration exacerbated the EFC, whereas BSA inhibited the EFC of the alloy. Higher Glu concentrations in BSA in turn inhibited EFC since Glu can complex with amino acids in proteins to form Glu-amino acid amides, which promoted protein adsorption and thereby forming a dense protective film on the alloy surface. The preferential dissolution of the Mg 2 Ca phase particles led to the complexation and adsorption of Glu and protein. This study enriches the understanding of the corrosion types in biomedical Mg-4Li-1Ca alloy and paving the way for enhancing the EFC resistance of the alloy. Bovine serum albumin ; Alloy ; Materials science ; Scanning electron microscope ; Corrosion ; Microstructure ; Dissolution ; Exfoliation joint ; Adsorption ; Texture (cosmology) ; Chemical engineering ; Chemistry ; Metallurgy ; Composite material ; Chromatography ; Nanotechnology ; Organic chemistry Magnesium Alloys: Properties and Applications ; Corrosion Behavior and Inhibition ; Aluminum Alloys Composites Properties
Authors: Ran Wang | Cheng Xu | Shuhao Zhang | Fangwen Ye | Yinuo Tang | S.H. Tang | Hangning Zhang | Wenya Du | Xiaotong Zhang
Source: Nature Communications (article, 2024-10-28)
Field: Materials Science — Materials Chemistry

MatSwarm: trusted swarm transfer learning driven materials computation for secure big data sharing The rapid advancement of Industry 4.0 necessitates close collaboration among material research institutions to accelerate the development of novel materials. However, multi-institutional cooperation faces significant challenges in protecting sensitive data, leading to data silos. Additionally, the heterogeneous and non-independent and identically distributed (non-i.i.d.) nature of material data hinders model accuracy and generalization in collaborative computing. In this paper, we introduce the MatSwarm framework, built on swarm learning, which integrates federated learning with blockchain technology. MatSwarm features two key innovations: a swarm transfer learning method with a regularization term to enhance the alignment of local model parameters, and the use of Trusted Execution Environments (TEE) with Intel SGX for heightened security. These advancements significantly enhance accuracy, generalization, and ensure data confidentiality throughout the model training and aggregation processes. Implemented within the National Material Data Management and Services (NMDMS) platform, MatSwarm has successfully aggregated over 14 million material data entries from more than thirty research institutions across China. The framework has demonstrated superior accuracy and generalization compared to models trained independently by individual institutions. Computer science ; Generalization ; Federated learning ; Swarm behaviour ; Key (lock) ; Transfer of learning ; Big data ; Confidentiality ; Data sharing ; Computation ; Distributed computing ; Computer security ; Artificial intelligence ; Data mining ; Algorithm Machine Learning in Materials Science ; Ferroelectric and Negative Capacitance Devices ; Advanced Memory and Neural Computing
Authors: Yingcheng Zhang | Marco Bertani | Alfonso Pedone | Randall E. Youngman | Grégory Tricot | Aditya Kumar | Ashutosh Goel
Source: Acta Materialia (article, 2024-02-21)
Field: Materials Science — Ceramics and Composites

Decoding crystallization behavior of aluminoborosilicate glasses: From structural descriptors to Quantitative Structure – Property Relationship (QSPR) based predictive models Crystallization ; Quantitative structure–activity relationship ; Nucleation ; Materials science ; Aluminosilicate ; Thermodynamics ; Phase (matter) ; Computer science ; Chemistry ; Organic chemistry ; Machine learning ; Physics Glass properties and applications ; Pigment Synthesis and Properties ; Mineralogy and Gemology Studies
Authors: Daria Poloneeva | Shuvo Jit Datta | Ronell Sicat | Rushana Khairova | Luis Garzón‐Tovar | Anastasiya Bavykina | Mohamed Eddaoudi | Jorge Gascón
Source: Small (article, 2024-03-30)
Field: Chemistry — Inorganic Chemistry

Advancing Membrane Technology: Ordered Macroporous ZIF‐67 as a Filler in Mixed Matrix Membranes for Enhanced Propylene/Propane Separation Conventional separation technologies for valuable commodities require substantial energy, accounting for 10%-15% of global consumption. Mixed-matrix membranes (MMMs) offer a promising solution by combining processable polymers with selective inorganic fillers. Here, the potential of using ordered microporous structured materials is demonstrated as MMM fillers. The use of ordered macroporous ZIF-67 in combination with the well-known 6FDA-DAM polymer leads to superior performance in the important separation of propylene from propane. The enhanced performance can be rationalized with the help of advanced microscopy, which demonstrates that the polymer is able to penetrate the macroporous network around which the MOF (Metal-Organic Framework) is synthesized, resulting in a much better interphase between the two components and the homogeneous distribution of the filler, even at high loadings. Propane ; Materials science ; Membrane ; Polymer ; Microporous material ; Chemical engineering ; Filler (materials) ; Interphase ; Gas separation ; Ternary operation ; Metal-organic framework ; Matrix (chemical analysis) ; Composite material ; Organic chemistry ; Chemistry ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Membrane Separation and Gas Transport ; Zeolite Catalysis and Synthesis
Authors: Y.Z. Jia | Dezhi Yang | Wenwen Wang | Kun Hu | Min Yan | Li Zhang | Li Gao | Yang Lü
Source: Natural Products and Bioprospecting (review, 2024-09-14)
Field: Chemistry — Physical and Theoretical Chemistry

Recent advances in pharmaceutical cocrystals of theophylline Currently, cocrystallization is a promising strategy for tailoring the physicochemical properties of active pharmaceutical ingredients. Theophylline, an alkaloid and the most primary metabolite of caffeine, is a readily available compound found in tea and coffee. It functions primarily as a bronchodilator and respiratory stimulant, making it a mainstay treatment for lung diseases like asthma. Theophylline's additional potential benefits, including anti-inflammatory and anticancer properties, and its possible role in neurological disorders, have garnered significant research interest. Cocrystal formation presents a viable approach to improve the physicochemical properties of theophylline and potentially mitigate its toxic effects. This review comprehensively explores several successful studies that utilized cocrystallization to favorably alter the physicochemical properties of theophylline or its CCF. Notably, cocrystals can not only enhance the solubility and bioavailability of theophylline but also exhibit synergistic effects with other APIs. The review further delves into the hydrogen bonding sites within the theophylline structure and the hydrogen bonding networks observed in cocrystal structures. Theophylline ; Cocrystal ; Bronchodilator ; Chemistry ; Theobromine ; Pharmacology ; Bioavailability ; Caffeine ; Hydrogen bond ; Asthma ; Medicine ; Organic chemistry ; Molecule Crystallography and molecular interactions ; Crystal structures of chemical compounds ; Crystallization and Solubility Studies
Authors: Yifan Tu | Mei-Ying Kwan | Kit‐Lun Yick
Source: Materials (review, 2024-10-13)
Field: Materials Science — Polymers and Plastics

A Systematic Review of AI-Driven Prediction of Fabric Properties and Handfeel Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 899 papers initially identified, 39 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations. Artificial intelligence ; Computer science ; Textile ; Machine learning ; Quality (philosophy) ; Generalization ; Sustainability ; Predictive modelling ; Data science ; Materials science ; Mathematics Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Color Science and Applications
Authors: Golshan Matinfar | Haoxin Ye | Moein Bashiry | Zahra Hashami | Tianxi Yang
Source: Comprehensive Reviews in Food Science and Food Safety (review, 2024-09-01)
Field: Materials Science — Biomaterials

Electrospinning‐based sensing technologies: Opportunities for food applications The article explores the science and practice of electrospinning, tracing its history and examining the factors that influence fiber morphology, including the solution composition, processing conditions, and environmental conditions. It offers a thorough examination of electrospinning fundamentals geared toward generating an appropriate platform for creating tailored nanofibers for sensing applications in the food industry. These nanofibers play a critical role in food analysis, sensing, and traceability, and we highlight their effectiveness in identifying pesticide residues, food components, antibiotics, heavy metals, and foodborne pathogens as well as in monitoring the freshness and spoilage of food. The use of electrospinning technology is poised to make sensing platforms more accessible, affordable, and widespread, thereby significantly contributing to the improvement of food quality and safety monitoring practices. Traceability ; Electrospinning ; Food spoilage ; Nanofiber ; Food safety ; Food packaging ; Food quality ; Food industry ; Nanotechnology ; Business ; Computer science ; Materials science ; Food science ; Chemistry Electrospun Nanofibers in Biomedical Applications ; Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials
Authors: Dongrui Su | Panpan Chen | Cunlei Li | Yongfei Yan | Ranlei Zhao | Qingyou Yue | Yupeng Qiao
Source: Molecules (review, 2024-09-16)
Field: Chemistry — Inorganic Chemistry

Research Progress in Microporous Materials for Selective Adsorption and Separation of Methane from Low-Grade Gas Given that methane (CH<sub>4</sub>) and nitrogen (N<sub>2</sub>) have similar properties, achieving high-purity enrichment of CH<sub>4</sub> from nitrogen-rich low-grade gas is extremely challenging and is of great significance for sustainable development in energy and the environment. This paper reviews the research progress on carbon-based materials, zeolites, and MOFs as adsorbent materials for CH<sub>4</sub>/N<sub>2</sub> separation. It focuses on the relationship between the composition, pore size, surface chemistry of the adsorbents, CH<sub>4</sub>/N<sub>2</sub> selectivity, and CH<sub>4</sub> adsorption capacity. The paper also highlights that controlling pore size and atomic-scale composition and optimizing these features for the best match are key directions for the development of new adsorbents. Additionally, it points out that MOFs, which combine the advantages of carbon-based adsorbents and zeolites, are likely to become the most promising adsorbent materials for efficient CH<sub>4</sub>/N<sub>2</sub> separation. Adsorption ; Microporous material ; Methane ; Gas separation ; Nitrogen ; Carbon fibers ; Materials science ; Chemical engineering ; Selective adsorption ; Nanotechnology ; Selectivity ; Chemistry ; Organic chemistry ; Catalysis ; Composite material Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Covalent Organic Framework Applications
Authors: Jahaan Shaikh | Salman Patel | Afzal Nagani | Moksh Shah | Siddik Ugharatdar | Ashish Patel | Drashti Shah | Dharti Patel
Source: In Silico Pharmacology (article, 2024-08-29)
Field: Chemistry — Organic Chemistry

Pharmacophore mapping, 3D QSAR, molecular docking, and ADME prediction studies of novel Benzothiazinone derivatives Pharmacophore ; Quantitative structure–activity relationship ; ADME ; Computational biology ; Chemistry ; Computer science ; Computational chemistry ; Stereochemistry ; Biology ; Biochemistry Synthesis and biological activity ; Computational Drug Discovery Methods ; Phenothiazines and Benzothiazines Synthesis and Activities
Authors: Zhijuan Duan | Haoqian Li | Chenguang Li | Jun Zhang | Dongfang Zhang | Xiaofei Fan | Xueping Chen
Source: Plant Methods (article, 2024-07-29)
Field: Chemistry — Analytical Chemistry

A CNN model for early detection of pepper Phytophthora blight using multispectral imaging, integrating spectral and textural information The research indicates that Phytophthora blight infection can be detected 48 h after inoculation (36 h before visible symptoms). This study provides an effective method for the early detection of Phytophthora blight in peppers. Multispectral image ; Phytophthora capsici ; Principal component analysis ; Pepper ; Blight ; Artificial intelligence ; Convolutional neural network ; Pattern recognition (psychology) ; Phytophthora ; Computer science ; Feature selection ; Linear discriminant analysis ; Mathematics ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Smart Agriculture and AI
Authors: Prathmesh Bhadane | Priya Mahato | Dhruv Menon | Biraj Kanta Satpathy | Lisi Wu | Swaroop Chakraborty | Prateek Goyal | Iseult Lynch | Superb K. Misra
Source: Environmental Science Nano (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Hydrolytically stable nanosheets of Cu–imidazolate MOF for selective trapping and simultaneous removal of multiple heavy metal ions This study reports stable and sustainable material for mitigating the multifaceted challenges presented by toxic metal contamination in water. Imidazolate ; Metal ; Metal ions in aqueous solution ; Zeolitic imidazolate framework ; Materials science ; Heavy metals ; Trapping ; Metal-organic framework ; Environmental chemistry ; Nanotechnology ; Chemical engineering ; Inorganic chemistry ; Chemistry ; Adsorption ; Metallurgy ; Organic chemistry ; Ecology Metal-Organic Frameworks: Synthesis and Applications ; Extraction and Separation Processes ; MXene and MAX Phase Materials
Authors: Aleksandra Smejda-Krzewicka | Konrad Mrozowski | Krzysztof Strzelec
Source: Materials (article, 2024-04-24)
Field: Materials Science — Polymers and Plastics

Effect of Modified and Unmodified Oak Bark (Quercus Cortex) on the Cross-Linking Process and Mechanical, Anti-Aging, and Hydrophobic Properties of Biocomposites Produced from Natural Rubber (NR) The study explores the novel use of oak bark (Quercus cortex) as a bio-filler in elastomeric composites, aligning with the global trend of plant-based biocomposites. Both modified and unmodified oak bark were investigated for their impact on the physicochemical properties of natural rubber (NR) composites. The bio-filler modified with n-octadecyltrimethoxysilane exhibited enhanced dispersion and reduced aggregates in the elastomeric matrix. NR composites containing more than 20 phr of unmodified and modified oak bark demonstrated an increased degree of cross-linking (α<sub>c</sub> > 0.21). Mechanical properties were optimal at 10-15 phr of oak bark and the sample with modified bio-filler (10 phr) achieved the highest tensile strength (15.8 MPa). Silanization and the addition of the bio-filler increased the hardness of vulcanizates. The incorporation of oak bark improved aging resistance at least two-fold due to phenolic derivatives with antioxidant properties. Hydrophobicity decreased with added bark, but silanization reversed the trend, making samples with a high content of oak bark the most hydrophobic (contact angle: 129°). Overall, oak bark shows promise as an eco-friendly, anti-aging filler in elastomeric composites, with modification enhancing compatibility and hydrophobicity. Bark (sound) ; Natural rubber ; Materials science ; Composite material ; Forestry Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Advanced Cellulose Research Studies