jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiaonan Lu | John D. Vienna | Jincheng Du
Source: Journal of the American Ceramic Society (review, 2023-07-18)
Field: Materials Science — Ceramics and Composites

Glass formulation and composition optimization with property models: A review Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed. Property (philosophy) ; Computer science ; Perspective (graphical) ; Compositional data ; Industrial engineering ; Data science ; Artificial intelligence ; Machine learning ; Engineering Glass properties and applications ; Phase-change materials and chalcogenides ; Cultural Heritage Materials Analysis
Authors: Robert Haase | Thomas Pinetz | Zeynep Bendella | Erich Kobler | Daniel Paech | Wolfgang Block | Alexander Effland | Alexander Radbruch | Katerina Deike‐Hofmann
Source: Investigative Radiology (article, 2023-01-28)
Field: Materials Science — Materials Chemistry

Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols The tested deep learning algorithm for synthesis of artificial T1w full-dose sequences based on images after administration of only 10% of the standard dose of a gadolinium-based contrast agent showed very good quantitative performance. Despite good image quality in all settings, both false-negative and false-positive signals resulted in significantly limited interchangeability of the synthesized sequences with the original full-dose sequences. Gadolinium ; Convolutional neural network ; Contrast (vision) ; Reduction (mathematics) ; Computer science ; Artificial intelligence ; Chemistry ; Mathematics Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Jia He | Cuiqian Yu | Shuang Lü | Shuyue Shan | Zhongwei Zhang | Jie Chen
Source: Nanotechnology (article, 2023-10-07)
Field: Materials Science — Materials Chemistry

Complex role of strain engineering of lattice thermal conductivity in hydrogenated graphene-like borophene induced by high-order phonon anharmonicity Strain engineering has been used as a versatile tool for regulating the thermal transport in various materials as a result of the phonon frequency shift. On the other hand, the phononic bandgap can be simultaneously tuned by the strain, which can play a critical role in wide phononic bandgap materials due to the high-order phonon anharmonicity. In this work, we investigate the complex role of uniaxial tensile strain on the lattice thermal conductivity of hydrogenated graphene-like borophene, by using molecular dynamics simulations with a machine learning potential. Our findings highlight a novel and intriguing phenomenon that the thermal conductivity in the armchair direction is non-monotonically dependent on the uniaxial armchair strain. Specifically, we uncover that the increase of phonon group velocity and the decrease of three-phonon scattering compete with the enhancement of four-phonon scattering under armchair strain, leading to the non-monotonic dependence. The enhanced four-phonon scattering originates from the unique bridged B-H bond that can sensitively control the phononic bandgap under armchair strain. This anomalous non-monotonic strain-dependence highlights the complex interplay between different mechanisms governing thermal transport in 2D materials with large phononic bandgaps. Our study offers valuable insights for designing innovative thermal management strategies based on strain. Phonon ; Materials science ; Anharmonicity ; Condensed matter physics ; Thermal conductivity ; Strain engineering ; Graphene ; Band gap ; Phonon scattering ; Scattering ; Lattice (music) ; Nanotechnology ; Optoelectronics ; Composite material ; Optics ; Physics Thermal properties of materials ; Graphene research and applications ; Advanced Thermoelectric Materials and Devices
Authors: Ryota Hikichi | Y. Tokura | Yasuhiko Igarashi | Hiroaki Imai | Yuya Oaki
Source: Bulletin of the Chemical Society of Japan (article, 2023-07-04)
Field: Materials Science — Surfaces, Coatings and Films

Fluorine-Free Substrate-Independent Superhydrophobic Coatings by Nanoarchitectonics of Polydispersed 2D Materials Abstract Fluorine-free superhydrophobic surfaces have been required to meet environmental regulations in recent years. A new nanoarchitectonics is required to achieve superhydrophobicity without using perfluoroalkyl compounds. In the present work, surface-modified exfoliated nanosheets with polydispersed sizes were utilized to prepare coatings with high surface roughness and low surface energy. Fluorine-free superhydrophobic surfaces were obtained by spray coating of surface-modified exfoliated nanosheets based on transition-metal oxides. The water contact angle (θw) 166.0 ± 0.5° is the highest compared with that of the fluorine-free substrate-independent coatings in previous reports. The significant factors related to θw were studied using machine learning combined with our chemical insight in the small data obtained in the present work. The resultant superhydrophobic coatings exhibited unique properties, such as sliding of water droplets, superoleophilic behavior, recyclability, and durability. The present design strategy can be applied to development of various functional coatings using exfoliated 2D materials with polydispersity. Contact angle ; Materials science ; Superhydrophobic coating ; Coating ; Fluorine ; Substrate (aquarium) ; Surface energy ; Monolayer ; Dispersity ; Surface finish ; Fluoropolymer ; Surface roughness ; Nanotechnology ; Surface modification ; Composite material ; Layer (electronics) ; Chemical engineering ; Metallurgy ; Polymer chemistry ; Polymer Surface Modification and Superhydrophobicity ; Advanced Sensor and Energy Harvesting Materials ; Adhesion, Friction, and Surface Interactions
Authors: Xingyuan San | Junwei Hu | Mingyi Chen | Haiyang Niu | Paul J. M. Smeets | Christos D. Malliakas | Jie Deng | Kunmo Koo | Roberto dos Reis | Vinayak P. Dravid | Xiaobing Hu
Source: Nature Communications (article, 2023-11-29)
Field: Materials Science — Biomaterials

Unlocking the mysterious polytypic features within vaterite CaCO3 Calcium carbonate (CaCO<sub>3</sub>), the most abundant biogenic mineral on earth, plays a crucial role in various fields such as hydrosphere, biosphere, and climate regulation. Of the four polymorphs, calcite, aragonite, vaterite, and amorphous CaCO<sub>3</sub>, vaterite is the most enigmatic one due to an ongoing debate regarding its structure that has persisted for nearly a century. In this work, based on systematic transmission electron microscopy characterizations, crystallographic analysis and machine learning aided molecular dynamics simulations with ab initio accuracy, we reveal that vaterite can be regarded as a polytypic structure. The basic phase has a monoclinic lattice possessing pseudohexagonal symmetry. Direct imaging and atomic-scale simulations provide evidence that a single grain of vaterite can contain three orientation variants. Additionally, we find that vaterite undergoes a second-order phase transition with a critical point of ~190 K. These atomic scale insights provide a comprehensive understanding of the structure of vaterite and offer advanced perspectives on the biomineralization process of calcium carbonate. Vaterite ; Calcite ; Aragonite ; Biomineralization ; Calcium carbonate ; Amorphous calcium carbonate ; Chemical physics ; Crystallography ; Chemistry ; Materials science ; Mineralogy ; Biology ; Paleontology Calcium Carbonate Crystallization and Inhibition ; Paleontology and Stratigraphy of Fossils ; Minerals Flotation and Separation Techniques
Authors: Lulu Chen | Siyue Yang | Zhuan Nan | Yanping Li | Jianlong Ma | Jianbao Ding | Yi Lv | Jin Yang
Source: Heliyon (article, 2023-06-01)
Field: Chemistry — Analytical Chemistry

Detection of dextran, maltodextrin and soluble starch in the adulterated Lycium barbarum polysaccharides (LBPs) using Fourier-transform infrared spectroscopy (FTIR) and machine learning models Due to the similar chemical structures and physicochemical properties, it is challenging to distinguish dextran, maltodextrin, and soluble starch from the polysaccharide products of plant origin, such as <i>Lycium barbarum</i> polysaccharides (LBPs). Using the first-order derivatives of Fourier-transformed infrared spectroscopy (FTIR, wave range 1800-400 cm<sup>-1</sup>), this study proposed a two-step pipeline to identify dextran, maltodextrin, and soluble starch from adulterated LBPs samples qualitatively and quantitatively. We applied principal component analysis (PCA) to reduce the dimensionality of FTIR features. For the qualitative step, a set of machine learning models, including logistic regression, support vector machine (SVM), Naïve Bayes, and partial least squares (PLS), were used to classify the adulterants. For the quantitative step, linear regression, LASSO, random forest, and PLS were used to predict the concentration of LBPs adulterants. The results showed that logistic regression and SVM are suitable for classifying adulterants, and random forests is superior for predicting adulterant concentrations. This would be the first attempt to discriminate the adulterants from the polysaccharide's product of plant origin. The proposed two-step methods can be easily extended to other applications for the quantitative and qualitative detection of samples from adulterants with similar chemical structures. Maltodextrin ; Fourier transform infrared spectroscopy ; Starch ; Chemistry ; Partial least squares regression ; Artificial intelligence ; Polysaccharide ; Principal component analysis ; Adulterant ; Support vector machine ; Mathematics ; Chromatography ; Food science ; Computer science ; Machine learning ; Spray drying ; Biochemistry ; Chemical engineering Spectroscopy and Chemometric Analyses ; Polysaccharides Composition and Applications ; Food composition and properties
Authors: Ri He | Hua Wang | Fucai Liu | Shi Liu | Houfang Liu | Zhicheng Zhong
Source: Physical review. B./Physical review. B (article, 2023-07-19)
Field: Materials Science — Materials Chemistry

Unconventional ferroelectric domain switching dynamics in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>CuIn</mml:mi><mml:msub><mml:mi mathvariant="normal">P</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">S</mml:mi><mml:mn>6</mml:mn></mml:msub></mml:mrow></mml:math> from first principles The switching dynamics of ferroelectric materials is a crucial intrinsic property which directly affects the operation and performance of ferroelectric devices. In conventional ferroelectric materials, the typical ferroelectric switching mechanism is governed by a universal process of domain-wall motion. However, recent experiments indicate that van der Waals ferroelectric $\mathrm{CuIn}{\mathrm{P}}_{2}{\mathrm{S}}_{6}$ possesses anomalous polarization switching dynamics under an electric field. It is important to understand the switching dynamics, but it remains theoretically unexplored in $\mathrm{CuIn}{\mathrm{P}}_{2}{\mathrm{S}}_{6}$ due to the lack of description of its order-disorder phase transition characteristics by density functional theory. Here we employ a machine-learning potential trained from the first-principles density functional theory dataset to conduct large-scale atomistic simulations of temperature-driven order-disorder ferroelectric phase transition in $\mathrm{CuIn}{\mathrm{P}}_{2}{\mathrm{S}}_{6}$. Most importantly, it is found that the electric-field-driven polarization switching in $\mathrm{CuIn}{\mathrm{P}}_{2}{\mathrm{S}}_{6}$ is mediated by a single Cu dipole flip rather than a conventional domain-wall-motion mechanism. This intrinsic unconventional switching behavior can be attributed to the competition between the energy barrier of domain-wall motion and single-dipole flip. Ferroelectricity ; Domain (mathematical analysis) ; Physics ; Materials science ; Mathematics ; Mathematical analysis ; Quantum mechanics Solid-state spectroscopy and crystallography ; Photorefractive and Nonlinear Optics ; Optical and Acousto-Optic Technologies
Authors: Afzan Mahmad | Zakariyya Uba Zango | Teh Ubaidah Noh | Fahad Usman | Osamah Aldaghri | Khalid Hassan Ibnaouf | Maizatul Shima Shaharun
Source: Groundwater for Sustainable Development (article, 2023-02-04)
Field: Chemistry — Inorganic Chemistry

Response surface methodology and artificial neural network for prediction and validation of bisphenol a adsorption onto zeolite imidazole framework Adsorption ; Zeolite ; Response surface methodology ; Enthalpy ; Bisphenol A ; Aqueous solution ; Imidazole ; Chemistry ; BET theory ; Exothermic reaction ; Chemical engineering ; Materials science ; Chromatography ; Thermodynamics ; Organic chemistry ; Catalysis Metal-Organic Frameworks: Synthesis and Applications ; Adsorption and biosorption for pollutant removal ; Covalent Organic Framework Applications
Authors: Yun Seon Lee | Nam Ryeol Kim | Sang Ki Park | Yong‐Il Ko | Yunjae Shin | Beomjoo Yang | Cheol‐Min Yang
Source: Applied Surface Science (article, 2023-12-18)
Field: Materials Science — Materials Chemistry

Effects of high-temperature thermal reduction on thermal conductivity of reduced graphene oxide polymer composites The graphitic crystalline structure of reduced graphene oxide (rGO) can be improved by high-temperature thermal reduction at various heat-treatment temperatures ranging from 1000 to 2500 °C. The crystallinity significantly increased with increasing heat-treatment temperature. The electrical conductivities of the rGOs heat-treated at 2000 and 2500 °C (h-rGO-2000 and h-rGO-2500, respectively) were similar to those of commercial graphite. The isotropic thermal conductivity of rGO/epoxy composite with 10 wt% h-rGO-2500 (2.56 W/mK) is 11.6 times higher than that of pristine rGO (p-rGO; 0.22 W/mK) and significantly superior to those of epoxy composites with commercial graphite (0.82 W/mK) and mesophase pitch-based carbon fibers (MPCFs; 1.29 W/mK). Moreover, owing to the synergistic effect operating in the MPCF–h-rGO hybrid filler in epoxy composites, this combination of fillers increases the thermal conductivity to a greater extent than the MPCF–p-rGO hybrid filler. Optimum synergistic effects on the isotropic and in-plane thermal conductivities were achieved with an MPCF:h-rGO-2000 weight ratio of 49:1 (17.93 W/mK, 1.85 times higher than 9.69 W/mK for MPCF–p-rGO). Finally, a machine learning method that could predict and optimize the properties of rGOs based on their HT temperatures and material compositions was developed. Materials science ; Graphene ; Composite material ; Thermal conductivity ; Epoxy ; Graphite ; Oxide ; Crystallinity ; Composite number ; Graphite oxide ; Filler (materials) ; Nanotechnology ; Metallurgy Thermal properties of materials ; Graphene research and applications ; Carbon Nanotubes in Composites
Authors: Yuwei Lu | Rui Wang | Tianyu Hu | Qiang He | Zhou Shuai Chen | Jinhu Wang | Lingbo Liu | Chuanying Fang | Jie Luo | Ling Fu | Lejun Yu | Qian Liu
Source: Frontiers in Plant Science (article, 2023-01-12)
Field: Chemistry — Analytical Chemistry

Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning Passion fruit is a tropical liana of the Passiflora family that is commonly planted throughout the world due to its abundance of nutrients and industrial value. Researchers are committed to exploring the relationship between phenotype and genotype to promote the improvement of passion fruit varieties. However, the traditional manual phenotyping methods have shortcomings in accuracy, objectivity, and measurement efficiency when obtaining large quantities of personal data on passion fruit, especially internal organization data. This study selected samples of passion fruit from three widely grown cultivars, which differed significantly in fruit shape, size, and other morphological traits. A Micro-CT system was developed to perform fully automated nondestructive imaging of the samples to obtain 3D models of passion fruit. A designed label generation method and segmentation method based on U-Net model were used to distinguish different tissues in the samples. Finally, fourteen traits, including fruit volume, surface area, length and width, sarcocarp volume, pericarp thickness, and traits of fruit type, were automatically calculated. The experimental results show that the segmentation accuracy of the deep learning model reaches more than 0.95. Compared with the manual measurements, the mean absolute percentage error of the fruit width and length measurements by the Micro-CT system was 1.94% and 2.89%, respectively, and the squares of the correlation coefficients were 0.96 and 0.93. It shows that the measurement accuracy of external traits of passion fruit is comparable to manual operations, and the measurement of internal traits is more reliable because of the nondestructive characteristics of our method. According to the statistical data of the whole samples, the Pearson analysis method was used, and the results indicated specific correlations among fourteen phenotypic traits of passion fruit. At the same time, the results of the principal component analysis illustrated that the comprehensive quality of passion fruit could be scored using this method, which will help to screen for high-quality passion fruit samples with large sizes and high sarcocarp content. The results of this study will firstly provide a nondestructive method for more accurate and efficient automatic acquisition of comprehensive phenotypic traits of passion fruit and have the potential to be extended to more fruit crops. The preliminary study of the correlation between the characteristics of passion fruit can also provide a particular reference value for molecular breeding and comprehensive quality evaluation. Passiflora ; Passion fruit ; Passion ; Segmentation ; Artificial intelligence ; Horticulture ; Mathematics ; Biology ; Computer science ; Psychology Spectroscopy and Chemometric Analyses
Authors: Min Xu | Ran Cao | Qin Han | Nuoxi Zhang | Wenle Yan | Li Liu | John T. S. Irvine | Di Chen
Source: Materials Reports Energy (article, 2023-04-26)
Field: Materials Science — Materials Chemistry

Exsolved materials for CO2 reduction in high-temperature electrolysis cells Electrochemical reduction of CO2 into valuable fuels and chemicals has become a contemporary research area, where the heterogeneous catalyst plays a critical role. Metal nanoparticles supported on oxides performing as active sites of electrochemical reactions have been the focus of intensive investigation. Here, we review the CO2 reduction with active materials prepared by exsolution. The fundamental of exsolution was summarized in terms of mechanism and models, materials, and driven forces. The advances in the exsolved materials used in high-temperature CO2 electrolysis were catalogued into tailored interfaces, synergistic effects on alloy particles, phase transition, reversibility and electrochemical switching. Electrolysis ; Materials science ; Electrochemistry ; Alloy ; Reduction (mathematics) ; Nanotechnology ; Chemical engineering ; Metallurgy ; Chemistry ; Electrode ; Engineering Advancements in Solid Oxide Fuel Cells ; Electronic and Structural Properties of Oxides ; CO2 Reduction Techniques and Catalysts
Authors: Mayuresh Khot | Rahaman Sharif Shaik | Wania Touseef | Amirkianoosh Kiani
Source: Scientific Reports (article, 2023-04-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Binder-free NiO/CuO hybrid structure via ULPING (Ultra-short Laser Pulse for In-situ Nanostructure Generation) technique for supercapacitor electrode Developing a cost-effective pseudocapacitor electrode manufacturing process incorporating binder-free, green synthesis methods and single-step fabrication is crucial in advancing supercapacitor research. This study aims to address this pressing issue and contribute to the ongoing efforts in the field by introducing ULPING (Ultra-short Laser Pulse for In-situ Nanostructure Generation) technique for effective design. Laser irradiation was conducted in ambient conditions to form a CuO/NiO hybrid structure providing a synergistic contribution to the electrical behavior of the electrode. Mainly, the effects of surface morphology and electrochemical surface because of tuning laser intensity were analyzed. The samples demonstrated high oxide formation, fiber generation, excellent porosity, and ease of ion accessibility. Owing to a less than 10-min binder-free fabrication method, the electrochemical performance of the as-fabricated electrode was 25.8 mC cm<sup>-2</sup> at a current density of 1 mA cm<sup>-2</sup> proved to be excellent. These excellent surface properties were possible by the simple working principle of pulsed laser irradiation in ambient conditions and smart tuning of the important laser parameters. The CuO/NiO electrode demonstrates excellent conductivity and rewarding cyclic stability of 83.33% after 8000 cycles. This study demonstrates the potential of the ULPING technique as a green and simple method for fabricating high-performance pseudocapacitor electrodes. Nanostructure ; Supercapacitor ; Materials science ; Electrode ; In situ ; Non-blocking I/O ; Laser ; Pulse (music) ; Optoelectronics ; Nanotechnology ; Electrochemistry ; Computer science ; Chemistry ; Optics ; Telecommunications ; Physics Supercapacitor Materials and Fabrication ; Transition Metal Oxide Nanomaterials ; Copper-based nanomaterials and applications
Authors: Sylvia L. Hanna | Omar K. Farha
Source: Chemical Science (review, 2023-01-01)
Field: Chemistry — Inorganic Chemistry

Energy–structure–property relationships in uranium metal–organic frameworks Located at the foot of the periodic table, uranium is a relatively underexplored element possessing rich chemistry. In addition to its high relevance to nuclear power, uranium shows promise for small molecule activation and photocatalysis, among many other powerful functions. Researchers have used metal-organic frameworks (MOFs) to harness uranium's properties, and in their quest to do so, have discovered remarkable structures and unique properties unobserved in traditional transition metal MOFs. More recently, (<i>e.g.</i> the last 8-10 years), theoretical calculations of framework energetics have supplemented structure-property studies in uranium MOFs (U-MOFs). In this Perspective, we summarize how these budding energy-structure-property relationships in U-MOFs enable a deeper understanding of chemical phenomena, enlarge chemical space, and elevate the field to targeted, rather than exploratory, discovery. Importantly, this Perspective encourages interdisciplinary connections between experimentalists and theorists by demonstrating how these collaborations have elevated the entire U-MOF field. Uranium ; Property (philosophy) ; Metal-organic framework ; Function (biology) ; Energy (signal processing) ; Materials science ; Chemistry ; Physics ; Physical chemistry ; Metallurgy ; Epistemology Radioactive element chemistry and processing ; Metal-Organic Frameworks: Synthesis and Applications ; Nuclear Materials and Properties