jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mengxian Yu | Qingzhu Jia | Qiang Wang | Zheng‐Hong Luo | Fangyou Yan | Yin‐Ning Zhou
Source: Chemical Science (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Data science-centric design, discovery, and evaluation of novel synthetically accessible polyimides with desired dielectric constants Rapidly advancing computer technology has demonstrated great potential in recent years to assist in the generation and discovery of promising molecular structures. Herein, we present a data science-centric "Design-Discovery-Evaluation" scheme for exploring novel polyimides (PIs) with desired dielectric constants (<i>ε</i>). A virtual library of over 100 000 synthetically accessible PIs is created by extending existing PIs. Within the framework of quantitative structure-property relationship (QSPR), a model sufficient to predict <i>ε</i> at multiple frequencies is developed with an <i>R</i> <sup>2</sup> of 0.9768, allowing further high-throughput screening of the prior structures with desired <i>ε</i>. Furthermore, the structural feature representation method of atomic adjacent group (AAG) is introduced, using which the reliability of high-throughput screening results is evaluated. This workflow identifies 9 novel PIs (<i>ε</i> >5 at 10<sup>3</sup> Hz and glass transition temperatures between 250 °C and 350 °C) with potential applications in high-temperature capacitive energy storage, and confirms these promising findings by high-fidelity molecular dynamics (MD) simulations. Dielectric ; Constant (computer programming) ; Computer science ; Materials science ; Nanotechnology ; Data science ; Optoelectronics ; Programming language Synthesis and properties of polymers ; Epoxy Resin Curing Processes ; Dielectric materials and actuators
Authors: Anusuya Pal | Amalesh Gope
Source: The European Physical Journal E (article, 2024-05-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Texture identification in liquid crystal-protein droplets using evaporative drying, generalized additive modeling, and K-means Clustering Sessile drying droplets manifest distinct morphological patterns, encompassing diverse systems, viz., DNA, proteins, blood, and protein-liquid crystal (LC) complexes. This study employs an integrated methodology that combines drying droplet, image texture analysis (features from First Order Statistics, Gray Level Co-occurrence Matrix, Gray Level Run Length Matrix, Gray Level Size Zone Matrix, and Gray Level Dependence Matrix), and statistical data analysis (Generalized Additive Modeling and K-means clustering). It provides a comprehensive qualitative and quantitative exploration by examining LC-protein droplets at varying initial phosphate buffered concentrations (0x, 0.25x, 0.5x, 0.75x, and 1x) during the drying process under optical microscopy with crossed polarizing configuration. Notably, it unveils distinct LC-protein textures across three drying stages: initial, middle, and final. The Generalized Additive Modeling (GAM) reveals that all the features significantly contribute to differentiating LC-protein droplets. Integrating the K-means clustering method with GAM analysis elucidates how textures evolve through the three drying stages compared to the entire drying process. Notably, the final drying stage stands out with well-defined, non-overlapping clusters, supporting the visual observations of unique LC textures. Furthermore, this paper contributes valuable insights, showcasing the efficacy of drying droplets as a rapid and straightforward tool for characterizing and classifying dynamic LC textures. Cluster analysis ; Texture (cosmology) ; Biological system ; Matrix (chemical analysis) ; Chemistry ; Gray level ; Materials science ; Chromatography ; Artificial intelligence ; Pattern recognition (psychology) ; Crystallography ; Computer science ; Image (mathematics) ; Biology Liquid Crystal Research Advancements ; Computer Graphics and Visualization Techniques ; Nanomaterials and Printing Technologies
Authors: Irsa Zulfiqar | Sania Gul | Hafiz Aamir Sohail | Iqra Rabani | Saima Gul | Malik Abdul Rehman | Saikh Mohammad Wabaidur | Muhammad Yasir | Inam Ullah | Muhammad Asghar Khan | Shania Rehman | Muhammad Farooq Khan
Source: Nanotechnology Reviews (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Single flake homo p–n diode of MoTe <sub>2</sub> enabled by oxygen plasma doping Abstract Two-dimensional (2D) materials play a crucial role as fundamental electrical components in modern electronics and optoelectronics next-generation artificial intelligent devices. This study presents a methodology for creating a laterally uniform p–n junction by using a partial oxygen plasma-mediated strategy to introduce p-type doping in single channel MoTe 2 device. The MoTe 2 field effect transistors (FETs) show high electron mobility of about ∼23.54 cm 2 V −1 s −1 and a current ON/OFF ratio of ∼10 6 while p-type FETs show hole mobility of about ∼9.25 cm 2 V −1 s −1 and current ON/OFF ratio ∼10 5 along with artificially created lateral MoTe 2 p–n junction, exhibited a rectification ratio of ∼10 2 and ideality factor of ∼1.7 which is proximity to ideal-like diode. Thus, our study showed a diversity in the development of low-power nanoelectronics of next-generation integrated circuits. Nanoelectronics ; Diode ; Doping ; Materials science ; Transistor ; Optoelectronics ; Rectification ; Electron mobility ; Plasma ; Nanotechnology ; Electronics ; Electrical engineering ; Physics ; Voltage ; Engineering 2D Materials and Applications ; Graphene research and applications ; Ferroelectric and Negative Capacitance Devices
Authors: M. Gjoka | C. Sarafidis | Stefanos Giaremis
Source: Materials (article, 2024-02-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Towards Production of Cost-Effective Modification of SmCo5-Type Alloys Suitable for Permanent Magnets SmCo<sub>5</sub> constitutes one of the strongest classes of permanent magnets, which exhibit magnetocrystalline anisotropy with uniaxial character and enormous energy and possess high Curie temperature. However, the performance of SmCo<sub>5</sub> permanent magnets is hindered by a limited energy product and relatively high supply risk. Sm is a moderately expensive element within the lanthanide group, while Co is a more expensive material than Fe, making SmCo<sub>5</sub>-based permanent magnets among the most expensive materials in the group. Subsequently, the need for new materials with less content in critical and thus expensive resources is obvious. A promising path of producing new compounds that meet these requirements is the chemical modification of established materials used in PM towards the reduction of expensive resources, for example, reducing Co content with transition metals (like Fe, Ni) or using as substitutes raw rare earth materials with greater abundance than global demand, like Ce and La. Important instruments to achieve these goals are theoretical calculations, such as ab initio methods and especially DFT-based calculations, in predicting possible stable RE-TM intermetallic compounds and their magnetic properties. This review aims to present the progress of recent years in the production of improved SmCo<sub>5</sub>-type magnets. Magnet ; Intermetallic ; Magnetocrystalline anisotropy ; Materials science ; Raw material ; Lanthanide ; Curie temperature ; Engineering physics ; Process engineering ; Metallurgy ; Mechanical engineering ; Condensed matter physics ; Magnetic anisotropy ; Ferromagnetism ; Alloy ; Chemistry ; Magnetic field ; Physics ; Magnetization ; Organic chemistry ; Engineering Magnetic Properties of Alloys ; Magnetic and transport properties of perovskites and related materials ; Rare-earth and actinide compounds
Authors: Xiaoqi Zhang | Kevin Maik Jablonka | Berend Smit
Source: Digital Discovery (article, 2024-01-01)
Field: Chemistry — Inorganic Chemistry

Deep learning-based recommendation system for metal–organic frameworks (MOFs) This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a high-dimensional chemical space and suggests a pool of promising materials for specific applications based on user-endorsed MOFs with similarity analysis. This proposed approach significantly reduces the need for exhaustive labeling of every material in the database, focusing instead on a select fraction for in-depth investigation. Ranging from methane storage and carbon capture to quantum properties, this study illustrates the system's adaptability to various applications. Metal-organic framework ; Deep learning ; Artificial intelligence ; Computer science ; Materials science ; Chemistry ; Adsorption ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Machine Learning in Materials Science ; Covalent Organic Framework Applications
Authors: Shreyas Srivatsa | W. Tokarz | J. Przewoźnik | Tomasz Strączek | Krzysztof Grabowski | Paweł Rutkowski | Tadeusz Uhl | J. Kulawik | Dariusz Kata | Dominika Madej | Jerzy Lis | Cz. Kapusta
Source: Materials (article, 2024-05-08)
Field: Materials Science — Materials Chemistry

Temperature Evolution of Composition, Thermal, Electrical and Magnetic Properties of Ti3C2Tx-MXene MXenes are a family of two-dimensional nanomaterials. Titanium carbide MXene (Ti3C2Tx-MXene), reported in 2011, is the first inorganic compound reported among the MXene family. In the present work, we report on the study of the composition and various physical properties of Ti3C2Tx-MXene nanomaterial, as well as their temperature evolution, to consider MXenes for space applications. X-ray diffraction, thermal analysis and mass spectroscopy measurements confirmed the structure and terminating groups of the MXene surface, revealing a predominant single OH layer character. The temperature dependence of the specific heat shows a Debye-like character in the measured range of 2 K–300 K with a linear part below 10 K, characteristic of conduction electrons of metallic materials. The electron density of states (DOS) calculations for Ti3C2OH-MXene reveal a significant DOS value at the Fermi level, with a large slope, confirming its metallic character, which is consistent with the experimental findings. The temperature dependence of electrical resistivity of the MXene samples was tested for a wide temperature range (3 K–350 K) and shows a decrease on lowering temperature with an upturn at low temperatures, where negative magnetoresistance is observed. The magnetoresistance versus field is approximately linear and increases its magnitude with decreasing temperature. The magnetization curves are straight lines with temperature-independent positive slopes, indicating Pauli paramagnetism due to conduction electrons. Materials science ; Thermal ; Composition (language) ; Thermodynamics ; Physics ; Philosophy MXene and MAX Phase Materials ; 2D Materials and Applications ; Advanced Memory and Neural Computing
Authors: Anastasia Barnes | Mohammad M. Afroz | Yun Kyung Shin | Adri C. T. van Duin | Katie Li-Oakey
Source: Journal of Membrane Science (article, 2024-02-29)
Field: Materials Science — Materials Chemistry

Mapping TpPa-1 covalent organic framework (COF) molecular interactions in mixed solvents via atomistic modeling and experimental study Permeance ; Nanofiltration ; Membrane ; Crystallinity ; Solvent ; Mass transfer ; Molecular dynamics ; Adsorption ; Chemical engineering ; Chemistry ; Covalent organic framework ; Filtration (mathematics) ; Membrane technology ; Force field (fiction) ; Polymer ; Materials science ; Covalent bond ; Chemical physics ; Organic chemistry ; Computational chemistry ; Chromatography ; Computer science ; Crystallography Covalent Organic Framework Applications ; Membrane Separation Technologies ; Membrane Separation and Gas Transport
Authors: Vitaly Goranov
Source: Biomaterials and Biosystems (article, 2024-08-31)
Field: Materials Science — Biomaterials

Biomaterials functionalized with magnetic nanoparticles for tissue engineering: Between advantages and challenges The integration of magnetic nanoparticles (MNPs) into biomaterials offers exciting opportunities for tissue engineering as they enable better control over cell guidance, release of bioactive factors and tissue maturation. Despite their potential, challenges such as the heterogeneity of MNPs, their cytotoxicity and the need for precise control of MNP`s properties hinder their widespread application. Overcoming these challenges will require new interdisciplinary efforts and technological advances, including the development of mathematical tools and additional elaborations to ensure the biocompatibility of MNPs. Magnetic nanoparticles ; Nanotechnology ; Tissue engineering ; Biocompatibility ; Nanoparticle ; Materials science ; Biochemical engineering ; Engineering ; Biomedical engineering Nanoparticle-Based Drug Delivery ; Electrospun Nanofibers in Biomedical Applications ; Bone Tissue Engineering Materials
Authors: Carl H. Fleischer | Sean T. Holmes | Kirill Levin | Stanislav L. Veinberg | Robert W. Schurko
Source: Faraday Discussions (article, 2024-06-24)
Field: Chemistry — Spectroscopy

Characterization of ephedrine HCl and pseudoephedrine HCl using quadrupolar NMR crystallography guided crystal structure prediction Quadrupolar NMR crystallography guided crystal structure prediction (QNMRX-CSP) is a nascent protocol for predicting, solving, and refining crystal structures. QNMRX-CSP employs a combination of solid-state NMR data from quadrupolar nuclides (<i>i.e.</i>, nuclear spin >1/2), static lattice energies and electric field gradient (EFG) tensors from dispersion-corrected density functional theory (DFT-D2*) calculations, and powder X-ray diffraction (PXRD) data; however, it has so far been applied only to organic HCl salts with small and rigid organic components, using <sup>35</sup>Cl EFG tensor data for both structural refinement and validation. Herein, QNMRX-CSP is extended to ephedrine HCl (Eph) and pseudoephedrine HCl (Pse), which are diastereomeric compounds that feature distinct space groups and organic components that are larger and more flexible. A series of benchmarking calculations are used to generate structural models that are validated against experimental data, and to explore the impacts of the: (i) starting structural models (<i>i.e</i>., geometry-optimized fragments based on either a known crystal structure or an isolated gas-phase molecule) and (ii) selection of unit cell parameters and space groups. Finally, we use QNMRX-CSP to predict the structure of Pse in the dosage form Sudafed® using only <sup>35</sup>Cl SSNMR data as experimental input. This proof-of-concept work suggests the possibility of employing QNMRX-CSP to solve the structures of organic HCl salts in dosage forms - something which is often beyond the capabilities of conventional, diffraction-based characterization methods. Crystal structure ; Pseudoephedrine ; Chemistry ; Nuclide ; Crystallography ; Crystal (programming language) ; Solid-state nuclear magnetic resonance ; Solid-state ; Materials science ; Ephedrine ; Physical chemistry ; Nuclear magnetic resonance ; Physics ; Computer science Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Molecular spectroscopy and chirality
Authors: Aleksandra Sknepnek | Suzana Filipović | Vladimir B. Pavlović | Nemanja Mirković | Dunja Miletić | Jelena Gržetić | Miljana Mirković
Source: Polymers (article, 2024-02-07)
Field: Materials Science — Biomaterials

Effects of Synthesis Parameters on Structure and Antimicrobial Properties of Bacterial Cellulose/Hydroxyapatite/TiO2 Polymer–Ceramic Composite Material Bacterial cellulose (BC) is a highly pure polysaccharide biopolymer that can be produced by various bacterial genera. Even though BC lacks functional properties, its porosity, three-dimensional network, and high specific surface area make it a suitable carrier for functional composite materials. In the present study, BC-producing bacteria were isolated from kombucha beverage and identified using a molecular method. Two sets of the BC hydrogels were produced in static conditions after four and seven days. Afterwards, two different synthesis pathways were applied for BC functionalization. The first method implied the incorporation of previously synthesized HAp/TiO<sub>2</sub> nanocomposite using an immersion technique, while the second method included the functionalization of BC during the synthesis of HAp/TiO<sub>2</sub> nanocomposite in the reaction mixture. The primary goal was to find the best method to obtain the functionalized material. Physicochemical and microstructural properties were analyzed by SEM, EDS, FTIR, and XRD methods. Further properties were examined by tensile test and thermogravimetric analysis, and antimicrobial activity was assessed by a total plate count assay. The results showed that HAp/TiO<sub>2</sub> was successfully incorporated into the produced BC hydrogels using both methods. The applied methods of incorporation influenced the differences in morphology, phase distribution, mechanical and thermal properties, and antimicrobial activity against <i>Staphylococcus aureus</i> (ATCC 25923), <i>Escherichia coli</i> (ATCC 25922), <i>Proteus mirabilis</i> (ATCC 12453), and <i>Candida albicans</i> (ATCC 10231). Composite material can be recommended for further development and application in environments that are suitable for diseases spreading. Bacterial cellulose ; Nanocomposite ; Self-healing hydrogels ; Materials science ; Thermogravimetric analysis ; Surface modification ; Ultimate tensile strength ; Composite number ; Cellulose ; Antimicrobial ; Chemical engineering ; Fourier transform infrared spectroscopy ; Biopolymer ; Ceramic ; Polymer ; Composite material ; Nuclear chemistry ; Chemistry ; Polymer chemistry ; Organic chemistry Advanced Cellulose Research Studies ; Nanoparticles: synthesis and applications ; Nanocomposite Films for Food Packaging
Authors: Wenwen Zhang | Mingxuan Pan | Peng Wang | Xue Jiao | Xinghu Zhou | Wenke Sun | Yadong Hu | Zhaopeng Shen
Source: Foods (article, 2024-09-24)
Field: Chemistry — Analytical Chemistry

Comparative Analysis of XGB, CNN, and ResNet Models for Predicting Moisture Content in Porphyra yezoensis Using Near-Infrared Spectroscopy This study explored the performance and reliability of three predictive models-extreme gradient boosting (XGB), convolutional neural network (CNN), and residual neural network (ResNet)-for determining the moisture content in <i>Porphyra yezoensis</i> using near-infrared (NIR) spectroscopy. We meticulously selected 380 samples from various sources to ensure a comprehensive dataset, which was then divided into training (300 samples) and test sets (80 samples). The models were evaluated based on prediction accuracy and stability, employing genetic algorithms (GA) and partial least squares (PLS) for wavelength selection to enhance the interpretability of feature extraction outcomes. The results demonstrated that the XGB model excelled with a determination coefficient (R<sup>2</sup>) of 0.979, a root mean square error of prediction (RMSEP) of 0.004, and a high ratio of performance to deviation (RPD) of 4.849, outperforming both CNN and ResNet models. A Gaussian process regression (GPR) was employed for uncertainty assessment, reinforcing the reliability of our models. Considering the XGB model's high accuracy and stability, its implementation in industrial settings for quality assurance is recommended, particularly in the food industry where rapid and non-destructive moisture content analysis is essential. This approach facilitates a more efficient process for determining moisture content, thereby enhancing product quality and safety. Interpretability ; Partial least squares regression ; Feature selection ; Mean squared error ; Reliability (semiconductor) ; Artificial intelligence ; Convolutional neural network ; Computer science ; Artificial neural network ; Pattern recognition (psychology) ; Near-infrared spectroscopy ; Biological system ; Statistics ; Mathematics ; Machine learning ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: József Prokisch | Gréta Törős | Duyen H. H. Nguyen | Chaima Neji | Aya Ferroudj | Daniella Sári | Arjun Muthu | Eric C. Brevik | Hassan El-Ramady
Source: Agronomy (article, 2024-03-18)
Field: Materials Science — Materials Chemistry

Nano-Food Farming: Toward Sustainable Applications of Proteins, Mushrooms, Nano-Nutrients, and Nanofibers The relationship between agriculture and food is very close. It is impossible to produce adequate crops for global food security without proper farm management. Farming practices represent direct and indirect controlling factors in terms of global food security. Farming management practices influence agro-food production from seed germination through to the post-harvest treatments. Nano-farming utilizes nanotechnologies for agricultural food production. This review covers four key components of nano-farming: nano-mushroom production, protein-based nanoparticles, nano-nutrients, and nanofibers. This provides a comprehensive overview of the potential applications of nanotechnology in agriculture. The role of these components will be discussed in relation to the challenges faced and solutions required to achieve sustainable agricultural production. Edible mushrooms are important to food security because they are a nutritious food source and can produce nanoparticles that can be used in the production of other food sources. Protein-based nanoparticles have considerable potential in the delivery of bioactives as carriers and other applications. Nano-nutrients (mainly nano-selenium, nano-tellurium and carbon nanodots) have crucial impacts on the nutrient status of plant-based foods. Carbon nanodots and other carbon-based nanomaterials have the potential to influence agricultural crops positively. There are promising applications of nanofibers in food packaging, safety and processing. However, further research is needed to understand the impacts and potential risks of nanomaterials in the food production system. Nano- ; Nanofiber ; Agriculture ; Nutrient ; Food systems ; Sustainable agriculture ; Nanotechnology ; Materials science ; Chemistry ; Food security ; Biology ; Ecology ; Composite material ; Organic chemistry Nanoparticles: synthesis and applications ; Proteins in Food Systems ; Carbon and Quantum Dots Applications