jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Chen Wang | Qijiao He | Zheng Li | Jie Yu | Idris Temitope Bello | Keqing Zheng | Minfang Han | Meng Ni
Source: Applied Energy (article, 2023-12-16)
Field: Materials Science — Materials Chemistry

A novel in-tube reformer for solid oxide fuel cell for performance improvement and efficient thermal management: A numerical study based on artificial neural network and genetic algorithm Solid oxide fuel cell ; Artificial neural network ; Genetic algorithm ; Parametric statistics ; Surrogate model ; Engineering ; Materials science ; Mechanical engineering ; Computer science ; Anode ; Machine learning ; Chemistry ; Mathematics Advancements in Solid Oxide Fuel Cells ; Catalytic Processes in Materials Science ; Chemical Looping and Thermochemical Processes
Authors: Cesare Roncaglia | Riccardo Ferrando
Source: Journal of Chemical Information and Modeling (article, 2023-01-04)
Field: Materials Science — Materials Chemistry

Machine Learning Assisted Clustering of Nanoparticle Structures We propose a scheme for the automatic separation (i.e., clustering) of data sets composed of several nanoparticle (NP) structures by means of Machine Learning techniques. These data sets originate from atomistic simulations, such as global optimizations searches and molecular dynamics simulations, which can produce large outputs that are often difficult to inspect by hand. By combining a description of NPs based on their local atomic environment with unsupervised learning algorithms, such as K-Means and Gaussian mixture model, we are able to distinguish between different structural motifs (e.g., icosahedra, decahedra, polyicosahedra, fcc fragments, twins, and so on). We show that this method is able to improve over the results obtained previously thanks to the successful implementation of a more detailed description of NPs, especially for systems showing a large variety of structures, including disordered ones. Cluster analysis ; Computer science ; Molecular dynamics ; Gaussian ; Nanoparticle ; Unsupervised learning ; Artificial intelligence ; Mixture model ; Machine learning ; Nanotechnology ; Materials science ; Chemistry ; Computational chemistry Machine Learning in Materials Science ; nanoparticles nucleation surface interactions ; Surface Chemistry and Catalysis
Authors: Xinzhao Xu | Haoqin Zhang | Lin Shao | Rong Ma | Meng Guo | Yunqi Liu | Yan Zhao
Source: Angewandte Chemie International Edition (article, 2023-05-13)
Field: Materials Science — Polymers and Plastics

An Aqueous Electrolyte Gated Artificial Synapse with Synaptic Plasticity Selectively Mediated by Biomolecules The emulation of functions and behaviors of biological synapses using electronic devices has inspired the development of artificial neural networks (ANNs) in biomedical interfaces. Despite the achievements, artificial synapses that can be selectively responsive to non-electroactive biomolecules and directly operate in biological environments are still lacking. Herein, we report an artificial synapse based on organic electrochemical transistors and investigate the selective modulation of its synaptic plasticity by glucose. The enzymatic reaction between glucose and glucose oxidase results in long-term modulation of the channel conductance, mimicking selective binding of biomolecules to their receptors and consequent long-term modulation of the synaptic weight. Moreover, the device shows enhanced synaptic behaviors in the blood serum at a higher glucose concentration, which suggests its potential application in vivo as artificial neurons. This work provides a step towards the fabrication of ANNs with synaptic plasticity selectively mediated by biomolecules for neuro-prosthetics and human-machine interfaces. Biomolecule ; Synaptic plasticity ; Synapse ; Glucose oxidase ; Synaptic scaling ; Chemistry ; Nanotechnology ; Biophysics ; Metaplasticity ; Neuroscience ; Materials science ; Biosensor ; Biology ; Receptor ; Biochemistry Conducting polymers and applications ; Advanced Memory and Neural Computing ; Neuroscience and Neural Engineering
Authors: Zhijian He | Jinlin Peng | Chihou Lei | Shuhong Xie | Daifeng Zou | Yunya Liu
Source: Materials & Design (article, 2023-03-28)
Field: Materials Science — Materials Chemistry

Prediction of superior thermoelectric performance in unexplored doped-BiCuSeO via machine learning BiCuSeO compound is a promising thermoelectric material, which has attracted many experimental studies through trial-and-error approaches to improve its thermoelectric performance by element doping, such that a fast and efficient prediction of thermoelectric property for unexplored and rarely explored doped-BiCuSeO is highly desired. In this work, a machine learning (ML) model for predicting the ZT value of M element doped-BiCuSeO (Bi1-xMxCuSeO) has been established via the correlation analysis for descriptors and the comparison among different ML approaches. The results show that Gradient Boosting Regressor is the most appropriate approach for our ML model, which is well validated by comparing the predicted and experimental ZT values for the cases in the dataset. The ML model is also used to predict the ZT values of Bi1-xMxCuSeO with unexplored and rarely explored doping element M, and the optimal doping elements as well as their doping contents are screened out. The results indicate that the ZT of Bi0.86Po0.14CuSeO (Po-doped) and Bi0.88Cs0.12CuSeO (Cs-doped) are higher than that of pure BiCuSeO, and are improved by 104 % and 98 % at the 923 K, respectively. The enhancement is well explained by the first-principles calculations. The findings offer a guideline for exploring superior thermoelectric performance in BiCuSeO. Thermoelectric effect ; Materials science ; Doping ; Boosting (machine learning) ; Thermoelectric materials ; Machine learning ; Condensed matter physics ; Engineering physics ; Artificial intelligence ; Optoelectronics ; Composite material ; Computer science ; Thermodynamics ; Thermal conductivity ; Engineering ; Physics Advanced Thermoelectric Materials and Devices ; Machine Learning in Materials Science ; Gas Sensing Nanomaterials and Sensors
Authors: Lindong Ma | Meihui Liu | Xinyuan Zhou | Cancan Li | Tie Wang
Source: Materials Chemistry Frontiers (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Metal–organic framework-based SERS sensing platforms for life and health detection Schematic diagram of MOF-based SERS sensing platforms for life and health detection. Schematic ; Nanotechnology ; Materials science ; Metal-organic framework ; Diagram ; Computer science ; Chemistry ; Engineering ; Database ; Organic chemistry ; Electronic engineering Advanced Nanomaterials in Catalysis ; Nanoplatforms for cancer theranostics ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Elena Filonova | E. Yu. Pikalova
Source: Materials (review, 2023-07-12)
Field: Materials Science — Materials Chemistry

Overview of Approaches to Increase the Electrochemical Activity of Conventional Perovskite Air Electrodes The progressive research trends in the development of low-cost, commercially competitive solid oxide fuel cells with reduced operating temperatures are closely linked to the search for new functional materials as well as technologies to improve the properties of established materials traditionally used in high-temperature devices. Significant efforts are being made to improve air electrodes, which significantly contribute to the degradation of cell performance due to low oxygen reduction reaction kinetics at reduced temperatures. The present review summarizes the basic information on the methods to improve the electrochemical performance of conventional air electrodes with perovskite structure, such as lanthanum strontium manganite (LSM) and lanthanum strontium cobaltite ferrite (LSCF), to make them suitable for application in second generation electrochemical cells operating at medium and low temperatures. In addition, the information presented in this review may serve as a background for further implementation of developed electrode modification technologies involving novel, recently investigated electrode materials. Cobaltite ; Materials science ; Lanthanum ; Electrode ; Lanthanum manganite ; Electrochemistry ; Strontium ; Perovskite (structure) ; Oxide ; Nanotechnology ; Chemical engineering ; Inorganic chemistry ; Metallurgy ; Electrolyte ; Chemistry Advancements in Solid Oxide Fuel Cells ; Electronic and Structural Properties of Oxides ; Gas Sensing Nanomaterials and Sensors
Authors: Lin Gao | Mengge Wu | Xinge Yu | Junsheng Yu
Source: International Journal of Extreme Manufacturing (article, 2023-09-26)
Field: Materials Science — Polymers and Plastics

Device design principles and bioelectronic applications for flexible organic electrochemical transistors Abstract Organic electrochemical transistors (OECTs) exhibit significant potential for applications in healthcare and human-machine interfaces, due to their tunable synthesis, facile deposition, and excellent biocompatibility. Expanding OECTs to the flexible devices will significantly facilitate stable contact with the skin and enable more possible bioelectronic applications. In this work, we summarize the device physics of flexible OECTs, aiming to offer a foundational understanding and guidelines for material selection and device architecture. Particular attention is paid to the advanced manufacturing approaches, including photolithography and printing techniques, which establish a robust foundation for the commercialization and large-scale fabrication. And abundantly demonstrated examples ranging from biosensors, artificial synapses/neurons, to bioinspired nervous systems are summarized to highlight the considerable prospects of smart healthcare. In the end, the challenges and opportunities are proposed for flexible OECTs. The purpose of this review is not only to elaborate on the basic design principles of flexible OECTs, but also to act as a roadmap for further exploration of wearable OECTs in advanced bio-applications. Nanotechnology ; Computer science ; Materials science Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Organic Electronics and Photovoltaics
Authors: Camilo Andrés Guerrero-Martín | Daniel Montes | Mariana Meneses Motta da Silva | Erik Giovany Montes Páez | Laura Estefanía Guerrero-Martin | Raúl Salinas-Silva | Stefanny Camacho-Galindo | Elizabete F. Lucas | Alexandre Szklo
Source: Energies (review, 2023-06-21)
Field: Chemistry — Analytical Chemistry

Asphaltene Precipitation/Deposition Estimation and Inhibition through Nanotechnology: A Comprehensive Review Asphaltene precipitation/deposition is considered a problem of formation damage, which can reduce the oil recovery factor. In addition, asphaltenes can be deposited in pipelines and surface installations, causing serious complications in guaranteeing runoff, decreasing the production of oil wells. The precipitation of asphaltenes can be minimized by reducing the oil production flowrate or by using chemical inhibitors. Analyzing the stability and precipitation trend of asphaltenes in petroleum is vital for the guarantee of flow. For this purpose, several experimental and numerical methods have been proposed. Once the risk of precipitation is established, strategies can be formulated for the prevention and diagnosis of deposition problems in production or production training. The tests can be performed with dead oil, available in the wellhead, and help in understanding the behavior of the asphaltenes. This review aims to present (i) the problem related to the precipitation of asphaltenes; (ii) thermodynamic models of asphaltene precipitation; and (iii) asphaltene inhibition, control, and removal techniques using nanoparticles. Asphaltene ; Precipitation ; Deposition (geology) ; Flow assurance ; Petroleum engineering ; Wellhead ; Petroleum ; Oil production ; Environmental science ; Chemical engineering ; Materials science ; Geology ; Chemistry ; Sediment ; Engineering ; Meteorology ; Organic chemistry Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis
Authors: Heidar Javdani Esfahani | Shahrokh Shahhosseini | Ahad Ghaemi
Source: Scientific Reports (article, 2023-10-17)
Field: Chemistry — Inorganic Chemistry

Improved structure of Zr-BTC metal organic framework using NH2 to enhance CO2 adsorption performance Modified mesoporous NH<sub>2</sub>-Zr-BTC mixed ligand MOF nanocomposites were synthesized via the hydrothermal method as a novel adsorbent for CO<sub>2</sub> capture. The newly modified MOF-808 with NH<sub>2</sub> demonstrated a similar mesoporous morphology as MOF-808, whereas the specific surface area, pore volume, and average particle size, respectively, increased by 15%, 6%, and 46% compared to those of MOF-808. The characterization analyses exhibited the formation of more active groups on the adsorbent surface after modification. In addition, a laboratory adsorption setup was used to evaluate the effect of temperature, pressure, and NH<sub>2</sub> content on the CO<sub>2</sub> adsorption capacity in the range of 25-65 °C, 1-9 bar, and 0-20 wt%, respectively. An increase in pressure and a decrease in temperature enhanced the adsorption capacity. The highest equilibrium adsorption capacity of 369.11 mg/g was achieved at 25 °C, 9 bar, and 20 wt% NH<sub>2</sub>. By adding 20 wt% NH<sub>2</sub>, the maximum adsorption capacity calculated by the Langmuir model increased by about 4% compared to that of pure MOF-808. Moreover, Ritchie second-order and Sips models were the best-fitted models to predict the kinetics and isotherm data of CO<sub>2</sub> adsorption capacity with the high correlation coefficient (R<sup>2</sup> > 0.99) and AARE% of less than 0.1. The ΔH°, ΔS°, and ΔG° values were - 17.360 kJ/mol, - 0.028 kJ/mol K, and - 8.975 kJ/mol, respectively, demonstrating a spontaneous, exothermic, and physical adsorption process. Furthermore, the capacity of MH-20% sample decreased from 279.05 to 257.56 mg/g after 15 cycles, verifying excellent stability of the prepared mix-ligand MOF sorbent. Adsorption ; Mesoporous material ; Bar (unit) ; Langmuir adsorption model ; Metal-organic framework ; Exothermic reaction ; Specific surface area ; Chemistry ; Materials science ; Chemical engineering ; Analytical Chemistry (journal) ; Chromatography ; Physical chemistry ; Organic chemistry ; Catalysis Metal-Organic Frameworks: Synthesis and Applications ; Carbon Dioxide Capture Technologies ; Carbon dioxide utilization in catalysis
Authors: Alessandro Tofoni | Francesco Tavani | Marco Vandone | Luca Braglia | Elisa Borfecchia | Paolo Ghigna | Dragos Costantin Stoian | Toni Grell | Sara Stolfi | Valentina Colombo | P. D’Angelo
Source: Journal of the American Chemical Society (article, 2023-09-18)
Field: Chemistry — Inorganic Chemistry

Full Spectroscopic Characterization of the Molecular Oxygen-Based Methane to Methanol Conversion over Open Fe(II) Sites in a Metal–Organic Framework Iron-based enzymes efficiently activate molecular oxygen to perform the oxidation of methane to methanol (MTM), a reaction central to the contemporary chemical industry. Conversely, a very limited number of artificial catalysts have been devised to mimic this process. Herein, we employ the MIL-100(Fe) metal-organic framework (MOF), a material that exhibits isolated Fe sites, to accomplish the MTM conversion using O<sub>2</sub> as the oxidant under mild conditions. We apply a diverse set of advanced operando X-ray techniques to unveil how MIL-100(Fe) can act as a catalyst for direct MTM conversion. Single-phase crystallinity and stability of the MOF under reaction conditions (200 or 100 °C, CH<sub>4</sub> + O<sub>2</sub>) are confirmed by X-ray diffraction measurements. X-ray absorption, emission, and resonant inelastic scattering measurements show that thermal treatment above 200 °C generates Fe(II) sites that interact with O<sub>2</sub> and CH<sub>4</sub> to produce methanol. Experimental evidence-driven density functional theory (DFT) calculations illustrate that the MTM reaction involves the oxidation of the Fe(II) sites to Fe(III) via a high-spin Fe(IV)═O intermediate. Catalyst deactivation is proposed to be caused by the escape of CH<sub>3</sub><sup>•</sup> radicals from the relatively large MOF pore cages, ultimately resulting in the formation of hydroxylated triiron units, as proven by valence-to-core X-ray emission spectroscopy. The O<sub>2</sub>-based MTM catalytic activity of MIL-100(Fe) in the investigated conditions is demonstrated for two consecutive reaction cycles, proving the MOF potential toward active site regeneration. These findings will desirably lay the groundwork for the design of improved MOF catalysts for the MTM conversion. Chemistry ; Catalysis ; Methanol ; Crystallinity ; Methane ; Valence (chemistry) ; Density functional theory ; Metal-organic framework ; Oxygen ; Inorganic chemistry ; Chemical engineering ; Physical chemistry ; Crystallography ; Computational chemistry ; Organic chemistry ; Adsorption Metal-Organic Frameworks: Synthesis and Applications ; Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions
Authors: Matthew J. McDermott | Brennan C. McBride | C. Regier | Gia Thinh Tran | Yu Chen | Adam A. Corrao | Max C. Gallant | Gabrielle E. Kamm | Christopher J. Bartel | Karena W. Chapman | Peter G. Khalifah | Gerbrand Ceder | James R. Neilson | Kristin A. Persson
Source: ACS Central Science (article, 2023-10-16)
Field: Materials Science — Materials Chemistry

Assessing Thermodynamic Selectivity of Solid-State Reactions for the Predictive Synthesis of Inorganic Materials Synthesis is a major challenge in the discovery of new inorganic materials. Currently, there is limited theoretical guidance for identifying optimal solid-state synthesis procedures. We introduce two selectivity metrics, primary and secondary competition, to assess the favorability of target/impurity phase formation in solid-state reactions. We used these metrics to analyze 3520 solid-state reactions in the literature, ranking existing approaches to popular target materials. Additionally, we implemented these metrics in a data-driven synthesis planning workflow and demonstrated its application in the synthesis of barium titanate (BaTiO<sub>3</sub>). Using an 18-element chemical reaction network with first-principles thermodynamic data from the Materials Project, we identified 82985 possible BaTiO<sub>3</sub> synthesis reactions and selected 9 for experimental testing. Characterization of reaction pathways via synchrotron powder X-ray diffraction reveals that our selectivity metrics correlate with observed target/impurity formation. We discovered two efficient reactions using unconventional precursors (BaS/BaCl<sub>2</sub> and Na<sub>2</sub>TiO<sub>3</sub>) that produce BaTiO<sub>3</sub> faster and with fewer impurities than conventional methods, highlighting the importance of considering complex chemistries with additional elements during precursor selection. Our framework provides a foundation for predictive inorganic synthesis, facilitating the optimization of existing recipes and the discovery of new materials, including those not easily attainable with conventional precursors. Selectivity ; Characterization (materials science) ; Workflow ; Computer science ; Impurity ; Ranking (information retrieval) ; Materials science ; Nanotechnology ; Chemistry ; Machine learning ; Catalysis ; Organic chemistry ; Database Machine Learning in Materials Science ; Inorganic Chemistry and Materials ; X-ray Diffraction in Crystallography
Authors: Bo Hu | Lixue Gai | Yonglei Liu | Pan Wang | Shuping Yu | Li Zhu | Xijiang Han | Yunchen Du
Source: iScience (review, 2023-09-11)
Field: Materials Science — Electronic, Optical and Magnetic Materials

State-of-the-art in carbides/carbon composites for electromagnetic wave absorption Electromagnetic wave absorbing materials (EWAMs) have made great progress in the past decades, and are playing an increasingly important role in radiation prevention and antiradar detection due to their essential attenuation toward incident EM wave. With the flourish of nanotechnology, the design of high-performance EWAMs is not just dependent on the intrinsic characteristics of single-component medium, but pays more attention to the synergistic effects from different components to generate rich loss mechanisms. Among various candidates, carbides and carbon materials are usually labeled with the features of chemical stability, low density, tunable dielectric property, and diversified morphology/microstructure, and thus the combination of carbides and carbon materials will be a promising way to acquire new EWAMs with good practical application prospects. In this review, we introduce EM loss mechanisms related to dielectric composites, and then highlight the state-of-the-art progress in carbides/carbon composites as high-performance EWAMs, including silicon carbide/carbon, MXene/carbon, molybdenum carbide/carbon, as well as some uncommon carbides/carbon composites and multicomponent composites. The critical information regarding composition optimization, structural engineering, performance reinforcement, and structure-function relationship are discussed in detail. In addition, some challenges and perspectives for the development of carbides/carbon composites are also proposed after comparing the performance of some representative composites. Carbide ; Materials science ; Carbon fibers ; Composite material ; Microstructure ; Dielectric ; Silicon carbide ; Absorption (acoustics) ; Nanotechnology ; Composite number ; Optoelectronics Electromagnetic wave absorption materials ; Advanced Antenna and Metasurface Technologies ; MXene and MAX Phase Materials
Authors: Qingyi Wei | Qirong Dong | Hongbin Pu
Source: Biosensors (review, 2023-02-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multiplex Surface-Enhanced Raman Scattering: An Emerging Tool for Multicomponent Detection of Food Contaminants For survival and quality of human life, the search for better ways to ensure food safety is constant. However, food contaminants still threaten human health throughout the food chain. In particular, food systems are often polluted with multiple contaminants simultaneously, which can cause synergistic effects and greatly increase food toxicity. Therefore, the establishment of multiple food contaminant detection methods is significant in food safety control. The surface-enhanced Raman scattering (SERS) technique has emerged as a potent candidate for the detection of multicomponents simultaneously. The current review focuses on the SERS-based strategies in multicomponent detection, including the combination of chromatography methods, chemometrics, and microfluidic engineering with the SERS technique. Furthermore, recent applications of SERS in the detection of multiple foodborne bacteria, pesticides, veterinary drugs, food adulterants, mycotoxins and polycyclic aromatic hydrocarbons are summarized. Finally, challenges and future prospects for the SERS-based detection of multiple food contaminants are discussed to provide research orientation for further. Food safety ; Contamination ; Biochemical engineering ; Food chain ; Human health ; Environmental science ; Chemometrics ; Multiplex ; Aflatoxin ; Environmental chemistry ; Food quality ; Nanotechnology ; Chemistry ; Food science ; Materials science ; Chromatography ; Biology ; Medicine ; Bioinformatics Gold and Silver Nanoparticles Synthesis and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Biosensors and Analytical Detection