jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yuandong Xu | Yingying Ben | Lili Sun | Jishan Su | Hui Guo | Rongjia Zhou | Yaqing Wei | Yajun Wei | Yongjuan Lu | Yizhan Sun | Xia Zhang
Source: Physical Chemistry Chemical Physics (article, 2023-12-29)
Field: Materials Science — Polymers and Plastics

Sensing platform for the highly sensitive detection of catechol based on composite coupling with conductive Ni<sub>3</sub>(HITP)<sub>2</sub> and nanosilvers Catechol, which has a high toxicity and low degradability, poses significant risks to both human health and the environment. Tracking of catechol residues is essential to protect human health and to assess the safety of the environment. We constructed sensing platforms to detect catechol based on the conductive metal-organic frameworks [Ni<sub>3</sub>(HITP)<sub>2</sub>] and their nanosilver composites. The reduction process of catechol at the Ni<sub>3</sub>(HITP)<sub>2</sub>/AgNP electrode is chemically irreversible as a result of the difference in compatibility of the oxidation stability and conductivity between the Ni<sub>3</sub>(HITP)<sub>2</sub>/AgNS and Ni<sub>3</sub>(HITP)<sub>2</sub>/AgNP electrodes. The electrochemical results show that the Ni<sub>3</sub>(HITP)<sub>2</sub>/AgNS electrode presents a lower detection limit of 0.053 μM and better sensitivity, reproducibility and repeatability than the Ni<sub>3</sub>(HITP)<sub>2</sub>/AgNP electrode. The kinetic mechanism of the catechol electrooxidation at the surface of the electrode is controlled by diffusion through a 2H<sup>+</sup>/2e<sup>-</sup> process. The transfer coefficient is the key factor used to illustrate this process. During the electrochemical conversion of phenol to ketone, more than half of Δ<i>G</i> is used to change the activation energy. We also studied the stability, anti-interference and reproducibility of these electrode systems. Catechol ; Composite number ; Electrical conductor ; Phenol ; Coupling (piping) ; Diffusion ; Materials science ; Chemistry ; Chemical engineering ; Nanotechnology ; Combinatorial chemistry ; Chemical physics ; Composite material ; Organic chemistry ; Thermodynamics ; Physics ; Engineering Conducting polymers and applications ; Electrochemical sensors and biosensors ; Electrochemical Analysis and Applications
Authors: Wenbin Xu | Elias Diesen | Tianwei He | Karsten Reuter | Johannes T. Margraf
Source: ChemRxiv (preprint, 2023-11-17)
Field: Materials Science — Materials Chemistry

Discovering high entropy alloy electrocatalysts in vast composition spaces with multi-objective optimization High entropy alloys (HEAs) are a highly promising class of materials for electrocatalysis, as their unique active site distributions break the scaling relations that limit the activity of conventional transition metal catalysts. Existing Bayesian optimization (BO) based virtual screening approaches focus on catalytic activity as sole objective and correspondingly tend to identify promising materials that are unlikely to be entropically stabilized. Here, we overcome this limitation with a multi-objective BO framework for HEAs that simultaneously targets activity, cost-effectiveness and entropic stabilization. With a diversity-guided batch selection further boosting the data efficiency, the framework readily identifies numerous promising candidates for the oxygen reduction reaction that strike the balance between all three objectives in hitherto unchartered HEA design spaces comprising up to ten elements. High entropy alloys ; Bayesian optimization ; Boosting (machine learning) ; Computer science ; Electrocatalyst ; Entropy (arrow of time) ; Scaling ; Alloy ; Materials science ; Biochemical engineering ; Nanotechnology ; Chemistry ; Artificial intelligence ; Engineering ; Mathematics ; Thermodynamics ; Metallurgy Machine Learning in Materials Science ; Electrocatalysts for Energy Conversion ; High Entropy Alloys Studies
Authors: Ekaterina V. Sukhanova | Nursultan E. Sagatov | Aleksandr S. Oreshonkov | Pavel N. Gavryushkin | Захар И. Попов
Source: Nanomaterials (article, 2023-01-16)
Field: Materials Science — Materials Chemistry

Halogen-Doped Chevrel Phase Janus Monolayers for Photocatalytic Water Splitting Chevrel non-van der Waals crystals are promising candidates for the fabrication of novel 2D materials due to their versatile crystal structure formed by covalently bonded (Mo<sub>6</sub>X<sub>8</sub>) clusters (X-chalcogen atom). Here, we present a comprehensive theoretical study of the stability and properties of Mo-based Janus 2D structures with Chevrel structures consisting of chalcogen and halogen atoms via density functional theory calculations. Based on the analysis performed, we determined that the S<sub>2</sub>Mo<sub>3</sub>I<sub>2</sub> monolayer is the most promising structure for overall photocatalytic water-splitting application due to its appropriate band alignment and its ability to absorb visible light. The modulated Raman spectra for the representative structures can serve as a blueprint for future experimental verification of the proposed structures. Chalcogen ; Janus ; Raman spectroscopy ; Monolayer ; van der Waals force ; Materials science ; Density functional theory ; Photocatalysis ; Halogen ; Crystal structure ; Covalent bond ; Doping ; Crystallography ; Nanotechnology ; Chemical physics ; Chemistry ; Computational chemistry ; Molecule ; Optoelectronics ; Optics ; Physics 2D Materials and Applications ; MXene and MAX Phase Materials ; Advanced Photocatalysis Techniques
Authors: Kamal Choudhary | Daniel Wines | Kangming Li | Kevin F. Garrity | Vishu Gupta | A. Romero | Jaron T. Krogel | Kayahan Saritas | Addis Fuhr | Panchapakesan Ganesh | Paul R. C. Kent | Keqiang Yan | Yuchao Lin | Shuiwang Ji | Ben Blaiszik | Patrick Reiser | Pascal Friederich | Ankit Agrawal | Pratyush Tiwary | Eric R. Beyerle | Peter Minch | Trevor David Rhone | Ichiro Takeuchi | Robert B. Wexler | Arun Mannodi‐Kanakkithodi | Elif Ertekin | Avanish Mishra | Nithin Mathew | Sterling G. Baird | Mitchell Wood | Andrew Rohskopf | Jason Hattrick‐Simpers | Shih‐Han Wang | Luke E. K. Achenie | Hongliang Xin | Maureen Williams | Adam J. Biacchi | Francesca Tavazza
Source: arXiv (Cornell University) (preprint, 2023-06-20)
Field: Materials Science — Materials Chemistry

JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboard Benchmarking ; Benchmark (surveying) ; Computer science ; NIST ; Set (abstract data type) ; Code (set theory) ; Computer engineering ; Data mining ; Data science ; Theoretical computer science Machine Learning in Materials Science ; Electronic and Structural Properties of Oxides ; Electron and X-Ray Spectroscopy Techniques
Authors: Hongyu Li | Hong Zhang | Xuelong Wang | Ralph G. Nuzzo | Anatoly I. Frenkel | Ping Liu | Dilip Gersappe
Source: The Journal of Physical Chemistry C (article, 2023-11-03)
Field: Materials Science — Materials Chemistry

Revealing Intermetallic Active Sites of PtNi Nanocatalysts for Reverse Water Gas Shift Reaction Bimetallic nanoparticles have gained great interest due to their potential applications in catalysis. By combining Lattice Boltzmann Modeling (LBM), Density Functional Theory (DFT) calculations, and kinetic Monte Carlo (KMC) simulation, here we rationalize the superior performance of supported Pt–Ni alloy nanostructures over Pt and Ni alone during the reverse Water Gas Shift (rWGS) reaction, which was observed previously. The LBM simulation including the diffusion and flow of the reacting gas molecules within the supporting nanoporous channels in SBA-15 indicates that the simple combination of contributions from Ni and Pt alone is not enough to result in the observed promotion in rWGS activity and selectivity of the Pt–Ni alloy. Instead, the synergy between Pt and Ni via a unique intermetallic motif is responsible according to the DFT and KMC simulation. Compared to the monometallic counterparts, the intermetallic-introduced ensemble effect at the low-coordinated Pt–Ni hybrid site of Pt–Ni alloy nanocatalysts enables the enhanced activation of CO2 and promoted removal of CO/H2O as gas phase product. Nanomaterial-based catalyst ; Intermetallic ; Bimetallic strip ; Water-gas shift reaction ; Alloy ; Materials science ; Catalysis ; Nanoclusters ; Density functional theory ; Kinetic Monte Carlo ; Chemical engineering ; Nanoparticle ; Chemistry ; Nanotechnology ; Computational chemistry ; Metal ; Monte Carlo method ; Metallurgy Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; Lattice Boltzmann Simulation Studies
Authors: A. Guillermo Bracamonte
Source: Recent Progress in Materials (article, 2023-12-26)
Field: Materials Science — Materials Chemistry

Quantum Semiconductors Based on Carbon Materials for Nanophotonics and Photonics Applications by Electron Shuttle and Near Field Phenomena This review intended to resume key Research reports and publications that open many themes and topics related to Carbon-based semiconductors and Quantum emitters. The Design and synthesis of highly pure materials such as Graphene, Carbon Nanotubes, fullerenes, and other Carbon-based allotropes were shown. They presented their most important and promising properties concerning new studies and developments in photonics. Carbon-based Quantum dots, semiconductors, and higher sized Nanoplatforms allowed us to discuss fundamental studies and perspectives within varied applications. In this context, relevant developments from literature related to electron transfer within various targeted processes, where energy and light transfers occurred through different optical active materials and platforms, were highlighted and discussed. Therefore, many approaches that tuned the desired Optical active properties were shown. Thus, Hybrid materials from single Quantum and Nanoplatforms towards modified substrates were incorporated within varied media such as colloidal dispersions, solid devices, and waveguides. Moreover, Heterojunctions and applications such as energy harvesters and emitter devices were also presented. This manner highlighted varied topics of Photonics' leading current status, perspectives, and implications in Nanophotonics, Quantum photonics, and Optical lenses. Further views and commentaries about Green Photonics were presented as well. Nanophotonics ; Photonics ; Nanotechnology ; Materials science ; Carbon nanotube ; Graphene ; Heterojunction ; Semiconductor ; Engineering physics ; Quantum dot ; Optoelectronics ; Physics Carbon Nanotubes in Composites ; Graphene research and applications ; Fullerene Chemistry and Applications
Authors: Siti Nabilla Aliya Mohd Nizar | Mohd Mustaqim Rosli | Siti Azrah Mohamad Samsuri | Ibrahim Abdul Razak | Suhana Arshad
Source: Physica Scripta (article, 2023-12-02)
Field: Materials Science — Materials Chemistry

Research perspectives on the structure-property relationship of polyaromatic pyrene-based chalcone derivatives as dye-sensitizers in DSSC applications Abstract Photovoltaic studies in DSSC have continued to be fascinated by chalcone derivatives because of their straightforward synthesis, green synthetic process and low toxicity properties using Claisen-Schmidt condensation method. In this report, the implementation of the newly synthesized pyrenyl chalcone derivatives, Py1 and Py2 as dye-sensitizers and the characterization studies are further discussed. The grown crystals are characterized via several spectroscopic analyses such as ATR, 1 H and 13 C NMR and UV–vis analyses. The UV–vis analysis shows a lower energy gap in Py1 (2.79 eV) in comparison to Py2 (2.90 eV) which further indicates better flow of charge transfer. The analysis of crystal packing reveals the arrangement of head-to-head by intermolecular π — π contacts and head-to-tail via intermolecular C–H···O interactions in Py1 and Py2 , respectively. The intermolecular interactions act to stabilize the crystal structure and further improve the charge transfer within the dyes and enhancement of DSSC efficiency. In electrochemical analysis using cyclic voltammetry (CV), Py1 and Py2 are found in the suitable HOMO and LUMO energy levels which confirms their applicability as photosensitizer materials. After the fabrication process, DSSC layers are continued for FESEM and EDX analyses before proceeding for the performance study. The Py1 with D- π -A architecture has significantly revealed a higher efficiency than D- π -D structure of Py2 . Dye-sensitized solar cell ; Intermolecular force ; Chalcone ; Materials science ; Cyclic voltammetry ; Photosensitizer ; HOMO/LUMO ; Photochemistry ; Band gap ; Chemistry ; Electrochemistry ; Organic chemistry ; Molecule ; Physical chemistry ; Optoelectronics Photochromic and Fluorescence Chemistry ; Free Radicals and Antioxidants ; Conducting polymers and applications
Authors: Zilin Yan | Yan Gao | Haibo Zhang
Source: Applied Sciences (article, 2023-10-04)
Field: Materials Science — Ceramics and Composites

Materials Development and Potential Applications of Ceramics: New Opportunities and Challenges Ceramics have been an indispensable part of human civilization for thousands of years [...] Materials science Advanced ceramic materials synthesis ; Advanced materials and composites ; Bone Tissue Engineering Materials
Authors: Puck van Gerwen | Ksenia R. Briling | Yannick Calvino Alonso | Malte Franke | Clémence Corminbœuf
Source: ChemRxiv (preprint, 2023-09-04)
Field: Materials Science — Materials Chemistry

Benchmarking machine-readable vectors of chemical re- actions on computed activation barriers In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based models to methods based on the three-dimensional structure of reactants and products. In tandem, many representations have been developed to predict experimental targets, which may hold promise for barrier prediction as well. Here, we bring together all of these efforts and benchmark various methods (CGR, SLATMd , B2R2l , MFPs, DRFP and RXNFP) for the prediction of computed activation barriers on three diverse datasets Benchmarking ; Benchmark (surveying) ; Computer science ; Graph ; Machine learning ; Artificial intelligence ; Theoretical computer science ; Business ; Geography Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Bioinformatics and Genomic Networks
Authors: Bruce G. Elmegreen | Hendrik F. Hamann | Benjamin H. Wunsch | Theodore van Kessel | Binquan Luan | Tonia Elengikal | M. Steiner | Rodrigo Neumann Barros Ferreira | Ricardo Luís Ohta | Felipe Lopes Oliveira | James L. McDonagh | Breanndán Ó Conchúir | Stamatia Zavitsanou | Alexander Harrison | Flaviu Cipcigan | Geeth de Mel | Young‐Hye La | Vidushi Sharma | Dmitry Yu. Zubarev
Source: Frontiers in Environmental Science (article, 2023-08-28)
Field: Materials Science — Materials Chemistry

MDLab: AI frameworks for carbon capture and battery materials There is a growing urgency to discover better materials that capture CO 2 from air and improve battery performance. An important step is to search large databases of materials properties to find examples that resemble known carbon capture agents or electrolytes and then test them for effectiveness. This paper describes novel computational tools for accelerated discovery of solvents, nano-porous materials, and electrolytes. These tools have produced interesting results so far, such as the identification of a relatively isolated location in amine configuration space for the solvents with known carbon capture use, and the demonstration of an end-to-end simulation and process model for carbon capture in MOFs. Carbon fibers ; Battery (electricity) ; Computer science ; Process (computing) ; Amine gas treating ; Process engineering ; Electrolyte ; Carbon capture and storage (timeline) ; Materials science ; Nanotechnology ; Environmental science ; Engineering ; Chemistry ; Physics Machine Learning in Materials Science ; Metal-Organic Frameworks: Synthesis and Applications ; Zeolite Catalysis and Synthesis
Authors: Joseph H. Montoya | Carolyn Grimley | Muratahan Aykol | Colin Ophus | Hadas Sternlicht | Benjamin H. Savitzky | Andrew M. Minor | Steven B. Torrisi | Jackson Goedjen | Ching‐Chang Chung | Andrew H. Comstock | Shijing Sun
Source: ChemRxiv (preprint, 2023-04-28)
Field: Materials Science — Materials Chemistry

Computer-assisted discovery and rational synthesis of ternary oxides Exploratory synthesis has been the main generator of new inorganic materials for decades. However, our Edisonian and bias-prone processes of synthetic exploration alone are no longer sufficient in an age that demands rapid advances in materials development. In this work, we demonstrate one of the first end-to-end attempts towards systematic, computer-aided discovery and laboratory synthesis of inorganic crystalline compounds as a modern alternative to purely exploratory synthesis. Our approach initializes materials discovery campaigns by autonomously mapping the synthetic feasibility of a chemical system using density functional theory with AI feedback. Following expert-driven down-selection of newly generated phases, we use solid-state synthesis and in situ characterization via hot-stage X-ray diffraction in order to realize new ternary oxide phases experimentally. We applied this strategy in six ternary transition-metal oxide chemistries previously considered well-explored, one of which culminated in the discovery of two novel phases of calcium ruthenates. Detailed characterization using room temperature X-ray powder diffraction, 4D-STEM and SQUID measurements identify the structure, composition and confirm distinct properties, including distinct defect concentrations, of one of the new phases formed in our experimental campaigns. While the discovery of a new material guided by AI and DFT theory represents a milestone, our procedure and results also highlight a number of critical gaps in the process that can inform future efforts towards the improvement of AI-coupled methodologies, which are discussed. Characterization (materials science) ; Ternary operation ; Nanotechnology ; Materials science ; Computer science ; Oxide Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electronic and Structural Properties of Oxides
Authors: Д.М. Захаров
Source: Electrochemical Materials and Technologies (article, 2023-07-14)
Field: Materials Science — Materials Chemistry

H/D exchange studies of methane activation mechanisms in heterogeneous catalysis The development of technologies for the efficient conversion of methane and other light hydrocarbons is becoming vital to the chemical industry. The main technologies for methane conversion are based on solid and liquid catalysts such as metals, oxides and oxide-supported metals. Methane is a highly stable molecule, and the analysis of the catalytic activity of materials with respect to the C-H bond cleavage in methane is of paramount importance for the development of novel methane conversion catalysts. One of the most promising methods for studying methane activation over a catalyst is H/D isotope exchange between the gas and condensed phases. The method provides reliable in situ information on the cleavage of chemical bonds in molecules and allows researchers to elucidate the elementary steps of catalytic methane activation and the stable intermediates involved in the activation process. This paper focuses on the critical analysis of H/D isotope exchange studies of the methane activation mechanism over various metals, oxides, composites, and other catalysts, from the earlier studies to the recent advances in the field. The existing theoretical and experimental approaches to study the H/D exchange between methane and a catalyst are discussed in the paper. A critical analysis of the structure-composition-catalytic activity relationships of the catalysts with respect to methane activation is provided. Methane ; Catalysis ; Chemistry ; Anaerobic oxidation of methane ; Oxidative coupling of methane ; Oxide ; Heterogeneous catalysis ; Chemical engineering ; Inorganic chemistry ; Organic chemistry Catalytic Processes in Materials Science ; Catalysis and Oxidation Reactions ; Ammonia Synthesis and Nitrogen Reduction