jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: De Zhang | Ruijing Wang | Sijia Luo | Guangfeng Wei
Source: Molecules (article, 2024-07-28)
Field: Materials Science — Materials Chemistry

Restructuring and Hydrogen Evolution on Sub-Nanosized PdxBy Clusters As a Pt-group element, Pd has been regarded as one of the alternatives to Pt-based catalysts for the hydrogen evolution reaction (HER). Herein, we performed density functional theory (DFT) computations to explore the most stable structures of Pd<i><sub>x</sub></i>B<i><sub>y</sub></i> (<i>x</i> = 6, 19, 44), revealed the in situ structural reconstruction of these clusters under acidic conditions, and evaluated their HER activity. We found that the presence of B can prevent underpotential hydrogen adsorption and activate the H atoms on the cluster surface for the HER. The theoretical calculations show that the reaction barrier for the HER on ~1 nm sized Pd<sub>44</sub>B<sub>4</sub> can be as low as 0.36 eV, which is even lower than for the same-sized Pt and Pd<sub>2</sub>B nanoparticles. The ultra-high HER activity of sub-nanosized Pd<i><sub>x</sub></i>B<i><sub>y</sub></i> clusters makes them a potential new and efficient HER electro-catalyst. This study provides new ideas for evaluating and designing novel nanocatalysts based on the structural reconstruction of small-sized nanoparticles in the future. Restructuring ; Hydrogen ; Materials science ; Nanotechnology ; Chemistry ; Chemical engineering ; Business ; Engineering ; Organic chemistry Catalytic Processes in Materials Science ; Copper-based nanomaterials and applications ; Machine Learning in Materials Science
Authors: William H. Green
Source: ChemRxiv (preprint, 2024-05-27)
Field: Materials Science — Materials Chemistry

Perspective on Automated Predictive Kinetics using Estimates derived from Large Datasets A longstanding project of the chemical kinetics community is to predict reaction rates and the behavior of reacting systems, even for systems where there are no experimental data. Many important reacting systems (atmosphere, combustion, pyrolysis, partial oxidations) involve a large number of reactions occurring simultaneously, and reaction intermediates that have never been observed, making this goal even more challenging. Improvements in our ability to compute rate coefficients and other important parameters accurately from first principles, and improvements in automated kinetic modeling software, have partially overcome many challenges. Indeed, in some cases quite complicated kinetic models have been constructed which accurately predicted the results of independent experiments. However, the process of constructing the models, and deciding which reactions to measure or compute ab initio, relies on accurate estimates (and indeed most of the numerical rate parameters in most large kinetic models are estimates.) Machine-learned models trained on large datasets can improve the accuracy of these estimates, and allow a better integration of quantum chemistry and experimental data. The need for continued development of shared (perhaps open-source) software and databases, and some directions for improvement, are highlighted. As we model more complicated systems, many of the weaknesses of the traditional ways of doing chemical kinetic modeling, and of testing kinetic models, have been exposed, identifying several challenges for future research by the community Perspective (graphical) ; Computer science ; Econometrics ; Artificial intelligence ; Mathematics Machine Learning in Materials Science
Authors: Irina N. Vikhareva | V. E. Antipin
Source: Nanotechnologies in Construction A Scientific Internet-Journal (article, 2024-02-29)
Field: Materials Science — General Materials Science

Modern strategies for the creation of polymer coatings. Part I Introduction. Coatings on hard materials are widely used in many industries. Coating technologies help prevent or reduce corrosion, contamination and biofouling, chemical and structural degradation, and wear and tear of external surfaces due to exposure to the elements and natural environments. The range of materials used for functional coatings is quite wide: from organic polymers to hybrid composites and inorganic nanoparticles, depending on the desired properties and functionality of the final product. Despite the excellent anti-corrosion characteristics of non-polymer coatings, their usage causes environmental damage. Organic coatings are among the most widely used. Such compositions are applied in liquid form; organic solvents are one of the main components. Environmental concerns have encouraged the development of alternative technologies. The main areas for development are availability of raw materials and the cost of environmentally friendly coatings. Results and discussion. The review substantiates the relevance of research on the development of multifunctional polymer-based coatings. The market for polymer coatings is presented. Methods of surface protection, types of coatings formed, their main components, features of the formation of coatings, the influence of various factors on the formation of polymer coatings, including methods of preparation and pre-treatment of the protected surface are presented. Methods for preventing corrosion are discussed in detail, as well as the main directions in the development of anti-corrosion coatings based on various protective mechanisms. The characteristics of the main components of protective coatings are given. The issue of destruction of polymer coatings depending on the operating environment is considered in detail. The types of media, their influence and mechanisms of action on protected objects are considered. Factors and mechanisms of destruction of polymer coatings, methods for preventing degradation of coatings are listed. The latest technologies for the formation of protective polymer coatings are highlighted. Conclusion. Currently, coatings provide a wide range of quality indicators. An important characteristic of modern coatings is minimal negative impact on the environment, which requires an integrated approach to the design and production of coatings Polymer ; Polymer science ; Materials science ; Composite material Material Properties and Applications ; Polymer Science and Applications
Authors: Lukas Lätsch | С. А. Гуда | Vladyslav Romankov | Christina Wartmann | Jörg‐M. Neudörfl | Jan Dreiser | Albrecht Berkessel | Alexander A. Guda | Christophe Copéret
Source: ChemRxiv (preprint, 2024-02-15)
Field: Materials Science — Materials Chemistry

Tracking Coordination Environment and Reaction Intermediates in Homo- and Heterogeneous Epoxidation Catalysts via Ti L2,3-edge NEXAFS Ti-based molecules and materials are ubiquitous, and play a major role in both homogeneous and heterogeneous catalytic processes. Understanding the electronic structures of their active sites (oxidation state, local symmetry and ligand environment) is key to developing molecular-level structure-property relationships. In that context, X-ray absorption spectroscopy (XAS) offers a unique combination of element selectivity and sensitivity to local symmetry. Commonly, for early transition metals such as Ti, K-edge XAS is applied for in situ characterization and subsequent structural analysis with high sensitivity towards tetrahedral species. Ti L2,3-edge spectroscopy is in principle complementary and offers specific opportunities to interrogate the electronic structure of five-and six-coordinated species. It is, however, much more rarely implemented, because the use of soft X-rays implies ultra-high vacuum conditions. Furthermore, the interpretation of the data can be challenging. Here, we show how Ti L2,3-edge spectroscopy can help to obtain unique information about both homogenous and heterogeneous epoxidation catalysts and to develop a molecular-level relationship between spectroscopic signatures and electronic structures. Towards this goal, we first establish a spectral library of molecular Ti reference compounds, comprising various coordination environments with mono- and dimeric Ti species having O, N and Cl-ligands. We next implemented a computational methodology based on multiplet ligand field theory and maximally localized Wannier orbitals benchmarked on our library to understand Ti L2,3-edge spectroscopic signatures. We finally used this approach to track and predict spectra of catalytically relevant intermediates, focusing on Ti-based olefin epoxidation catalysts. XANES ; Catalysis ; Tracking (education) ; Enhanced Data Rates for GSM Evolution ; Chemistry ; Materials science ; Computer science ; Organic chemistry ; Physics ; Psychology ; Spectroscopy ; Artificial intelligence Polyoxometalates: Synthesis and Applications ; Chemical Synthesis and Reactions ; Catalysis and Oxidation Reactions
Authors: Ali Haji Ebrahim Zargar | Ali Amini | Ahmad Ayatollahi
Source: Micro and Nanostructures (article, 2024-03-09)
Field: Materials Science — Materials Chemistry

Estimation enhancing in optoelectronic property: A novel approach using orbital interaction parameters and tight-binding Computation ; Gallium arsenide ; Computer science ; Band gap ; Quantum ; Lattice (music) ; Scope (computer science) ; Materials science ; Optoelectronics ; Physics ; Algorithm ; Quantum mechanics Machine Learning in Materials Science ; Nanowire Synthesis and Applications ; Semiconductor materials and devices
Authors: Nobahar Shahidi | Jeffrey A. Laub | Konstantinos D. Vogiatzis | Manolis Doxastakis
Source: Polymers (article, 2024-08-07)
Field: Chemistry — Organic Chemistry

Multiscale Modeling of Vinyl-Addition Polynorbornenes: The Effect of Stereochemistry Vinyl-addition polynorbornenes are candidates for designing high-performance polymers due to unique characteristics, which include a high glass transition temperature associated with a rigid backbone. Recent studies have established that the processability and properties of these polymers can be fine-tuned by using targeted substitutions. However, synthesis with different catalysts results in materials with distinct properties, potentially due to the presence of various stereoisomers that are difficult to quantify experimentally. Herein, we develop all-atom models of polynorbornene oligomers based on classical force fields and density functional theory. To establish the relationship between chemical architecture, chain conformations, and melt structure, we perform detailed molecular dynamics simulations with the fine-tuned atomistic force field and propose simpler coarse-grained descriptions to address the high molecular weight limit. All-atom simulations of oligomers suggest high glass transition temperatures in the range of 550-600 K. In the melt state (800 K), meso chains form highly rigid extended coils (C∞≈11) with amorphous structural characteristics similar to the X-ray diffraction data observed in the literature. In contrast, simulations with racemo chains predict highly helical tubular chain conformations that could promote assembly into crystalline structures. Chemistry ; Materials science ; Organic chemistry Supramolecular Chemistry and Complexes ; Analytical Chemistry and Chromatography ; Advanced Polymer Synthesis and Characterization
Authors: Mikael Valter | Minttu M. Kauppinen | David Degerman | Gabriel L. S. Rodrigues | Henrik Grönbeck | Lars G. M. Pettersson
Source: ChemRxiv (preprint, 2024-04-04)
Field: Materials Science — Materials Chemistry

Microkinetic Model Fitted with a Genetic Algorithm to Experimental XPS Coverages at High Pressure – CO hydrogenation on Rh(111) Comparisons to experiments are important when developing kinetic models based on density functional theory (DFT) calculations. The comparisons are, however, often challenging due to the assumed uncertainties in the energies from which the kinetic parameters are calculated. Here, we introduce a genetic algorithm to adjust the DFT-energies to better match experimental XPS data, using CO hydrogenation on Rh(111) as an example. The adjustments are made to adsorption energies, adsorbate-adsorbate interactions, XPS energies and peak shapes. While these parameters improve the experimental agreement considerably, the required changes to the DFT energies are relatively large, which indicates the need for refined treatments of, for example, possible surface species and reaction steps, surface inhomogeneities, or higher levels of electronic structure calculations. We propose the genetic-algorithm based method as a general tool for assessment of computational models. X-ray photoelectron spectroscopy ; Density functional theory ; Kinetic energy ; Genetic algorithm ; Adsorption ; Surface (topology) ; Electronic structure ; Materials science ; Chemistry ; Computational chemistry ; Physical chemistry ; Computer science ; Physics ; Mathematics ; Quantum mechanics ; Geometry ; Nuclear magnetic resonance ; Machine learning Catalytic Processes in Materials Science ; Copper-based nanomaterials and applications ; nanoparticles nucleation surface interactions
Authors: Marc Hennebelle | Yoann Cirillo | Anne‐Doriane Manick | Didier Nuel | Alexandre Martinez | Bastien Châtelet
Source: The Journal of Organic Chemistry (article, 2024-03-25)
Field: Chemistry — Organic Chemistry

Synthesis, Resolution, and Absolute Configuration of a Phosphine-Based Hemicryptophane Cage with an Endo Phosphorus Lone Pair and Formation of the Corresponding Gold Complex The synthesis, characterization, and chiroptical properties of a new class of hemicryptophanes combining a phosphine moiety and a cyclotriveratrylene unit are reported. The synthesis was short and efficient. The racemic mixture of the cage was resolved by chiral high-performance liquid chromatography (HPLC), giving access to enantiopure molecular cages, whose absolute configurations could be assigned by electronic circular dichroism (ECD) spectroscopy. These new phosphines were then reacted with gold in order to make the corresponding enantiopure gold complexes. The X-ray structure reveals an endohedral functionalization of the cage with the gold metal entrapped in the heart of the cavity, leading to a <i>V</i><sub>bur</sub> of 58%. Moreover, the chirality of the cyclotriveratrylene unit was found to control the chiral arrangement of the aryl group linked to the phosphorus atom, located at the opposite side of the cavity. Enantiopure drug ; Absolute configuration ; Chemistry ; Chirality (physics) ; Circular dichroism ; Phosphine ; Moiety ; Lone pair ; Chiral column chromatography ; Crystallography ; Stereochemistry ; Aryl ; Chiral resolution ; Enantiomer ; Organic chemistry ; Molecule ; Enantioselective synthesis Supramolecular Chemistry and Complexes ; Molecular Sensors and Ion Detection ; Mass Spectrometry Techniques and Applications
Authors: Marian Arale Brännvall | Gabriel Persson | Luis Casillas‐Trujillo | Rickard Armiento | Björn Alling
Source: arXiv (Cornell University) (preprint, 2024-06-04)
Field: Materials Science — Materials Chemistry

Predicting the Curie temperature of magnetic materials with automated calculations across chemistries and structures We develop a technique for predicting the Curie temperature of magnetic materials using density functional theory calculations suitable to include in high-throughput frameworks. We apply four different models, including physically relevant observables and assess numerical constants by studying 32 ferro- and ferrimagnets. With the best-performing model, the Curie temperature can be predicted with a mean absolute error of approximately 126 K. As predictive factors, the models consider either the energy differences between the magnetic ground state and a magnetically disordered paramagnetic state, or the average constraining fields acting on magnetic moments in a disordered local moments calculation. Additionally, the energy differences are refined by incorporating the magnetic entropy of the paramagnetic state and the number of nearest magnetic neighbors of the magnetic atoms. The most advanced model is found to extend well into Fe$_{1-x}$Co$_x$ alloys, indicating the potential efficacy of utilizing our model in designing materials with tailored Curie temperatures by altering alloy compositions. This examination can illuminate the factors influencing magnetic transition temperatures in magnetic materials and provide insights into how they can be employed to make quantitative predictions of Curie temperatures. Our approach is not restricted to specific crystal structures or chemical compositions. It offers a more cost-effective alternative, in terms of human time and need for hands-on oversight, to other density functional theory methods for predicting the Curie temperature. As a result, it provides a practical strategy for conducting high-throughput screening for new technologically applicable magnetic materials. Alternatively, it can complement ML-based screening of magnetic materials by integrating physical principles into such approaches, thereby enhancing their prediction accuracy. Curie temperature ; Curie ; Materials science ; Condensed matter physics ; Ferromagnetism ; Physics Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Hongyi Wang | Ji Ung Sun | Jinzhe Liang | Li Zhai | Zitian Tang | Zijian Li | Wei Zhai | Xusheng Wang | Weihao Gao | Shaohua Gong
Source: arXiv (Cornell University) (preprint, 2024-07-23)
Field: Materials Science — Materials Chemistry

CrysToGraph: A Comprehensive Predictive Model for Crystal Materials Properties and the Benchmark The ionic bonding across the lattice and ordered microscopic structures endow crystals with unique symmetry and determine their macroscopic properties. Unconventional crystals, in particular, exhibit non-traditional lattice structures or possess exotic physical properties, making them intriguing subjects for investigation. Therefore, to accurately predict the physical and chemical properties of crystals, it is crucial to consider long-range orders. While GNN excels at capturing the local environment of atoms in crystals, they often face challenges in effectively capturing longer-ranged interactions due to their limited depth. In this paper, we propose CrysToGraph ($\textbf{Crys}$tals with $\textbf{T}$ransformers $\textbf{o}$n $\textbf{Graph}$s), a novel transformer-based geometric graph network designed specifically for unconventional crystalline systems, and UnconvBench, a comprehensive benchmark to evaluate models' predictive performance on unconventional crystal materials such as defected crystals, low-dimension crystals and MOF. CrysToGraph effectively captures short-range interactions with transformer-based graph convolution blocks as well as long-range interactions with graph-wise transformer blocks. CrysToGraph proofs its effectiveness in modelling unconventional crystal materials in multiple tasks, and moreover, it outperforms most existing methods, achieving new state-of-the-art results on the benchmarks of both unconventional crystals and traditional crystals. Benchmark (surveying) ; Materials science ; Computer science ; Geography ; Cartography Machine Learning in Materials Science
Authors: Jessy Paterson | Sunanda Mitra | Yanqing Liu | M. Boukhari | Dhruv Singhal | David Lacroix | E. Hadji | A. Barski | Dimitri Tainoff | Olivier Bourgeois
Source: arXiv (Cornell University) (preprint, 2024-04-30)
Field: Materials Science — Materials Chemistry

Thermal conductivity reduction due to phonon geometrical scattering in nano-engineered epitaxial germanium Nano-engineering crystalline materials can be used to tailor their thermal properties. By adding new nanoscale phonon scattering centers and controlling their size, one can effectively decrease the phonon mean free path and hence the thermal conductivity of a fully crystalline material. In this letter, we use the 3$ω$ method in the temperature range of 100-300 K to experimentally report on the more than threefold reduction of the thermal conductivity of an epitaxially-grown crystalline germanium thin film with embedded polydispersed crystalline \ch{Ge3Mn5} nano-inclusions with diameters ranging from 5 to 25~nm. A detailed analysis of the structure of the thin film coupled with Monte Carlo simulations of phonon transport highlight the role of the nano-inclusions volume fraction in the reduction of the phononic contribution to the thermal conductivity, in particular its temperature dependence, leading to a phonon mean free path that is set by geometrical constraints. Germanium ; Phonon ; Thermal conductivity ; Epitaxy ; Scattering ; Materials science ; Reduction (mathematics) ; Phonon scattering ; Nano- ; Condensed matter physics ; Thermal ; Optoelectronics ; Engineering physics ; Nanotechnology ; Composite material ; Optics ; Physics ; Thermodynamics ; Mathematics ; Silicon ; Geometry Thermal properties of materials ; Advancements in Semiconductor Devices and Circuit Design ; Integrated Circuits and Semiconductor Failure Analysis
Authors: Ephraiem S. Sarabamoun | Pramod Aryal | Jonathan Bietsch | Maurice Curran | Sandeep Verma | Grayson Johnson | Lucy U. Yoon | Amelia G. Reid | Esther H. R. Tsai | Charles W. Machan | Christopher Paolucci | Guijun Wang | Joshua J. Choi
Source: The Journal of Physical Chemistry C (article, 2024-11-21)
Field: Materials Science — Materials Chemistry

Photoluminescence Switching in Quantum Dots Connected with Carboxylic Acid and Thiocarboxylic Acid End-Group Diarylethene Molecules We contrast the switching of photoluminescence (PL) of PbS quantum dots (QDs) cross-linked with photochromic diarylethene molecules with different end groups, 4,4'-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenecarboxylic acid] (<b>1C</b>) and 4,4'-(1-cyclopentene-1,2-diyl)bis[5-methyl-2-thiophenethiocarboxylic acid] (<b>2T</b>). Our results show that the QDs cross-linked with the carboxylic acid end group molecules (<b>1C</b>) exhibit a greater amount of switching in photoluminescence intensity compared to QDs cross-linked with the thiocarboxylic acid end group (<b>2T</b>). We also demonstrate that regardless of the molecule used, greater switching amounts are observed for smaller quantum dots. Varying these parameters allows for the fabrication of photoswitches with tunable PL change. We relate these observations to the differences in the HOMO energy levels between the QDs and the photochromic molecules. Our findings demonstrate how the size of the QDs and the energy levels of the linker ligands influences the charge tunneling rate and thus the PL switching performance in tunneling-based photoswitches. Diarylethene ; Photoluminescence ; Molecule ; Chemistry ; Group (periodic table) ; Photochemistry ; Photochromism ; Materials science ; Optoelectronics ; Organic chemistry Photochromic and Fluorescence Chemistry ; Luminescence and Fluorescent Materials ; Photoreceptor and optogenetics research