jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiao L. Pan | Hao Wang | Leilei Zhang | Yu F. Wang | Xiang-Rong Chen | Hua-Yun Geng | Ying Chen
Source: Journal of Nuclear Materials (article, 2023-03-17)
Field: Materials Science — Materials Chemistry

Prediction of novel final phases in aged uranium-niobium alloys Intermetallic ; Metastability ; Niobium ; Phase diagram ; Alloy ; Materials science ; Thermodynamics ; Decomposition ; Phase transition ; Uranium ; Superposition principle ; Tantalum ; High pressure ; Phase (matter) ; Chemical physics ; Chemistry ; Metallurgy ; Physics Nuclear Materials and Properties ; Rare-earth and actinide compounds ; Fusion materials and technologies
Authors: Philip Marmet | Lorenz Holzer | Thomas Hocker | Vinzenz Muser | Gernot Kurt Boiger | Mathias Fingerle | Sarah A. Reeb | Dominik Michel | J. M. Brader
Source: Energy Advances (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Stochastic microstructure modeling of SOC electrodes based on a pluri-Gaussian method A workflow for the stochastic microstructure modeling of solid oxide cell electrodes is presented. Based on a few real microstructures, the design space can be virtually explored, allowing for a subsequent optimization of microstructure properties. Microstructure ; Electrode ; Materials science ; Gaussian ; Workflow ; Computer science ; Composite material ; Chemistry Machine Learning in Materials Science ; Industrial Vision Systems and Defect Detection ; Manufacturing Process and Optimization
Authors: Goktug Ercakir | Gokhan Onder Aksu | Çiğdem Altıntaş | Seda Keskın
Source: ACS Engineering Au (article, 2023-10-07)
Field: Chemistry — Inorganic Chemistry

Hierarchical Computational Screening of Quantum Metal–Organic Framework Database to Identify Metal–Organic Frameworks for Volatile Organic-Compound Capture from Air The design and discovery of novel porous materials that can efficiently capture volatile organic compounds (VOCs) from air are critical to address one of the most important challenges of our world, air pollution. In this work, we studied a recently introduced metal-organic framework (MOF) database, namely, quantum MOF (QMOF) database, to unlock the potential of both experimentally synthesized and hypothetically generated structures for adsorption-based <i>n</i>-butane (C<sub>4</sub>H<sub>10</sub>) capture from air. Configurational Bias Monte Carlo (CBMC) simulations were used to study the adsorption of a quaternary gas mixture of N<sub>2</sub>, O<sub>2</sub>, Ar, and C<sub>4</sub>H<sub>10</sub> in QMOFs for two different processes, pressure swing adsorption (PSA) and vacuum-swing adsorption (VSA). Several adsorbent performance evaluation metrics, such as C<sub>4</sub>H<sub>10</sub> selectivity, working capacity, the adsorbent performance score, and percent regenerability, were used to identify the best adsorbent candidates, which were then further studied by molecular simulations for C<sub>4</sub>H<sub>10</sub> capture from a more realistic seven-component air mixture consisting of N<sub>2</sub>, O<sub>2</sub>, Ar, C<sub>4</sub>H<sub>10</sub>, C<sub>3</sub>H<sub>8</sub>, C<sub>3</sub>H<sub>6</sub>, and C<sub>2</sub>H<sub>6</sub>. Results showed that the top five QMOFs have C<sub>4</sub>H<sub>10</sub> selectivities between 6.3 × 10<sup>3</sup> and 9 × 10<sup>3</sup> (3.8 × 10<sup>3</sup> and 5 × 10<sup>3</sup>) at 1 bar (10 bar). Detailed analysis of the structure-performance relations showed that low/mediocre porosity (0.4-0.6) and narrow pore sizes (6-9 Å) of QMOFs lead to high C<sub>4</sub>H<sub>10</sub> selectivities. Radial distribution function analyses of the top materials revealed that C<sub>4</sub>H<sub>10</sub> molecules tend to confine close to the organic parts of MOFs. Our results provided the first information in the literature about the VOC capture potential of a large variety and number of MOFs, which will be useful to direct the experimental efforts to the most promising adsorbent materials for C<sub>4</sub>H<sub>10</sub> capture from air. Adsorption ; Metal-organic framework ; Butane ; Porosity ; Vacuum swing adsorption ; Chemistry ; Bar (unit) ; Materials science ; Pressure swing adsorption ; Organic chemistry ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Gas Sensing Nanomaterials and Sensors ; Catalytic Processes in Materials Science
Authors: Dan Zhan | Aihui Ye | Tingting Hou
Source: Frontiers in Environmental Science (article, 2023-12-20)
Field: Materials Science — Materials Chemistry

Research progress on biochar-based material adsorption and removal of ibuprofen Ibuprofen, commonly used for pain relief, inflammation, and to reduce high fever, etc., is a widely available over-the-counter drug. In recent years, due to the excessive use of ibuprofen, its presence in the aquatic environments has shown a significant increasing trend, raising concerns about potential risks to environmental safety, which attracted people’s close attention. Notably, biochar, known as an environmentally friendly functional material, had been widely studied and applied for the removal of ibuprofen in water environments. According to current reports, the adsorption capacity value of biochar for IBP is between 9.69–309 mg/g, and the adsorption mechanism mainly includes π-π stacking, hydrogen bonding, pore filling, etc. In response to this research hotspot, this study reviewed the most recent research progress on the adsorption of ibuprofen using biochar-based materials, including the modified preparation process of biochar and the adsorption mechanism of IBP on various modified biochar surfaces. Additionally, potential challenges and future development directions for the practical applications of biochar were discussed and proposed. Biochar ; Adsorption ; Ibuprofen ; Charcoal ; Stacking ; Environmentally friendly ; Chemical engineering ; Environmental science ; Materials science ; Environmental chemistry ; Waste management ; Chemistry ; Nanotechnology ; Pulp and paper industry ; Organic chemistry ; Pyrolysis ; Pharmacology ; Medicine Covalent Organic Framework Applications ; Adsorption and biosorption for pollutant removal ; Metal-Organic Frameworks: Synthesis and Applications
Authors: Ilenia D’Abbrunzo | Giuseppe Procida | Beatrice Perissutti
Source: Pharmaceutics (review, 2023-12-24)
Field: Chemistry — Physical and Theoretical Chemistry

Praziquantel Fifty Years on: A Comprehensive Overview of Its Solid State This review discusses the entire progress made on the anthelmintic drug praziquantel, focusing on the solid state and, therefore, on anhydrous crystalline polymorphs, amorphous forms, and multicomponent systems (i.e., hydrates, solvates, and cocrystals). Despite having been extensively studied over the last 50 years, new polymorphs and the greater part of their cocrystals have only been identified in the past decade. Progress in crystal engineering science (e.g., the use of mechanochemistry as a solid form screening tool and more strategic structure-based methods), along with the development of analytical techniques, including Synchrotron X-ray analyses, spectroscopy, and microscopy, have furthered the identification of unknown crystal structures of the drug. Also, computational modeling has significantly contributed to the prediction and design of new cocrystals by considering structural conformations and interactions energy. Whilst the insights on praziquantel polymorphs discussed in the present review will give a significant contribution to controlling their formation during manufacturing and drug formulation, the detailed multicomponent forms will help in designing and implementing future praziquantel-based functional materials. The latter will hopefully overcome praziquantel's numerous drawbacks and exploit its potential in the field of neglected tropical diseases. Nanotechnology ; Solid-state ; Mechanochemistry ; Chemistry ; Materials science ; Physical chemistry Crystallography and molecular interactions ; Crystallization and Solubility Studies ; Phytochemistry and Bioactivity Studies
Authors: Carolina A. Garcia-Soto | Edmond Baratte | Tiago Silva | Vasco Guerra | Vasile I. Pârvulescu | Olivier Guaitella
Source: Plasma Chemistry and Plasma Processing (article, 2023-11-17)
Field: Materials Science — Materials Chemistry

CO2/CH4 Glow Discharge Plasma. Part II: Study of Plasma Catalysis Interaction Mechanisms on CeO2 Plasma ; Hydrogen ; Catalysis ; Analytical Chemistry (journal) ; Chemistry ; Formate ; Crystallography ; Physics Catalytic Processes in Materials Science ; CO2 Reduction Techniques and Catalysts ; Catalysis and Oxidation Reactions
Authors: Lim Heo | Michael Feig
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2023-05-23)
Field: Materials Science — Materials Chemistry

One particle per residue is sufficient to describe all-atom protein structures ABSTRACT Atomistic resolution is considered the standard for high-resolution biomolecular structures, but coarse-grained models are often necessary to reflect limited experimental resolution or to achieve feasibility in computational studies. It is generally assumed that reduced representations involve a loss of detail, accuracy, and transferability. This study explores the use of advanced machine-learning networks to learn from known structures of proteins how to reconstruct atomistic models from reduced representations to assess how much information is lost when the vast knowledge about protein structures is taken into account. The main finding is that highly accurate and stereochemically realistic all-atom structures can be recovered with minimal loss of information from just a single bead per amino acid residue, especially when placed at the side chain center of mass. High-accuracy reconstructions with better than 1 Å heavy atom root-mean square deviations are still possible when only Cα coordinates are used as input. This suggests that lower-resolution representations are essentially sufficient to represent protein structures when combined with a machine-learning framework that encodes knowledge from known structures. Practical applications of this high-accuracy reconstruction scheme are illustrated for adding atomistic detail to low-resolution structures from experiment or coarse-grained models generated from computational modeling. Moreover, a rapid, deterministic all-atom reconstruction scheme allows the implementation of an efficient multi-scale framework. As a demonstration, the rapid refinement of accurate models against cryoEM densities is shown where sampling at the coarse-grained level is guided by map correlation functions applied at the atomistic level. With this approach, the accuracy of standard all-atom simulation based refinement schemes can be matched at a fraction of the computational cost. STATEMENT OF SIGNIFICANCE The fundamental insight of this work is that atomistic detail of proteins can be recovered with minimal loss of information from highly reduced representations with just a single bead per amino acid residue. This is possible by encoding the existing knowledge about protein structures in a machine-learning model. This suggests that it is not strictly necessary to resolve structures in atomistic detail in experiments, computational modeling, or the generation of protein conformations via neural networks since atomistic details can inferred quickly via the neural network. This increases the relevance of experimental structures obtained at lower resolutions and broadens the impact of coarse-grained modeling. Transferability ; Computer science ; Resolution (logic) ; Algorithm ; Atom (system on chip) ; Artificial intelligence ; Machine learning Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Xin Zeng | Shuai Zhang | Chenhua Ren | Tao Shao
Source: Journal of Physics D Applied Physics (article, 2023-02-24)
Field: Materials Science — Materials Chemistry

Physics informed neural networks for electric field distribution characteristics analysis Abstract Electric field calculations based on the Poisson equation have been widely used in high voltage and plasma technology. However, in practical applications, the electric field distribution in space is relatively complex, and the simulation technology based on the traditional method is often a simplification of reality, which leads to a large error between the simulation and the actual measured value. In the actual application process, due to the limitation of measurement methods, it is necessary to infer the electric field data at other locations in space according to the measurement results. Physics informed neural networks (PINNs) are introduced into the electric field calculation. PINNs are considered partial differential equation solvers based on deep neural networks. In this paper, 2D and 3D electric field distributions are discussed and compared with the finite element method. A method of dividing the dielectric distribution based on the sigmoid function is proposed, which can be effectively used to construct the spatial electric field model of the homogeneous dielectric. The combination of the data and physical model based on PINNs establishes a method to solve the inverse problem of the relative permittivity in the electric field. The results show that PINNs can calculate the distribution of the electric field according to the physical equations and different types of constraints and parameters. Electric field ; Field (mathematics) ; Artificial neural network ; Poisson's equation ; Statistical physics ; Physics ; Dielectric ; Computer science ; Algorithm ; Applied mathematics ; Mathematical analysis ; Mathematics ; Artificial intelligence ; Quantum mechanics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrostatic Discharge in Electronics
Authors: Malvika Viswanathan | Leqi Yin | Yashwant Kurmi | Zhongliang Zu
Source: Magnetic Resonance in Medicine (article, 2023-12-14)
Field: Materials Science — Materials Chemistry

Machine learning‐based <scp>amide proton transfer</scp> imaging using partially synthetic training data Partially synthetic CEST data can address the challenges in conventional ML methods. Synthetic data ; Computer science ; Ground truth ; Training set ; Artificial intelligence ; Experimental data ; Fidelity ; Flexibility (engineering) ; Machine learning ; Data mining ; Pattern recognition (psychology) ; Mathematics Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Electron Spin Resonance Studies
Authors: Luiza Mădălina Grădinaru | Maria Bercea | Alexandra Lupu | Vasile Robert Grădinaru
Source: Polymers (article, 2023-03-29)
Field: Materials Science — Polymers and Plastics

Development of Polyurethane/Peptide-Based Carriers with Self-Healing Properties In situ-forming gels with self-assembling and self-healing properties are materials of high interest for various biomedical applications, especially for drug delivery systems and tissue regeneration. The main goal of this research was the development of an innovative gel carrier based on dynamic inter- and intramolecular interactions between amphiphilic polyurethane and peptide structures. The polyurethane architecture was adapted to achieve the desired amphiphilicity for self-assembly into an aqueous solution and to facilitate an array of connections with peptides through physical interactions, such as hydrophobic interactions, dipole-dipole, electrostatic, π-π stacking, or hydrogen bonds. The mechanism of the gelation process and the macromolecular conformation in water were evaluated with DLS, ATR-FTIR, and rheological measurements at room and body temperatures. The DLS measurements revealed a bimodal distribution of small (~30-40 nm) and large (~300-400 nm) hydrodynamic diameters of micelles/aggregates at 25 °C for all samples. The increase in the peptide content led to a monomodal distribution of the peaks at 37 °C (~25 nm for the sample with the highest content of peptide). The sol-gel transition occurs very quickly for all samples (within 20-30 s), but the equilibrium state of the gel structure is reached after 1 h in absence of peptide and required more time as the content of peptide increases. Moreover, this system presented self-healing properties, as was revealed by rheological measurements. In the presence of peptide, the structure recovery after each cycle of deformation is a time-dependent process, the recovery is complete after about 300 s. Thus, the addition of the peptide enhanced the polymer chain entanglement through intermolecular interactions, leading to the preparation of a well-defined gel carrier. Undoubtedly, this type of polyurethane/peptide-based carrier, displaying a sol-gel transition at a biologically relevant temperature and enhanced viscoelastic properties, is of great interest in the development of medical devices for minimally invasive procedures or precision medicine. Polyurethane ; Self-healing ; Peptide ; Materials science ; Polymer science ; Composite material ; Chemistry ; Medicine ; Biochemistry Polymer composites and self-healing ; Advanced Polymer Synthesis and Characterization ; Polydiacetylene-based materials and applications
Authors: Manuel A.V. Ribeiro da Silva | G. Léon | María D.M.C. Ribeiro da Silva | Thomas M. Klapötke | Jelena Reinhardt
Source: Thermo (article, 2023-10-05)
Field: Chemistry — Organic Chemistry

Enthalpy of Formation of the Nitrogen-Rich Salt Guanidinium 5,5′-Azotetrazolate (GZT) and a Simple Approach for Estimating the Enthalpy of Formation of Energetic C, H, N, O Salts The discrepancy between the calculated (CBS-4M/Jenkins) and experimentally determined enthalpies of formation recently reported for the 2:1 salt TKX-50 raised the important question of whether the enthalpies of formation of other 2:1 C, H, N, O salts calculated using the CBS-4M/Jenkins method are reliable values. The standard (p° = 0.1 MPa) enthalpy of formation of crystalline guanidinium 5,5′-azotetrazolate (GZT) (453.6 ± 3.2 kJ/mol) was determined experimentally using static-bomb combustion calorimetry and was found to be in good agreement with the literature’s values. However, using the CBS-4M/Jenkins method, the calculated enthalpy of formation of GZT was again in poor agreement with the experimentally determined value. The method we used recently to calculate the enthalpy of formation of TKX-50, based on the calculation of the heat of formation of the salt and of the corresponding neutral adduct, was then applied to GZT and provided excellent agreement with the experimentally determined value. Finally, in order to validate the findings, this method was also applied to predict the enthalpy of formation of a range of 1:1 and 2:1 salts (M+X− and (M+)2X2− salts, respectively), and the values obtained were comparable to experimentally determined values. The agreement using this approach was generally very good for both 1:1 and 2:1 salts; therefore, this approach provides a simple and reliable method which can be applied to calculate the enthalpy of formation of energetic C, H, N, O salts with much greater accuracy than the current, commonly used method. Enthalpy ; Standard enthalpy of formation ; Standard enthalpy change of formation ; Chemistry ; Calorimetry ; Salt (chemistry) ; Thermodynamics ; Standard enthalpy of reaction ; Enthalpy change of solution ; Adduct ; Enthalpy of atomization ; Physical chemistry ; Organic chemistry Chemical Thermodynamics and Molecular Structure ; Energetic Materials and Combustion ; Thermal and Kinetic Analysis
Authors: Mauricio Maldonado‐Domínguez | Martin Srnec
Source: Dalton Transactions (article, 2023-01-01)
Field: Chemistry — Organic Chemistry

Quantifiable polarity match effect on C–H bond cleavage reactivity and its limits in reaction design When oxidants favour cleaving a strong C-H bond at the expense of weaker ones, which are otherwise inherently preferred due to their favourable reaction energy, reactivity factors such as the polarity match effect are often invoked. Polarity match follows the intuition of electrophilic (nucleophilic) oxidants reacting faster with nucleophilic (electrophilic) C-H bonds. Nevertheless, this concept is purely qualitative and is best suited for <i>a posteriori</i> rationalization of experimental observations. Here, we propose and inspect two methods to quantify polar effects in C-H cleavage reactions, one by computation <i>via</i> the difference of atomic charges (Δ<i>q</i>) of reacting atoms, and one amenable to experimental measurement through asynchronicity factors, <i>η</i>. By their application to three case studies, we observe that both Δ<i>q</i> and <i>η</i> faithfully capture the notion of polarity match. The polarity match model, however, proves insufficient as a predictor of H-atom abstraction reactivity and we discourage its use as a standalone variable in reaction design. Besides this caveat, <i>η</i> and Δ<i>q</i> (through its mapping on <i>η</i>) allow the implementation of polarity match into a Marcus-type model of reactivity, alleviating its shortcomings and making reaction planning feasible. Electrophile ; Reactivity (psychology) ; Nucleophile ; Chemistry ; Polarity (international relations) ; A priori and a posteriori ; Bond cleavage ; Computational chemistry ; Stereochemistry ; Catalysis ; Organic chemistry Catalytic C–H Functionalization Methods ; Synthesis and Catalytic Reactions ; Sulfur-Based Synthesis Techniques
Authors: Jiewei Cheng | Tingwei Li | Yongyi Wang | Ahmed H. Ati | Qiang Sun
Source: The Journal of Chemical Physics (article, 2023-11-15)
Field: Materials Science — Materials Chemistry

The relationship between activated H2 bond length and adsorption distance on MXenes identified with graph neural network and resonating valence bond theory Motivated by the recent experimental study on hydrogen storage in MXene multilayers [Liu et al., Nat. Nanotechnol. 16, 331 (2021)], for the first time we propose a workflow to computationally screen 23 857 compounds of MXene to explore the general relation between the activated H2 bond length and adsorption distance. By using density functional theory we generate a dataset to investigate the adsorption geometries of hydrogen on MXenes, based on which we train physics-informed atomistic line graph neural networks (ALIGNNs) to predict adsorption parameters. To fit the results, we further derived a formula that quantitatively reproduces the dependence of H2 bond length on the adsorption distance from MXenes within the framework of Pauling's resonating valence bond theory, revealing the impact of transition metal's ligancy and valence on activating dihydrogen in H2 storage. MXenes ; Adsorption ; Valence (chemistry) ; Density functional theory ; Valence bond theory ; Hydrogen bond ; Bond length ; Graph theory ; Materials science ; Computational chemistry ; Chemical physics ; Generalized valence bond ; Chemistry ; Statistical physics ; Molecule ; Mathematics ; Physical chemistry ; Physics ; Quantum mechanics ; Nanotechnology ; Bond order ; Combinatorics MXene and MAX Phase Materials ; Hydrogen Storage and Materials ; Graphene research and applications