jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Abhishek T. Sose | Troy Gustke | Fangxi Wang | Gaurav Anand | Sanjana Pasupuleti | Aditya Savara | Sanket A. Deshmukh
Source: Journal of Chemical Theory and Computation (article, 2024-06-26)
Field: Materials Science — Materials Chemistry

Evaluation of Sampling Algorithms Used for Bayesian Uncertainty Quantification of Molecular Dynamics Force Fields New Bayesian parameter estimation methods have the capability to enable more physically realistic and reliable molecular dynamics (MD) simulations by providing accurate estimates of uncertainties of force-field (FF) parameters and associated properties. However, the choice of which Bayesian parameter estimation algorithm to use has not been widely investigated, despite its impact on the effective exploration of parameter space. Here, using a case example of the Embedded Atom Method (EAM) FF parameters, we investigated the ramifications of several of the algorithm choices. We found that Ensemble Slice Sampling (ESS) and Affine-Invariant Ensemble Sampling (AIES) demonstrate a new level of superior performance, culminating in more accurate parameter and property estimations with tighter uncertainty bounds, compared to traditional methods such as Metropolis-Hastings (MH), Gradient Search (GS), and Uniform Random Sampler (URS). We demonstrate that Bayesian Uncertainty Quantification with ESS and AIES leads to significantly more accurate and reliable predictions of the FF parameters and properties. The results suggest that ESS and AIES should be used to obtain more accurate parameter and uncertainty estimations while providing deeper physical insights. Sampling (signal processing) ; Bayesian probability ; Computer science ; Algorithm ; Uncertainty quantification ; Parameter space ; Molecular dynamics ; Force field (fiction) ; Field (mathematics) ; Estimation theory ; Mathematics ; Statistics ; Artificial intelligence ; Machine learning ; Physics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Nuclear Materials and Properties
Authors: Fu‐Zhi Dai | Bo Wen | Yixuan Hu | Xinfu Gu
Source: Journal of Materials Informatics (article, 2024-08-12)
Field: Materials Science — Materials Chemistry

A deep neural network potential model for transition metal diborides Transition metal diborides (TMB2s) are renowned for their high melting point and exceptional wear, corrosion, and erosion resistance, making them promising candidate materials for applications in extreme environments. As such, there is an urgent need for reliable material design tools for TMB2s to improve efficiency in developing new materials. To address this need, we have developed a domain-specific medium-scale interatomic potential model for TMB2s that encompasses elements Ti, Zr, Hf, V, Nb, Ta, Cr, Mo, W, and B. The prediction errors in energy and force of our model are 8.8 meV/atom and 387 meV/Å, respectively. Furthermore, the model demonstrates high accuracy in predicting various material properties, including lattice parameters, elastic constants, equations of states, and melting points, as well as grain boundary segregations. By providing a reliable and efficient tool for material design, this model will play a crucial role in the development of new, high-performance TMB2s for use in extreme environments. Artificial neural network ; Computer science ; Artificial intelligence Machine Learning in Materials Science ; Metal and Thin Film Mechanics ; Advanced Materials Characterization Techniques
Authors: Henry N. Abonyi | Ikechukwu Emmanuel Peter | Akachukwu Marytheresa Onwuka | Paul A. Achile | B. Chinonso | Maureen O. Akunne | Paul M. Ejikeme | Samson Amos | Theophine Chinwuba Akunne | Anthony A. Attama | Peter A. Akah
Source: Nanomedicine (review, 2024-12-26)
Field: Materials Science — Materials Chemistry

Nanotoxicology: developments and new insights The use of nanoparticles (NPs) in treatment of diseases have increased exponentially recently, giving rise to the science of nanomedicine. The safety of these NPs in humans has also led to the science of nanotoxicology. Due to a dearth of both readily available models and precise bio-dispersion characterization techniques, nanotoxicological research has obviously been constrained. However, the ensuing years were notable for the emergence of improved synthesis methods and characterization tools. Major advances have been made in linking certain physical variables, paralleling improvements in characterization size, shape, or coating factors to the resulting physiological reactions. Although significant progress has been a contribution to the development of nanotoxicology, however, it faces numerous difficulties and technical constraints distinct from those of conventional toxicological assessment as it attempts to improve the therapeutic effects of medicines. Determining thorough characterization standards, standardizing dosimetry, assessing the kinetics of ions dissolving and enhancing the accuracy of <i>in vitro-in vivo</i> correlation efficiency, also defining restrictions on exposure protection are some of the most important and pressing concerns. This article will explore the past advancement and potential prospects of nanotoxicology, standard models, emphasizing significant findings from earlier studies and examining current challenges, giving insight on the way forward. Nanotoxicology ; Data science ; Nanotechnology ; Engineering ethics ; Engineering ; Computer science ; Materials science ; Nanoparticle Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Anesthesia and Neurotoxicity Research
Authors: Lixia Wu | Yu Zhu | Jing Yuan | Xiaozhong Guo | Qian‐Feng Zhang
Source: Journal of Materials Science and Chemical Engineering (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Volatile Organic Compounds (VOCs) in China: Progress and Prospects of Research on Treatment Technologies and Policy Provisions Volatile organic compounds (VOCs) are an atmospheric pollutant with a boiling point of 50˚C - 260˚C at room temperature and pressure. They are precursors of sulfur dioxide and ozone, which can seriously pollute the atmosphere and endanger human health. After the “14th Five-Year Plan”, VOCs, instead of SO2, became one of the five indicators of China’s atmospheric governance. As a result, the government’s efforts to control VOCs have increased significantly. VOCs governance mustn’t be delayed. This paper provides a comprehensive summary and analysis of VOCs governance, covering the classification of VOCs, analysis of VOC governance technology (with a focus on end-of-pipe governance technology), national policy regulations, current governance shortcomings, and a forward-looking perspective on the future direction of VOCs governance, emphasizing healthy and sustainable development. Materials science ; China ; Engineering ethics ; Environmental chemistry ; Volatile organic compound ; Waste management ; Environmental planning ; Organic chemistry ; Environmental science ; Political science ; Engineering ; Law Catalytic Processes in Materials Science ; Industrial Gas Emission Control ; Atmospheric chemistry and aerosols
Authors: Daniel W. Armstrong | Saba Aslani | Jordan Nafie | Yong Wu | J. Fraser Stoddart
Source: JACS Au (article, 2024-12-19)
Field: Chemistry — Spectroscopy

Actions and Interactions of Mirror-Image Cyclodextrins Cyclodextrins (CDs) were the first identified molecules and arguably the most consequential molecules in the areas of macrocyclic science and technology. As carbohydrates, their intrinsic architecture and chirality have played a fundamental role in their response to and effect on guest molecules. Indeed, the nature of inclusion complexation was formalized with CD-based hosts. A recent report on the first synthesis of unnatural mirror-image l-cyclodextrins foreshadows a new era of stereochemical research involving macrocyclic entities. Here, we show the inherently difficult, but rapid and sensitive, separation of enantiomeric CDs. The absolute configurations of CD antipodes have been investigated and distinguished by vibrational circular dichroism (VCD). Results indicated that the most intense VCD band at 1150 cm<sup>-1</sup> arises from the C-O stretching of the glucosidic bonds lining the CD torus. It follows that chiroptical radiation can excite either d- or l-CD selectively. The enzymatic susceptibilities of mirror-image CDs are vastly different, suggesting the possibility of different biochemical and medicinal uses. The electrophoretic migration of small chiral molecules, e.g., amino acids is easily and predictably reversed with d- and l-CDs. Circular dichroism ; Chirality (physics) ; Enantiomer ; Molecule ; Chemistry ; Vibrational circular dichroism ; Stereochemistry ; Crystallography ; Physics ; Organic chemistry ; Chiral symmetry Molecular spectroscopy and chirality ; Analytical Chemistry and Chromatography ; Protein Structure and Dynamics
Authors: Miguel Ramos | Miquel Solà | Albert Poater
Source: Journal of Molecular Modeling (review, 2024-09-30)
Field: Chemistry — Organic Chemistry

Hydrophenoxylation of alkynes by gold catalysts: a mini review DFT calculations have played a key role in promoting the activation of alkynes, in particular the hydrophenoxylation of alkynes by metal-based catalysts. They not only help identify the most efficient and selective catalysts but also aid in screening for those capable of performing a dual metal catalytic mechanism. The most commonly used functionals are BP86 and B3LYP, with the SVP and 6-31G(d) basis sets employed for geometry optimizations, and M06 with TZVP or 6-311G(d,p) basis sets used for single-point energy calculations in a solvent. Grimme dispersion correction has been explicitly added either in the solvent single point energy calculations or in the gas phase geometry optimizations or in both. To point out that M06 implicitly includes part of this dispersion scheme. Catalysis ; Hydroamination ; Combinatorial chemistry ; Context (archaeology) ; Chemistry ; Nanotechnology ; Homogeneous catalysis ; Computational chemistry ; Materials science ; Organic chemistry Catalytic Alkyne Reactions ; Catalysis and Hydrodesulfurization Studies ; Organometallic Complex Synthesis and Catalysis
Authors: Mathieu Doucet | Riccardo Candeago | Hanyu Wang | James F. Browning | Xiao Su
Source: The Journal of Physical Chemistry Letters (article, 2024-04-16)
Field: Materials Science — Materials Chemistry

Studying Transient Phenomena in Thin Films with Reinforcement Learning Neutron reflectometry has long been a powerful tool to study the interfacial properties of energy materials. Recently, time-resolved neutron reflectometry has been used to better understand transient phenomena in electrochemical systems. Those measurements often comprise a large number of reflectivity curves acquired over a narrow <i>q</i> range, with each individual curve having lower information content compared to a typical steady-state measurement. In this work, we present an approach that leverages existing reinforcement learning tools to model time-resolved data to extract the time evolution of structure parameters. By mapping the reflectivity curves taken at different times as individual states, we use the Soft Actor-Critic algorithm to optimize the time series of structure parameters that best represent the evolution of an electrochemical system. We show that this approach constitutes an elegant solution to the modeling of time-resolved neutron reflectometry data. Reflectometry ; Neutron reflectometry ; Reinforcement learning ; Transient (computer programming) ; Neutron ; Materials science ; Range (aeronautics) ; Computer science ; Reflectivity ; Work (physics) ; Biological system ; Optics ; Neutron scattering ; Artificial intelligence ; Physics ; Composite material ; Small-angle neutron scattering ; Time domain ; Thermodynamics ; Nuclear physics ; Computer vision Machine Learning in Materials Science ; Fuel Cells and Related Materials ; Advanced Electron Microscopy Techniques and Applications
Authors: D.M. Hoat | J. Guerrero-Sánchez
Source: Materials Advances (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

Hole doping at Sn sublattice of the buckled honeycomb SnX (X = S and Se) monolayer: an efficient functionalization approach Stable honeycomb SnX (X = S and Se) monolayers are functionalized by doping with IA- and IIIA-group atoms for spintronic applications. Monolayer ; Surface modification ; Doping ; Honeycomb ; Materials science ; Honeycomb structure ; Condensed matter physics ; Nanotechnology ; Composite material ; Chemistry ; Physics ; Optoelectronics ; Physical chemistry 2D Materials and Applications ; ZnO doping and properties ; Physics of Superconductivity and Magnetism
Authors: Arkaitz Fidalgo-Marijuán | Idoia Ruiz de Larramendi | Gotzone Barandika
Source: Nanomaterials (article, 2024-02-21)
Field: Chemistry — Inorganic Chemistry

Superprotonic Conductivity in a Metalloporphyrin-Based SMOF (Supramolecular Metal–Organic Framework) Metal-organic frameworks and supramolecular metal-organic frameworks (SMOFs) exhibit great potential for a broad range of applications taking advantage of the high surface area and pore sizes and tunable chemistry. In particular, metalloporphyrin-based MOFs and SMOFs are becoming of great importance in many fields due to the bioessential functions of these macrocycles that are being mimicked. On the other hand, during the last years, proton-conducting materials have aroused much interest, and those presenting high conductivity values are potential candidates to play a key role in some solid-state electrochemical devices such as batteries and fuel cells. In this way, using metalloporphyrins as building units we have obtained a new crystalline material with formula [H(bipy)]<sub>2</sub>[(MnTPPS)(H<sub>2</sub>O)<sub>2</sub>]·2bipy·14H<sub>2</sub>O, where bipy is 4,4'-bipyidine and TPPS<sup>4-</sup> is the <i>meso</i>-tetra(4-sulfonatephenyl) porphyrin. The crystal structure shows a zig-zag water chain along the [100] direction located between the sulfonate groups of the porphyrin. Taking into account those structural features, the compound was tested for proton conduction by complex electrochemical impedance spectroscopy (EIS). The as-obtained conductivity is 1 × 10<sup>-2</sup> S·cm<sup>-1</sup> at 40 °C and 98% relative humidity, which is a remarkably high value. Porphyrin ; Supramolecular chemistry ; Metal-organic framework ; Electrochemistry ; Conductivity ; Materials science ; Metal ; Dielectric spectroscopy ; Nanotechnology ; Crystal structure ; Crystallography ; Chemistry ; Photochemistry ; Physical chemistry ; Electrode Metal-Organic Frameworks: Synthesis and Applications ; Fuel Cells and Related Materials ; Covalent Organic Framework Applications
Authors: Francisco Malaret
Source: Metals (article, 2024-03-29)
Field: Materials Science — Materials Chemistry

Semi-Quantitative Categorization Method for the Corrosion Behavior of Metals Based on Immersion Test Corrosion processes are complex in nature and their studies have become an interdisciplinary research field, combining fundamental sciences and engineering. As the quantification of corrosion processes is affected by many variables, standard guidelines to study such phenomena had been developed, such as ASME and ISO, and are broadly used in industry and academics. They describe methods to perform immersion test experiments and to quantify the corrosion rates of metals exposed to corrosive environments, but do not provide any guidelines for post-exposure analysis of the as-obtained corroded samples, which might provide useful information to understand the underlying physicochemical mechanisms of corrosion. This knowledge is useful for selecting optimal construction materials and developing corrosion prevention strategies. In this work, a semi-quantitative categorization method of the corrosion behavior of metals exposed to a corrosive medium based on their mass loss and aspect is presented. For each category, the mathematical aspects of gravimetric measurements of mass change rate and the analytical techniques that can be used for the characterization of materials are discussed. The following method does not intend to replace industrial standards, but to expand them in order to maximize the amount of information that can be extracted from immersion tests. Corrosion ; Immersion (mathematics) ; Categorization ; Gravimetric analysis ; Process engineering ; Computer science ; Materials science ; Biochemical engineering ; Metallurgy ; Environmental science ; Engineering ; Artificial intelligence ; Chemistry ; Mathematics Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Non-Destructive Testing Techniques
Authors: Clodagh M. Carr | Frederike Göttsch | Bruno Francesco Rodrigues de Oliveira | Pedro A. Sánchez‐Murcia | Stephen A. Jackson | Ren Wei | David J. Clarke | Uwe T. Bornscheuer | Alan D. W. Dobson
Source: Microbial Biotechnology (article, 2024-06-01)
Field: Materials Science — Biomaterials

Identification and expression of MarCE, a marine carboxylesterase with synthetic ester‐degrading activity Carboxylic ester hydrolases with the capacity to degrade polyesters are currently highly sought after for their potential use in the biological degradation of PET and other chemically synthesized polymers. Here, we describe MarCE, a carboxylesterase family protein identified via genome mining of a Maribacter sp. isolate from the marine sponge Stelligera stuposa. Based on phylogenetic analysis, MarCE and its closest relatives belong to marine-associated genera from the Cytophaga-Flavobacterium-Bacteroides taxonomic group and appear evolutionarily distinct to any homologous carboxylesterases that have been studied to date in terms of structure or function. Molecular docking revealed putative binding of BHET, a short-chain PET derivative, onto the predicted MarCE three-dimensional structure. The synthetic ester-degrading activity of MarCE was subsequently confirmed by MarCE-mediated hydrolysis of 2 mM BHET substrate, indicated by the release of its breakdown products MHET and TPA, which were measured, respectively, as 1.28 and 0.12 mM following 2-h incubation at 30°C. The findings of this study provide further insight into marine carboxylic ester hydrolases, which have the potential to display unique functional plasticity resulting from their adaptation to complex and fluctuating marine environmentsw. Carboxylesterase ; Hydrolysis ; Chemistry ; Hydrolase ; Biochemistry ; Polyester ; Esterase ; Enzyme ; Stereochemistry ; Sponge ; Biology ; Organic chemistry biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution ; Enzyme Catalysis and Immobilization
Authors: Yijia Hao | Tuo Ji | Jing Zhang | Weilin Chen
Source: Nano Research (article, 2024-12-16)
Field: Materials Science — Polymers and Plastics

Triboelectric nanogenerator based on changing the nanomorphology of polyoxometalates for gait monitoring of teenagers Timely monitoring abnormal gaits of teenagers is crucial for their physical health and development. Triboelectric nanogenerators (TENGs) are widely used in the wearable field. Choosing high-performance and safe triboelectric materials to monitor abnormal gaits remains challenging. Polyoxometalates (POMs) nanomaterials can effectively serve as triboelectric materials due to rich surface morphology and large specific surface area. Herein, six different sized POMs nanorods (Ag<sub>4</sub>SiW<sub>12</sub>O<sub>40</sub>·<i>n</i>H<sub>2</sub>O) synthesized through self-assembly of POMs (H<sub>4</sub>SiW<sub>12</sub>O<sub>40</sub>·<i>n</i>H<sub>2</sub>O) were used as triboelectric materials. The TENG composed of nanorod with a diameter of 100 nm and a length of 400–1000 nm has optimal performance with the voltage, current density and charge are 104.3 V, 1127.1 μA·m<sup>−2</sup>, and 15.38 nC, respectively, which are more than two times of the TENG composed of POMs (H<sub>4</sub>SiW<sub>12</sub>O<sub>40</sub>·<i>n</i>H<sub>2</sub>O). The optimized TENG maintained a voltage of around 100 V throughout the 1000 s stability test. The maximum power amounts to 25.2 μW at 500 MΩ external resistance. The reasons for the improved performance of nanorods TENG compared to POMs TENG are the increase in roughness and surface potential, which was confirmed through atomic force microscopy (AFM) and kelvin probe force microscopy (KPFM) testing. Furthermore, optimized TENG was applied to the feet of different teenagers and the left and right feet of the same person to monitor abnormal gait. The changes in voltage can sensitively display the inconsistency and abnormal situations of gaits. This study confirms the potential and unique advantages of POMs nanomaterials as triboelectric materials and provides a design scheme for gait monitoring. Triboelectric effect ; Nanogenerator ; Nanotechnology ; Gait ; Materials science ; Physical medicine and rehabilitation ; Medicine ; Composite material Conducting polymers and applications ; Advanced Sensor and Energy Harvesting Materials ; Polyoxometalates: Synthesis and Applications
Authors: Nina Strasser | Sandro Wieser | Egbert Zojer
Source: International Journal of Molecular Sciences (article, 2024-03-05)
Field: Chemistry — Inorganic Chemistry

Predicting Spin-Dependent Phonon Band Structures of HKUST-1 Using Density Functional Theory and Machine-Learned Interatomic Potentials The present study focuses on the spin-dependent vibrational properties of HKUST-1, a metal-organic framework with potential applications in gas storage and separation. Employing density functional theory (DFT), we explore the consequences of spin couplings in the copper paddle wheels (as the secondary building units of HKUST-1) on the material's vibrational properties. By systematically screening the impact of the spin state on the phonon bands and densities of states in the various frequency regions, we identify asymmetric -COO- stretching vibrations as being most affected by different types of magnetic couplings. Notably, we also show that the DFT-derived insights can be quantitatively reproduced employing suitably parametrized, state-of-the-art machine-learned classical potentials with root-mean-square deviations from the DFT results between 3 cm<sup>-1</sup> and 7 cm<sup>-1</sup>. This demonstrates the potential of machine-learned classical force fields for predicting the spin-dependent properties of complex materials, even when explicitly considering spins only for the generation of the reference data used in the force-field parametrization process. Density functional theory ; Spins ; Spin (aerodynamics) ; Parametrization (atmospheric modeling) ; Phonon ; Spin states ; Condensed matter physics ; Physics ; Materials science ; Quantum mechanics ; Thermodynamics Metal-Organic Frameworks: Synthesis and Applications ; Advanced NMR Techniques and Applications ; Machine Learning in Materials Science