jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Corentin Villot | Tong Huang | Ka Un Lao
Source: The Journal of Chemical Physics (article, 2023-07-24)
Field: Materials Science — Materials Chemistry

Accurate prediction of global-density-dependent range-separation parameters based on machine learning In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0-1 and only five systems (0.07%) with an absolute error larger than 0.01 a0-1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model. Ab initio ; Range (aeronautics) ; Transferability ; Perturbation theory (quantum mechanics) ; Density functional theory ; Series (stratigraphy) ; Statistical physics ; Computational physics ; Algorithm ; Mathematics ; Computer science ; Physics ; Materials science ; Chemistry ; Computational chemistry ; Quantum mechanics ; Statistics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Luminescence Properties of Advanced Materials
Authors: Zewei Liu | Qibin Xia | Bichun Huang | Yi Hao | Jian Yan | Xin Chen | Feng Xu | Hongxia Xi
Source: Molecules (article, 2023-10-31)
Field: Chemistry — Inorganic Chemistry

Prediction of Xe/Kr Separation in Metal-Organic Frameworks by a Precursor-Based Neural Network Synergistic with a Polarizable Adsorbate Model Adsorption and separation of Xe/Kr are significant for making high-density nuclear energy environmentally friendly and for meeting the requirements of the gas industry. Enhancing the accuracy of the adsorbate model for describing the adsorption behaviors of Xe and Kr in MOFs and the efficiency of the model for predicting the separation potential (SP) value of Xe/Kr separation in MOFs helps in searching for promising MOFs for Xe/Kr adsorption and separation within a short time and at a low cost. In this work, polarizable and transferable models for mimic Xe and Kr adsorption behaviors in MOFs were constructed. Using these models, SP values of 38 MOFs at various temperatures and pressures were calculated. An optimal neural network model called BPNN-SP was designed to predict SP value based on physical parameters of metal center (electronegativity and radius) and organic linker (three-dimensional size and polarizability) combined with temperature and pressure. The regression coefficient value of the BPNN-SP model for each data set is higher than 0.995. MAE, MBE, and RMSE of BPNN-SP are only 0.331, -0.002, and 0.505 mmol/g, respectively. Finally, BPNN-SP was validated by experiment data from six MOFs. The transferable adsorbate model combined with the BPNN-SP model would highly improve the efficiency for designing MOFs with high performance for Xe/Kr adsorption and separation. Electronegativity ; Polarizability ; Adsorption ; Chemistry ; Artificial neural network ; Krypton ; Metal-organic framework ; Xenon ; Thermodynamics ; Molecule ; Physical chemistry ; Organic chemistry ; Machine learning ; Computer science ; Physics Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Carbon Dioxide Capture Technologies
Authors: Ronald L. Aquino
Source: International Journal of Biosciences (IJB) (article, 2023-05-04)
Field: Chemistry — Analytical Chemistry

Forecasting Volume of Corn Production through Neural Network Model: A Post-harvest Monitoring Tool The paper deals with the forecasting of volume (in tonnes) of corn production relative to the harvested farmed area during the second semester of agricultural cropping.Time series data used were obtained from the open stat database published by the Philippine Statistics Authority from the second semester of 1987 to second semester of 2022.Artificial Neural Network (ANN) models were developed, trained and validated to forecast the volume of corn production.Statistical errors such as Root Mean Square Error (RMSE) were computed and compared to identify the most suitable model to forecast the corresponding volume.ANN ( ) model was identified and used to forecast the volume of corn production.The two sets of data, namely actual and forecast volumes of production, were found to have statistically no significant difference, which implies that the model gives forecast values that are relatively close to the actual ones. Production (economics) ; Artificial neural network ; Volume (thermodynamics) ; Environmental science ; Agricultural engineering ; Agronomy ; Agroforestry ; Computer science ; Engineering ; Biology ; Artificial intelligence ; Economics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis
Authors: Ana R. R. P. Almeida | Bruno D. A. Pinheiro | Manuel J.S. Monte
Source: Molecules (article, 2023-02-07)
Field: Chemistry — Organic Chemistry

Phase Transitions Equilibria of Five Dichlorinated Substituted Benzenes This work reports an experimental study aiming to determine the thermodynamic properties of five chlorinated compounds with environmental impact. The vapor pressures of the crystalline phases of three isomers of dichlorobenzoic acid (2,4-, 2,5-, and 2,6-) and 2,6-dichlorobenzonitrile were measured at several temperatures using the Knudsen effusion technique. Another technique (a static method based on capacitance diaphragm manometers) allowed the measurement of the vapor pressures of both the crystalline and liquid phases of 2,4-dichlorobenzonitrile between 303.0 and 380.0 K. This latter technique also enabled the measurement of sublimation vapor pressures of 2,6-dichlorobenzonitrile over a larger range interval of temperatures, <i>T</i> = 328.7 and 391.8 K. The standard molar enthalpy, entropy, and Gibbs energy of sublimation (for all the compounds studied) and vaporization (for 2,4-dichlorobenzonitrile) were derived, at reference temperatures, from the experimental vapor pressure results. The temperatures and enthalpies of fusion and the isobaric heat capacities of the five crystalline-substituted benzenes were determined using differential scanning calorimetry. The contributions of the three substituents (-COOH, -CN, and -Cl) to the sublimation thermodynamic properties of the compounds studied were discussed. Vapor pressure ; Chemistry ; Sublimation (psychology) ; Enthalpy ; Knudsen number ; Differential scanning calorimetry ; Vaporization ; Thermodynamics ; Enthalpy of sublimation ; Gibbs free energy ; Isobaric process ; Standard enthalpy of formation ; Enthalpy of fusion ; Physical chemistry ; Standard molar entropy ; Atmospheric temperature range ; Lattice energy ; Analytical Chemistry (journal) ; Organic chemistry ; Melting point ; Crystal structure Chemical Thermodynamics and Molecular Structure ; Free Radicals and Antioxidants ; Thermal and Kinetic Analysis
Authors: Lauren McNamara | Ai-Mei Zhou | Tijana Rajh | Lei Sun | John S. Anderson
Source: ChemRxiv (preprint, 2023-08-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Realizing Solution-Phase Room Temperature Quantum Coherence in a Tetrathiafulvalene-Based Diradicaloid Complex Molecular electron spins are promising candidates as scalable and tunable qubits but often suffer from air sensitivity or other undesirable decomposition pathways. Furthermore, significant spin‒lattice relaxation and nuclear spin-mediated decoherence limit their applications. While significant advances in the synthesis of new molecular electron spin qubit candidates have led to improved coherence lifetimes, one key question is whether coherence can be maintained under conditions relevant for employment as quantum sensors, for instance in solution and at room temperature for sensing in biological systems. Here we report a tetrathiafulvalene-based molecular qubit candidate with spin centered on a nuclear spin-free bridging ligand. This unique air and water-stable scaffold exhibits a long spin decoherence time of hundreds of nanoseconds at ambient temperatures and in nuclear spin-rich protonated solvents. These results distinguish this system as a promising candidate for the development of novel room temperature, solution-phase quantum sensing technologies, and suggest that molecular electron spin qubits can be ideal candidates for these applications. Quantum decoherence ; Qubit ; Spin engineering ; Coherence (philosophical gambling strategy) ; Spins ; Quantum ; Quantum computer ; Chemistry ; Chemical physics ; Physics ; Nanotechnology ; Materials science ; Quantum mechanics ; Condensed matter physics ; Spin polarization ; Electron Magnetism in coordination complexes ; Electron Spin Resonance Studies ; Organic and Molecular Conductors Research
Authors: Srwa Ramadhan Hamza
Source: International Journal of Membrane Science and Technology (article, 2023-10-28)
Field: Chemistry — Analytical Chemistry

FLAVOR Enhancers in Food Processing: Spectrophotometric Determination of Maltol and Ethyl Maltol in Some Commercial Food Samples During Different Storage Conditions It is important for flavor additives to maintain adequate thermal stability under high temperature conditions. Since many excellent fragrances are organic and have relatively small molecular weights, they lack thermal stability. As a result, a rapid and accurate method has been developed for simultaneous determination of maltol and ethyl maltol by reaction with iron(III) in sulfuric acid solution. This reaction was the basis for an indirect spectrophotometric method, which followed the development of the pink ferroin product (?max = 520 nm). It appears that ethyl maltol and maltol follow Beer's law at concentrations of 0.5–20.0 mg/L according to the optimized method. According to the alternative standard method, the LOD values for maltol and ethyl maltol are 0.2 mg/L and 0.3 mg/L, respectively. Commercial food samples were successfully analyzed using the proposed methods. A study was conducted to determine how different storage conditions affected the concentrations of maltol and ethyl maltol. High temperature and sunlight lead to decomposition of these two flavor enhancer concentrations more than 10%. Maltol ; Chemistry ; Flavor ; Chromatography ; Nuclear chemistry ; Organic chemistry ; Food science Dye analysis and toxicity ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Xiang Yu | Yong‐Hui Wang | Guangqiang Hou | Jingyan Ye | Rabah Boukherroub
Source: Preprints.org (preprint, 2023-11-15)
Field: Materials Science — Materials Chemistry

Toughness Characterization and Toughening Mechanism of Diamond-like Carbon Films Diamond-like carbon (DLC) films have a promising tribological application in green precision manufacturing, but their toughness represents a serious issue in the way of their application perspective. The film thickness is on the micrometer scale and makes conventional methods unsuitable for its toughness characterization. The absence of an accepted method for characterizing the DLC toughness has hindered the related research on the development of toughening methods and understanding the mechanism. This work intends to explore a relatively simple and acceptable characterization method to measure the film toughness. Moreover, toughening mechanisms of DLC films are proposed during the characterization to reveal the toughening mechanism. The toughness can be fully characterized through combining impact toughness and scratch toughness. The impact toughness can be obtained by observing the size of the indentation and the crack state around the indentation in the impact experiment. The scratch toughness could be assessed by combining the scratch morphology and Crack Propagation Resistance (CPRS). The improvement of film toughness should be carried out from two aspects: preventing microcrack initiation and suppressing crack propagation. Appropriate doping of non-carbide metal particles can effectively improve the toughness of the film, and there are seven main factors affecting the toughening of the film. Five toughening mechanisms of non-carbide metals from film preparation to test stage are revealed during the investigation of the change patterns. Toughness ; Materials science ; Indentation ; Composite material ; Toughening ; Fracture toughness ; Scratch ; Nanoindentation ; Carbide ; Characterization (materials science) ; Nanotechnology Diamond and Carbon-based Materials Research ; Metal and Thin Film Mechanics ; Force Microscopy Techniques and Applications
Authors: Sufen Wei | Yi Liu | Qianqian Shi | Tinglin He | Feng Shi | Ming-kwei Lee
Source: Preprints.org (preprint, 2023-07-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Further characterization of the polycrystalline p-type β-Ga2O3 films grown through thermal oxidation of GaN at 1000 to 1100 °C in N2O atmosphere The development of good conductivity p-type β-Ga2O3 is critical to realize its devices and applications. The nitrogen-doped p-type β-Ga2O3 films with enhanced conductivity characteristics were prepared through the thermal oxidation of GaN in the N2O atmosphere. Further measurements were performed on the oxidized films at 1000, 1050, and 1100 °C to have insight into the underlying mechanism of the thermally activated transformation process. The room temperature photoluminescence (PL) spectra demonstrated a moderate ultraviolet emission peak at 246 nm, confirming the generation of gallium oxide with a band gap of ~5.0 eV. The normalized X-ray diffraction (XRD), the high-resolution transmission electron microscopy (HRTEM), and the selected area electron diffraction (SAED) patterns were used to confirm the characteristic of polycrystalline and anisotropic growth. Then, the effects of the oxidation temperature on the amount of incorporated nitrogen were analyzed using secondary ion mass spectrometry (SIMS). Moreover, the ionization energy of the acceptor of films oxidized at 1000, 1050, and 1100 °C was calculated and analyzed using the temperature-dependent Hall test results. The results showed that nitrogen doping was the main contributor to p-type electrical properties. The activation energy of the polycrystalline β-Ga2O3 prepared through thermal oxidation of GaN in the N2O atmosphere was estimated to be 147.175 kJ·mol-1 using the Arrhenius plot, which was considerably lower than that of both dry and wet oxidations of GaN in O2 ambient, thus confirming the efficiency of thermal oxidation of GaN in N2O. Crystallite ; Analytical Chemistry (journal) ; Materials science ; High-resolution transmission electron microscopy ; Photoluminescence ; Selected area diffraction ; Band gap ; Activation energy ; Thermal oxidation ; Oxide ; Transmission electron microscopy ; Chemistry ; Physical chemistry ; Nanotechnology ; Optoelectronics ; Metallurgy Ga2O3 and related materials ; GaN-based semiconductor devices and materials ; ZnO doping and properties
Authors: Mahdiyeh Ghaffari | Gerjen H. Tinnevelt | Marcel C. P. van Eijk | Stanislav Podchezertsev | Geert Postma | Jeroen J. Jansen
Source: arXiv (Cornell University) (preprint, 2023-08-15)
Field: Chemistry — Analytical Chemistry

Mono/Multi-material Characterization Using Hyperspectral Images and Multi-Block Non-Negative Matrix Factorization Plastic sorting is a very essential step in waste management, especially due to the presence of multilayer plastics. These monomaterial and multimaterial plastics are widely employed to enhance the functional properties of packaging, combining beneficial properties in thickness, mechanical strength, and heat tolerance. However, materials containing multiple polymer species need to be pretreated before they can be recycled as monomaterials and therefore should not end up in monomaterial streams. Industry 4.0 has significantly improved materials sorting of plastic packaging in speed and accuracy compared to manual sorting, specifically through Near Infrared Hyperspectral Imaging (NIRHSI) that provides an automated, fast, and accurate material characterization, without sample preparation. Identification of multimaterials with HSI however requires novel dedicated approaches for chemical pattern recognition. Non negative Matrix Factorization, NMF, is widely used for the chemical resolution of hyperspectral images. Chemically relevant model constraints may make it specifically valuable to identify multilayer plastics through HSI. Specifically, Multi Block Non Negative Matrix Factorization (MBNMF) with correspondence among different chemical species constraint may be used to evaluate the presence or absence of particular polymer species. To translate the MBNMF model into an evidence based sorting decision, we extended the model with an F test to distinguish between monomaterial and multimaterial objects. The benefits of our new approach, MBNMF, were illustrated by the identification of several plastic waste objects. Hyperspectral imaging ; Sorting ; Characterization (materials science) ; Non-negative matrix factorization ; Identification (biology) ; Block (permutation group theory) ; Computer science ; Matrix (chemical analysis) ; Matrix decomposition ; Biological system ; Artificial intelligence ; Polymer ; Pattern recognition (psychology) ; Constraint (computer-aided design) ; Materials science ; Algorithm ; Mathematics ; Nanotechnology ; Composite material ; Engineering ; Mechanical engineering ; Physics ; Ecology Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Stephanie A. Wankowicz | James S. Fraser
Source: ChemRxiv (preprint, 2023-10-30)
Field: Materials Science — Materials Chemistry

Comprehensive Encoding of Conformational and Compositional Protein Structural Ensembles through mmCIF Data Structure In their folded state, biomolecules exchange between multiple conformational states, crucial for their function. However, most structural models derived from experiments and computational predictions only encode a single state. To represent biomolecules more accurately, we must move towards modeling and predicting structural ensembles. Information about structural ensembles exists within experimental data from X-ray crystallography and cryo electron microscopy (cryoEM). While new tools are available to detect conformational and compositional heterogeneity that exist within these ensembles, the legacy PDB data structure does not robustly encapsulate this complexity. We propose modifications to the Macromolecular Crystallographic Information File (mmCIF) to improve the representation and interrelation of conformational and compositional heterogeneity. These modifications will enable improved tools to capture macromolecular ensembles in a way that is human and machine interpretable, potentially catalyzing breakthroughs for ensemble-function predictions, analogous to AlphaFold's achievements with single structure prediction. Conformational ensembles ; Biomolecule ; Protein Data Bank (RCSB PDB) ; Representation (politics) ; Biomolecular structure ; Computer science ; Structural bioinformatics ; Function (biology) ; Protein structure ; Structural biology ; Biological system ; Chemistry ; Nanotechnology ; Materials science ; Biology Enzyme Structure and Function ; Microbial Metabolic Engineering and Bioproduction ; Protein Structure and Dynamics
Authors: Timmo Weidner | Vincent Taupin | Sylvie Demouchy | Karine Gouriet | Antoine Guitton | Patrick Cordier | Alexandre Mussi
Source: Modelling and Simulation in Materials Science and Engineering (article, 2023-11-07)
Field: Materials Science — Materials Chemistry

From electron tomography of dislocations to field dislocation mechanics: application to olivine Abstract We propose a new procedure to extract information from electron tomography and use them as an input in a field dislocation mechanics. Dislocation electron tomography is an experimental technique that provides three-dimensional (3D) information on dislocation lines and Burgers vectors within a thin foil. The characterized 3D dislocation lines are used to construct the spatial distribution of the equivalent Nye dislocation density tensor. The model dislocation lattice incompatibility equation and stress balance equation are solved with a spectral code based on fast Fourier transform algorithms. As an output of the model, one obtains the 3D distribution of mechanical fields, such as strains, rotations, stresses, resolved shear stresses (RSSs) and energy, inside the material. To assess the potential of the method, we consider two regions from a previously compressed olivine sample. Our results reveal significant local variations in local stress fields and RSSs in various slip systems, which can impact the strong plastic anisotropy of olivine and the activation of different dislocation slip systems. It also evidences the built-up of kinematic hardening down to the nanometre scale. Materials science ; Dislocation ; Peierls stress ; Mechanics ; Stress field ; Classical mechanics ; Condensed matter physics ; Dislocation creep ; Physics ; Composite material ; Finite element method ; Thermodynamics Microstructure and mechanical properties ; Advanced Electron Microscopy Techniques and Applications ; Force Microscopy Techniques and Applications