jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alberto Zaragoza | Matías H. Factorovich | Valeria Molinero
Source: ChemRxiv (preprint, 2023-08-20)
Field: Chemistry — Inorganic Chemistry

Multi-Stage Condensation Pathway Minimizes Hysteresis in Water Harvesting with Large-Pore Metal-Organic Frameworks Metal-organic frameworks (MOFs) have emerged as promising materials for atmospheric water harvesting (AWH). Large-pore MOFs provide high water capacity, but their significant hysteresis between sorption and desorption makes them unsuitable for AWH. Co2Cl2(BTDD) is a noteworthy exception. This MOF has large, 2.2 nm diameter one-dimensional pores, and combines both record-high water capacity and minimal hysteresis, making it an excellent material for water capture in arid areas. Sorption reversibility in Co2Cl2(BTDD) has been attributed to continuous water uptake. However, the sharp adsorption/desorption in the isotherms supports a discontinuous first-order transition. Here we use molecular simulations to compute the water adsorption and desorption pathways and isotherms in a Co2Cl2(BTDD) model, to elucidate how does this MOF achieve reversibility despite its large pore size. The simulations reveal a multi-stage mechanism of discontinuous water uptake facilitated by spatial segregation of rows of hydrophilic metal sites bridged by ~1 nm hydrophobic ligands. The multi-stage mechanism breaks the barrier of capillary condensation into smaller, easier to surmount ones, resulting in a facile process despite the sharp density discontinuity between confined liquid and vapor. Our results explain why exchanging Co2+ for Ni2+ or Cl- for F- in the MOF have minimal impact on the condensation and desorption pressures. On the other hand, we predict that a decrease in hydrophilicity of the MOF vertices would strongly increase the hysteresis. We expect that the relationships between spatial distribution of hydrophilic sites and hysteresis unraveled in this study assist the design of water harvesting materials with maximal capacity and reversibility. Hysteresis ; Desorption ; Sorption ; Adsorption ; Condensation ; Capillary condensation ; Materials science ; Water vapor ; Chemical physics ; Chemical engineering ; Metal-organic framework ; Capillary action ; Thermodynamics ; Chemistry ; Composite material ; Physical chemistry ; Organic chemistry Metal-Organic Frameworks: Synthesis and Applications ; Enhanced Oil Recovery Techniques ; Nanopore and Nanochannel Transport Studies
Authors: Anita Rácz | Krisztina László | Szilvia Klébert
Source: Carbon (article, 2023-12-20)
Field: Chemistry — Analytical Chemistry

Qualitative and quantitative chemometric modelling of nanostructured carbon samples based on infrared spectroscopy Rapid population growth necessitates a continuous increase in industrial productivity, with a concomitant environmental burden. During the past few years, nanostructured carbon materials have proved their effectiveness in reducing the usage of several hazardous substances, owing to their distinct characteristics. These properties depend on the type of feedstock and the parameters of pyrolysis. We have developed multivariate prediction models to determine several physical properties of nanostructured carbon samples, which are usually calculated from the adsorption isotherms. Adsorption measurement is a time-consuming and exhaustive process. Therefore, our goal was to provide a fast and environmentally friendly alternative to current methods to determine micropore volume, specific surface area and total pore volume, based on FTIR spectroscopy coupled with chemometric methods. Moreover, we have created classification models, which are capable of predicting from IR spectra what feedstock materials were used. Our support vector machine–based classification model had the best accuracy values, above 0.86. Our classification and regression models have excellent performance and were properly validated, thus they are good alternatives for determining the important qualitative and quantitative features of carbon samples robustly and fast. Raw material ; Carbon fibers ; Materials science ; Multivariate statistics ; Adsorption ; Volume (thermodynamics) ; Process engineering ; Pyrolysis ; Biological system ; Computer science ; Machine learning ; Chemistry ; Organic chemistry ; Thermodynamics ; Engineering ; Composite material Spectroscopy and Chemometric Analyses ; Thermochemical Biomass Conversion Processes ; Advanced Chemical Sensor Technologies
Authors: Christos Gioldasis | Απόστολος Γκάμας | Othonas A. Moultos | Costas Vlahos
Source: Preprints.org (preprint, 2023-06-09)
Field: Chemistry — Organic Chemistry

Chemical Feedback in Templated Reaction-Assembly of Polyelectrolyte Complex Micelles: A Molecular Simulation Study of the Kinetics and Clustering The chemical feedback between building blocks in templated polymerization of diblock copolymers and their consecutive micellization was studied for the first time by means of coarse-grained molecular dynamics simulations. Using a stochastic polymerization model, we were able to reproduce the experimental findings on the effect of chemical feedback on the polymerization rates at low and high solution concentrations. The size and shape of micelles were computed using a newly development software in python conjugated with graph theory. In full agreement with the experiments, our simulations revealed that micelles formed by the templated micellization are more spherical and have lower radius of gyration than those formed by the traditional two-step micellization method. Understanding the underlying mechanisms in templated reaction/assembly of polymers will help for rational design of new synthetic supramolecular materials. Micelle ; Radius of gyration ; Polymerization ; Supramolecular chemistry ; Copolymer ; Molecular dynamics ; Materials science ; Polymer ; Kinetics ; Polymer chemistry ; Chemistry ; Computational chemistry ; Molecule ; Physical chemistry ; Organic chemistry ; Physics Advanced Polymer Synthesis and Characterization ; Polymer Surface Interaction Studies ; biodegradable polymer synthesis and properties
Authors: S. A. Sarkisov | Л. В. Иванова | Olga V. Primerova | В. Н. Кошелев
Source: Processes (article, 2023-11-22)
Field: Chemistry — Analytical Chemistry

Determination of N-Paraffins Content in Crude Oil via Near-Infrared Spectroscopy Associated with Chemometric Approaches This study explores the potential application of NIR spectroscopy coupled with different linear and nonlinear models for rapid evaluation of n-alkanes in crude oil. Samples for calibration were 30 model mixtures of n-eicosane in crude oil samples with a concentration of 1–15%. The prediction models were established based on 21 methods: linear regression, regression trees, support vector machines, Gaussian process regression, ensembles of trees, and neural networks. The spectral range 4500–9000 cm−1 was determined to be the most informative for prediction. The prediction capability of lineal regression methods turned out to be unsatisfactory. Nonlinear models were preferred over linear models; better results were obtained using the regression trees method, including «fine tree» (RMSE = 2.8635) and neural networks (RMSE = 2.0157). The LS-SVM model exhibited satisfactory prediction performance (R2 = 0.96, RMSE = 0.91), as did the Gaussian Process Regression Matern 5.2 GPR (R2 = 0.96, RMSE = 1.03) and Gaussian Process Regression (Rational Quadratic) (R2 = 0.95, RMSE = 1.04). Among the 21 chemometric algorithms, the best and weakest models were the LS-SVM and PLSR models, respectively. The LS-SVM model was the optimal model for the prediction of n-alkanes content in crude oil. Mean squared error ; Support vector machine ; Artificial neural network ; Linear regression ; Calibration ; Mathematics ; Regression analysis ; Partial least squares regression ; Statistics ; Regression ; Biological system ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Junhao Chang | Zengtao Chen | James D. Hogan
Source: Modelling—International Open Access Journal of Modelling in Engineering Science (article, 2023-05-05)
Field: Materials Science — Ceramics and Composites

Molecular Dynamics Simulations Correlating Mechanical Property Changes of Alumina with Atomic Voids under Triaxial Tension Loading The functionalization of nanoporous ceramics for applications in healthcare and defence necessitates the study of the effects of geometric structures on their fundamental mechanical properties. However, there is a lack of research on their stiffness and fracture strength along diverse directions under multi-axial loading conditions, particularly with the existence of typical voids in the models. In this study, accurate atomic models and corresponding properties were meticulously selected and validated for further investigation. Comparisons were made between typical material geometric and elastic properties with measured results to ensure the reliability of the selected models. The mechanical behavior of nanoporous alumina under multiaxial stretching was explored through molecular dynamics simulations. The results indicated that the stiffness of nanoporous alumina ceramics under uniaxial tension was greater, while the fracture strength was lower compared to that under multiaxial loading. The fracture of nanoporous ceramics under multi-axial stretching, was mainly dominated by void and crack extension, atomic bond fracture, and cracking with different orientations. Furthermore, the effects of increasing strain rates on the void volume fraction were found to be similar across different initial radii. It was also found that the increasing tension loading rates had greater effects on decreasing the fracture strain. These findings provide additional insight into the fracture mechanisms of nanoporous ceramics under complex loading states, which can also contribute to the development of higher-scale models in the future. Nanoporous ; Materials science ; Composite material ; Ceramic ; Stiffness ; Void (composites) ; Fracture (geology) ; Atomic units ; Molecular dynamics ; Cracking ; Tension (geology) ; Fracture mechanics ; Volume fraction ; Ultimate tensile strength ; Nanotechnology Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Microstructure and mechanical properties
Authors: Tevhide Ayça Yıldız | Murat Durandurdu
Source: Journal of the American Ceramic Society (article, 2023-01-02)
Field: Materials Science — Materials Chemistry

Ab initio study of boron‐rich amorphous boron carbides Abstract Amorphous boron carbide compositions having high B contents (B x C 1− x , 0.50 ≤ x ≤ 0.95) are systematically created by way of ab initio molecular dynamics calculations, and their structural, electrical, and mechanical characteristics are inclusively investigated. The coordination number of both B and C atoms increases progressively with increasing B/C ratio and more close‐packed materials having pentagonal pyramid motifs form. An amorphous diamond‐like local arrangement is found to be dominant up to 65% B content, and beyond this content, a mixed state of amorphous diamond– and B‐like structures is perceived in the models because sp 3 hybridization around C atoms is still leading one for all compositions. The pentagonal pyramid motifs around C atoms are anticipated to appear beyond 65% content. The intericosahedral linear C–B–C chains do not form in any model. All amorphous boron carbides are semiconducting materials. The mechanical properties gradually increase with increasing B concentration, and some amorphous compositions are proposed to be hard materials on the basis of their Vickers hardness estimation. Amorphous solid ; Boron ; Boron carbide ; Materials science ; Diamond ; Carbide ; Ab initio ; Crystallography ; Coordination number ; Ab initio quantum chemistry methods ; Amorphous carbon ; Metallurgy ; Chemistry ; Ion ; Molecule ; Organic chemistry Boron and Carbon Nanomaterials Research ; Diamond and Carbon-based Materials Research ; MXene and MAX Phase Materials
Authors: Behnam Moeini | John M. Linford | Neal B. Gallagher | Matthew R. Linford
Source: Surface and Interface Analysis (article, 2023-11-14)
Field: Materials Science — Surfaces, Coatings and Films

Surface analysis insight note: An example of a cluster analysis of spectra from an X‐ray photoelectron spectroscopy image Identification of similar and dissimilar spectra is an important part of analyzing X‐ray photoelectron spectroscopy (XPS) images. Cluster analysis (CA) is a commonly used exploratory data analysis (EDA) method that groups similar spectra in a data set. CA can be performed in either an agglomerative fashion, for example, using Ward's method, which involves successively linking together/clustering the most similar spectra in a data set, or in a divisive fashion, for example, using the K‐means approach, which involves partitioning all the data into a specified number of clusters. In this note, we show the application of CA to an XPS image dataset. The use of Ward's method identified two major clusters in the image, where one of the clusters appeared as two subclusters. The K‐means image based on two clusters agrees well with previous analyses of the same image. The average spectra corresponding to clusters helped confirm the assignments made by the CA algorithms, as did a multivariate curve resolution (MCR) analysis of the interior region identified in our cluster analysis. “Elbow” plots can help determine the number of clusters to keep in K‐means clustering. The combination of the agglomerative and divisive forms of CA, where the first informs the second, can be effective in revealing the structures of XPS image datasets. The Procrustean bed is a metaphor for overfitting and underfitting in EDA. X-ray photoelectron spectroscopy ; Cluster (spacecraft) ; Hierarchical clustering ; Cluster analysis ; Spectral line ; Overfitting ; Pattern recognition (psychology) ; Complete-linkage clustering ; Set (abstract data type) ; Data set ; Chemistry ; Resolution (logic) ; Computer science ; Artificial intelligence ; Physics ; Nuclear magnetic resonance ; Fuzzy clustering ; Artificial neural network Electron and X-Ray Spectroscopy Techniques ; Geochemistry and Geologic Mapping ; Machine Learning in Materials Science
Authors: Tingting Liu | Zuliang Wang | Ting Zhang | Shang Bingwan | Tang Wenshun | Qiao Fengkang | Xue Yanan | Zhipeng Li | Feifan Liu
Source: Research Square (preprint, 2023-12-29)
Field: Chemistry — Analytical Chemistry

Classification of Sugar Content of Kiwi Fruit Based on Deep Learning and Near Infrared Spectrum <title>Abstract</title> In recent years, the kiwifruit industry has undergone rapid development. The quality of kiwifruit significantly impacts its market price. The current manual grading system for kiwifruit is inefficient and lacks accuracy. Therefore, the application of intelligent methods for the rapid classification of kiwifruit has become a prominent topic in kiwifruit research. Sugar content is a critical factor in evaluating kiwifruit quality. This study establishes a non-destructive detection and classification model for sugar content using near-infrared spectroscopy and deep learning techniques. Initially, near-infrared spectra and sugar content values of kiwifruit were gathered. Following the classification of kiwifruit samples based on sugar content standards, two preprocessing methods – MSC and SNV – along with four deep learning network structures – LeNet, AlexNet, VGG, and ResNet – were utilized to construct classification models for the spectra and sugar content. Through comparison of training set accuracy, test set accuracy, and confusion matrix of the test set, the combination of MSC preprocessing and the ResNet classification model was identified as the optimal approach, achieving a test set accuracy of 100%. These findings indicate that the classification model established using near-infrared spectrum and deep learning effectively promotes kiwifruit classification based on sugar content. Sugar ; Artificial intelligence ; Deep learning ; Computer science ; Test set ; Preprocessor ; Machine learning ; Pattern recognition (psychology) ; Mathematics ; Chemistry ; Food science Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Koichi Kitahara | Hiroyuki Takakura | Yutaka Iwasaki | Kaoru Kimura
Source: MATERIALS TRANSACTIONS (article, 2023-12-24)
Field: Materials Science — Materials Chemistry

Phase Equilibria in Aluminium–Ruthenium–Silicon System near 1200 Kelvin A narrow-gap semiconductor with a complex crystal structure was recently discovered in the Al–Ru–Si system. To determine the homogeneity range of the semiconductor phase and further discover new phases, phase equilibria in the Al–Ru–Si system near 1200 K were investigated through prolonged-annealing experiments. Eleven new ternary phases including two incommensurate composite-crystalline and an icosahedral quasicrystalline phases were identified using powder and single-crystal X-ray diffraction, and their compositions at two-phase and three-phase equilibria were evaluated by means of electron-probe X-ray microanalysis. On the basis of the data obtained in this study and those adopted from the literature, a tentative isothermal section of the Al–Ru–Si equilibrium phase diagram near 1200 K was drawn. Materials science ; Phase diagram ; Silicon ; Annealing (glass) ; Ternary operation ; Homogeneity (statistics) ; Isothermal process ; Aluminium ; Semiconductor ; Quasicrystal ; Crystallography ; Diffraction ; Phase (matter) ; Ruthenium ; Crystal structure ; Analytical Chemistry (journal) ; Thermodynamics ; Metallurgy ; Optics ; Chemistry ; Optoelectronics Quasicrystal Structures and Properties ; X-ray Diffraction in Crystallography ; Intermetallics and Advanced Alloy Properties
Authors: Yijun Zou | Hui Jin | Rongrong Zhu | Ting Zhang
Source: Preprints.org (preprint, 2023-11-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Metasurface Holography with Multiplexing and Reconfigurability Metasurface holography offers significant advantages, including a broad field of view, minimal noise, and high imaging quality, making it valuable across various optical domains such as 3D displays, VR, and color displays. However, the conventional pure-structured metasurface holographic devices face a limitation: once fabricated, their functionality remains fixed, restricting practical applications. In recent developments, the landscape of metasurface holography has witnessed a notable shift from passive to active elements, spurred by the introduction of multiplexed and reconfigurable metasurfaces. This paper provides a comprehensive review of the latest advancements in multiplexing and reconfigurable metasurface holography, delving into fundamental characteristics, design strategies, and diverse applications. In conclusion, we offer a brief summary of this rapidly evolving research area, suggest potential future directions, and explore applications. Finally, we briefly summarize this rapidly growing area of research, propose future directions and potential applications. Reconfigurability ; Holography ; Multiplexing ; Computer science ; Face (sociological concept) ; Field (mathematics) ; Electronic engineering ; Telecommunications ; Engineering ; Optics ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: N. Yu. Kruchinin
Source: Nanosystems Physics Chemistry Mathematics (article, 2023-12-30)
Field: Chemistry — Physical and Theoretical Chemistry

Molecular dynamics simulation of the rearrangement of polyampholyte conformations on the surface of a charged oblate metal nanospheroid in a microwave electric field Using molecular dynamics, the rearrangement of the conformational structure of polyampholytes on the surface of a gold oblate nanospheroid in an alternating electric field was studied depending on the value of its total charge. On the surface of the nanospheroid, at its high total charge and at small amplitude of the alternating electric field strength vector, polyampholyte loops stretched over the entire surface of the nanospheroid. With an increase in the amplitude of the electric field in the equatorial region of the nanospheroid, an annular polyampholytic fringe was formed, ordered by the types of links depending on the distance to the polarization axis of the nanoparticle. In the case of high simulation temperature, the shape of the annular fringe changed twice over a period: in one case, ordering according to the types of links along the polarization axis of the nanospheroid, and in the other case, perpendicular to it. Oblate spheroid ; Microwave ; Molecular dynamics ; Electric field ; Chemical physics ; Field (mathematics) ; Metal ; Dynamics (music) ; Surface (topology) ; Physics ; Molecular physics ; Classical mechanics ; Chemistry ; Computational chemistry ; Geometry ; Quantum mechanics ; Acoustics Electrostatics and Colloid Interactions ; Electrohydrodynamics and Fluid Dynamics ; Minerals Flotation and Separation Techniques
Authors: Sina Malakpour Estalaki | Tengfei Luo | Khachatur V. Manukyan
Source: Journal of Applied Physics (article, 2023-06-01)
Field: Materials Science — Materials Chemistry

Bayesian optimization of metastable nickel formation during the spontaneous crystallization under extreme conditions Spontaneous crystallization of metals under extreme conditions is a unique phenomenon occurring under far-from-equilibrium conditions that could enable the development of revolutionary and disruptive metastable metals with unusual properties. In this work, the formation of the hexagonal close-packed nickel (hcp-Ni) metastable phase during spontaneous crystallization is studied using non-equilibrium molecular dynamics (MD) simulations, with the goal of maximizing the fraction of this metastable phase in the final state. We employ Bayesian optimization (BO) with the Gaussian processes (GPs) regression as the surrogate model to maximize the hcp-Ni phase fraction, where temperature and pressure are control variables. MD simulations provide data for training the GP model, which is then used with BO to predict the next simulation condition. Such BO-guided active learning leads to a maximum hcp-Ni fraction of 43.38% in the final crystallized phase within 40 iterations when a face-centered cubic crystallite serves as the seed for crystallization from the amorphous phase. When an hcp seed is used, the maximum hcp-Ni fraction in the final crystal increases to 58.25% with 13 iterations. This study shows the promise of using BO to identify the process conditions that can maximize the rare phases. This method can also be generally applicable to process optimization to achieve target material properties. Crystallization ; Metastability ; Materials science ; Phase (matter) ; Crystallite ; Thermodynamics ; Amorphous metal ; Fraction (chemistry) ; Amorphous solid ; Bayesian optimization ; Crystallography ; Chemistry ; Physics ; Mathematics ; Metallurgy ; Mathematical optimization ; Alloy ; Chromatography Machine Learning in Materials Science ; Injection Molding Process and Properties ; Advanced Memory and Neural Computing