Number Of Atoms Research Articles

Screening the organic materials database for superconducting metal-organic frameworks

The increasing financial and environmental cost of many inorganic materials has motivated study into organic and “green” alternatives. However, most organic compounds contain a large number of atoms in the primitive unit cell, posing a significant barrier to high-throughput screening for functional properties. In this work, we attempt to overcome this challenge and identify superconducting candidates among the metal-organic-frameworks in the organic materials database using a recently proposed proxy for the electron-phonon coupling. We then isolate the most promising candidate for in-depth analysis, C9H8Mn2O11, providing evidence for superconductivity below 100mK.

Limitation of single-repumping schemes for laser cooling of Sr atoms

We explore the efficacy of two single-repumping schemes, 5s5pP23−5p2P23 (481nm) and 5s5pP23−5s5dD23 (497nm), for a magneto-optical trap (MOT) of Sr atoms. We reveal that the enhancement in the MOT lifetime is limited to 26.9(2) for any single-repumping scheme. Our investigation indicates that the primary decay path from the 5s5pP11 state to the 5s5pP03 state proceeds via the 5s4dD13 state, rather than through the upper states accessed by the single-repumping lasers. We estimate that the branching ratio for the 5s5pP11→5s4dD13→5s5pP03 decay path is 1:3.9(1.5)×106 and the decay rate for the transition from the 5s5pP11 state to the 5s4dD13 state is 83(32)s−1. This outcome underscores the limitation on atom number in the MOT for long loading times (≳1s) when employing a single-repumping scheme. These findings will contribute to the construction of field-deployable optical lattice clocks. Published by the American Physical Society 2024

Conductivity Prediction Method of Solid Electrolyte Materials Based on Pearson Coefficient Method and Ensemble Learning

In order to screen solid electrolytic materials with high ionic conductivity more quickly and accurately, a conductivity prediction method for solid electrolyte materials based on logistic regression model and random forest regression model is constructed. The method first selects 20 characteristic descriptors related to ionic conductivity from material library according to four dimensions: structural stability, metal stability, electronic conductivity and oxidative decomposition stability. The enumeration method and feature selection method are used to combine different features. Then, the dimension reduction of the feature combinations is carried out by Pearson coefficient method, so as to screen the optimal feature combinations. Finally, according to the optimal feature combination and data subset, the constructed random forest ensemble learning model is utilized to predict the ionic conductivity of other solid-state electrolyte materials in the material library, in order to find the solid-state electrolyte materials that can meet the high conductivity. The results indicate that as the number of features in the combination increases, the prediction performance of the model shows a trend of first increasing and then decreasing. When the feature descriptor in the combination is 7, the maximum AUC (Accuracy) value is reached, and the optimal feature in this case contains 7 optimal feature subsets corresponding to feature descriptors, namely the standard deviation of the average adjacency number of Li atoms, the standard deviation of Li-X ion bonds, the average electronegativity of the straight path, the average width of the straight path, the average atomic volume, the average Li-Li bond, and the filling fraction of the sublattice. On the basis of the optimal feature screening, the average prediction accuracy of the logistic regression model is 87.13%, which has a high accuracy. Using the random forest regression model for prediction, the average absolute error and root mean square error obtained are only 0.237 and 0.134, and compared with classical classification methods such as KNN, SVM and Adaboost, they are smaller, which can better predict the ionic conductivity of solid electrolyte materials. This proves that the constructed method can quickly and accurately produce high ionic conductivity materials in solid electrolyte materials, which is worthy of further research and promotion.

Extraction of molecular information from experimental data on liquids using manifold learning

This study proposes that microscopic information can be extracted from experimental data on liquid substances using a manifold learning technique. Here, 98 liquid substances could be classified based on their functional groups by applying the isomap method, a manifold learning technique, to nine thermal properties of the substances. Moreover, information related to their intermolecular interactions, which could be divided into the contributions of van der Waals and polar interactions, molecular weight, and number of carbon atoms could be extracted by the proposed method. This study could guide future research on the utilization of manifold learning techniques in liquid-substance characterization and development.

Correlative Activation Free Energy (CAFE) Model: Application to Viscous Processes in Inorganic Oxide Glass-Formers

We explore the concept of correlative activation free energy (CAFE) for the analysis and interpretation of viscosity data of a collection of 847 inorganic oxide glass formers that exhibit various degrees of non-Arrhenius behavior. The CAFE model formalism is strictly based on transition state theory and accounts for the variation in the activation barrier for the viscous dissipation due to the structural evolution the system undergoes upon traversing the glass transition regime. Thus, fitting parameters are meaningful in a statistical thermodynamic context. Compared to the VFT and MYEGA equations, fits using the CAFE model are more robust when extrapolating to infinite temperature because the latter encodes non-enthalpic contributions to the rate coefficient more realistically. The CAFE model-based analysis reveals a strong connection between melt fragility and the degree of change in the potential energy landscape with temperature. Accordingly, while the average ground-state potential energy of the glass forming liquid gradually increases with temperature, the energy of the activated state remains relatively invariant. Our analysis also allows one to estimate the number of atoms involved in the viscous relaxation process, which ranges from approximately 10 to 50 atoms for the oxide glass formers studied. We observe that thermally activated dynamic phenomena exhibited by glassy networks, such as the mixed alkali effect, persist into the supercooled liquid state.

Synthesis of 1,2,3‐Triphospholenes, 1,2‐Diphosphetes, and Unsymmetric Phospholes by Rhodium‐catalyzed Cleavage of P−P Bonds and Addition to Alkynes

AbstractThe rhodium‐catalyzed addition reaction of cyclo‐(PPh)5 to alkynes in refluxing THF efficiently provide 1,2,3‐triphospholenes, in which the –PPh–PPh–PPh– group is transferred from cyclo‐(PPh)5 by the cleavage of P−P bonds. In refluxing chlorobenzene, the reactions are accompanied by the formation of 1,2‐diphosphetes. When the triphospholenes containing P−P bonds are reacted with reactive alkynes under rhodium‐catalyzed conditions, unsymmetric phospholes are obtained. The rhodium‐catalyzed reactions can be used to synthesize various phosphorus‐containing heterocycles with different numbers of phosphorus atoms.

In-phase collective unconventional photon blockade and its stability in asymmetrical cavity containing N bosonic atoms

Abstract We present a work of cavity-driven QED system combined an asymmetrical Fabry-Perot cavity and N two-level atoms (TLAs) and show the convenience of simplifying from distinguishable atoms to undistinguishable bosons when atoms are prepared in the same initial state. Such simplification is valid even when the atoms are not prepared in the in-phase condition, since any partial in-phase initial state will evolve into the ground state through a relaxation process. Thus, we get a reduced group of differential equations by introducing the Dicke states, and the under-zero Lyapunov exponents verify its stability. We also work out the collective unconventional photon blockade (UCPB) and get two kinds of giant nonreciprocal UCPBs (NUCPBs) in the weak-driving approximation. Results show that we can employ N non-interacting bosonic atoms to generate a collective UCPB instead of a monoatomic UCPB as UCPB conditions do not vary with the number of atoms. Furthermore, the forward giant NUCPB only occurring for N larger than a certain number, as well as the backward giant NUCPB, are controllable by the cavity asymmetry and by the number of atoms. Our findings suggest a prospective approach to the generation of quantum nonreciprocity by N identical atoms.

Hybrid Boson Sampling

We propose boson sampling from a system of coupled photons and Bose–Einstein condensed atoms placed inside a multi-mode cavity as a simulation process testing the quantum advantage of quantum systems over classical computers. Consider a two-level atomic transition far-detuned from photon frequency. An atom–photon scattering and interatomic collisions provide interactions that create quasiparticles and excite atoms and photons into squeezed entangled states, orthogonal to the atomic condensate and classical field driving the two-level transition, respectively. We find a joint probability distribution of atom and photon numbers within a quasi-equilibrium model via a hafnian of an extended covariance matrix. It shows a sampling statistics that is ♯P-hard for computing, even if only photon numbers are sampled. Merging cavity-QED and quantum-gas technologies into a hybrid boson sampling setup has the potential to overcome the limitations of separate, photon or atom, sampling schemes and reveal quantum advantage.

Simulation of wind-temperature-density measurement in near space by spaceborne Fe resonance fluorescence Doppler lidar

Spaceborne resonance fluorescence Doppler lidar uses metal atoms as tracers to detect atmospheric temperature, wind speed, and metal atom number density from the top of the mesosphere to the bottom of the thermosphere in the global atmosphere. This study proposes a concept of spaceborne Fe resonance fluorescence Doppler lidar (spaceborne Fe lidar). To theoretically analyze the feasibility of this technology, key parameters of the lidar were designed. Starting from the lidar equation, the echo signal intensity of spaceborne Fe lidar and the random error of atmospheric parameters were simulated and analyzed. Satellite orbit height is designed to be 400 km, monopulse energy is 300 mJ, and vertical and horizontal distance resolution is 2 km and 230 km, respectively. The simulation calculation shows that the random error of temperature detection of the spaceborne Fe lidar is 3.32 K, the line of sight wind speed is 1.67 m/s, and the horizontal wind speed is 3.34 m/s at 90 km. At the same time, the atmospheric density and temperature of 30-70 km can be detected at night, and the error is less than 10%. The conclusion of this paper has reference value for developing spaceborne resonance fluorescence Doppler lidar to detect atmospheric parameters in near space.

On the Existence of Extreme Coherent Distributions with No Atoms

The paper is devoted to the study of extremal points of C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {C}}$$\\end{document}, the family of all bivariate coherent distributions on [0,1]2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$[0,1]^2$$\\end{document}. It is well-known that the set C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {C}}$$\\end{document} is convex and weak∗\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox {weak}^*$$\\end{document} compact, and all extreme points of C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\mathcal {C}}$$\\end{document} must be supported on sets of Lebesgue measure zero. Conversely, examples of extreme coherent measures with a finite or countably infinite number of atoms have been successfully constructed in the literature. The main purpose of this article is to bridge the natural gap between those two results: We provide an example of extreme coherent distribution with an uncountable support and with no atoms. Our argument is based on classical tools and ideas from dynamical systems theory. This unexpected connection can be regarded as an independent contribution of the paper.

Aromatase as a novel target of parabens in human and rat placentas: 3D-quantitative structure-activity relationship and docking analysis

Aromatase (CYP19A1), a pivotal enzyme in the biosynthesis of estradiol from testosterone, is predominantly expressed in reproductive tissues including placentas. This study investigated the effects of paraben acid and nine parabens on the activity of human and rat CYP19A1 using microsomes derived from human and rat placentas and on estradiol secretion in human choriocarcinoma BeWo cells. The results showed that propyl, butyl, hexyl, heptyl, and nonyl parabens significantly inhibited human CYP19A1 activity, with IC50 values of 66.37, 61.08, 55.65, 48.26, and 27.24 μM, respectively. In BeWo cells, these parabens notably diminished estradiol secretion at concentrations of 100 μM. Similarly, rat CYP19A1 was inhibited by these parabens, with IC50 values of 98.07, 70.10, 41.30, 27.93, and 6.33 μM for propyl, butyl, hexyl, heptyl, and nonyl parabens, respectively. Kinetic analysis identified these compounds as mixed inhibitors. Bivariate correlation analysis revealed a negative correlation between the partition coefficient value, molecular weight, the number of carbon atoms in the alcohol moiety, as well as heavy atom number and IC50 values. Three-dimensional quantitative structure-activity relationship analysis highlighted the critical role of hydrophobic regions in determining inhibitory potency. Docking studies suggested that parabens interact with the heme-iron binding site of both human and rat CYP19A1. This study elucidates the inhibitory effects of various parabens on CYP19A1 and their binding mechanisms, thereby providing a deeper understanding of their potential impact on estrogen biosynthesis.

Determination of Chain Transfer Constants of Alcohols for High‐Pressure Polyethylene Polymerization

AbstractIn low‐density polyethylene (LDPE) production, low‐molecular‐weight species are used as chain transfer agents (CTAs). They reduce the degree of polymerization, which has an impact on the polymer properties, such as processability. To specifically adjust the product properties, a detailed understanding of the transfer kinetics to CTAs is indispensable. Thus, the transfer activity of various primary, secondary, and tertiary alcohols as well as diols was investigated experimentally between 120 °C and 250 °C at 2000 bar. The results were evaluated using the Mayo and chain length distribution (CLD) method, and the latter was found to give more reliable results. It was observed that the hydroxy group systematically increases transfer activity compared to alkanes. Additionally, a linear increase of transfer activity with the number of hydrogen atoms is found.

Atomically Precise Ternary Cluster: Polyoxometalate Cluster Sandwiched by Gold Clusters Protected by N‐Heterocyclic Carbenes

AbstractCoinage metal (Au, Ag, Cu) cluster and polyoxometalate (POM) cluster represent two types of subnanometer “artificial atoms” with significant potential in catalysis, sensing, and nanomedicine. While composite clusters combining Ag/Cu clusters with POM have achieved considerable success, the assembly of gold clusters with POM is still lagging. Herein, we first designedly synthesized two cluster structural units: an Au3O cluster stabilized by diverse N‐heterocyclic carbene (NHC) ligands and an amine‐terminated POM linker. The subsequent reaction involved amine substitution in the POM linker for the central O atom in the Au3O cluster, resulting in the first ternary composite cluster—a POM cluster sandwiched by two Au clusters protected by NHCs. Single‐crystal X‐ray diffraction and other characteristic methods characterized their atomically precise structures. Furthermore, altering the NHC ligands decreased the number of gold atoms in the sandwich structures, accompanying the different protonated degrees of amine ligand in the terminal end of the POM linker. These composite clusters showed excellent performances in catalytic H2O2 conversion through the synergistic effect between gold clusters and POM clusters. This work opens a new avenue to functional composite metal clusters and would promote their enhanced catalysis applications through intercluster synergistic interactions within composite systems.

AI-Driven Electrolyte Additive Selection to Boost Aqueous Zn-Ion Batteries Stability.

In tackling the stability challenge of aqueous Zn-ion batteries (AZIBs) for large-scale energy storage, the adoption of electrolyte additive emerges as a practical solution. Unlike current trial-and-error methods for selecting electrolyte additives, a data-driven strategy is proposed using theoretically computed surface free energy as a stability descriptor, benchmarked against experimental results. Numerous additives are calculated from existing literature, forming a database for machine learning (ML) training. Importantly, this ML model relies solely on experimental values, effectively addressing the challenge of large solvent molecule models that are difficult to handle with quantum chemistry computation. The interpretable linear regression algorithm identifies the number of heavy atoms in the additive molecule and the liquid surface tension as key factors. Artificial intelligence (AI) clustering categorizes additive molecules, identifying regions with the most significant impact on enhancing battery stability. Experimental verification successfully confirms the exceptional performance of 1,2,3-butanetriol and acetone in the optimal region. This integrated methodology, combining theoretical models, data-driven ML, and experimental validation, provides insights into the rational design of battery electrolyte additives.

Ultra-Narrowband Circularly Polarized Luminescence from Multiple 1,4-Azaborine-Embedded Helical Nanographenes.

In this manuscript we present a strategy to achieve ultranarrowband circularly polarized luminescence (CPL) from multiple 1,4-azaborine-embedded helical nanographenes. The impact of number and position of boron and nitrogen atoms in the rigid core of the molecule on optical properties─including absorption and emission maxima, photoluminescence quantum yield, Stokes shift, excited singlet-triplet energy gap and full width at half-maximum (fwhm) for CPL and fluorescence─was investigated. The molecules reported here exhibits ultranarrowband fluorescence (fwhm 16-17.5 nm in toluene) and CPL (fwhm 18-19 nm in toluene). To the best of our knowledge, this is among the narrowest CPL for any organic molecule reported to date. Quantum chemical calculations, including computed CPL spectra involving vibronic contributions, provide valuable insights for future molecular design aimed at achieving narrowband CPL.

The Influence of Pressure on the Electronic and Elastic Characteristics of GaP Nanocrystals using Density Functional Theory

The electronic structural and mechanical properties of III-V Gallium Phosphide (GaP) nano-crystals zinc-blende stable (ZB) phase under pressure dependence have been studied via the model of the density functional theory (DFT) in combination with the large unit cell (LUC) approach at (8, 16, 54 & 64) atoms. The exchanges and correlations (XC) energy has been defined in all approaches through generalized gradient approximations of the Perdew-Burke-Ernzerhof (GGA-PBE), and determination of GaP characteristics in the case where the pressure has been increased from 0GPa to ±50GPa. Elastic parameters like elastic constants (C11, C12 & C44), Kleinmann parameter (ξ), Zener anisotropic factor (A), shear modulus (G), Young's modulus (E), Poisson’s ratio (v), Bulk modules (B) of GaP-ZB structure have been calculated and showed systematic variation with a pressure increase. Our calculations show that Bulk modules and sound speed increase with an increase in the number of core atoms. In this systematic approach, it has been found that the B/G ratio is 1.58 for this compound and it exhibits a negative Cauchy pressure, classifying GaP as brittle. The results were discovered to be consistent with other theoretical as well as experimental results. The present study directly relates to the latest experimental works on the III-phosphide compounds. The current results provide information and direction for further investigation into the fundamentals and potential applications of gallium phosphate (GaP) nanocrystals. In addition, we attempted to compare the results of the investigation with some similar types of compounds that are already documented in the literature. We believe that our study will have a significant impact on both the field of research and contemporary technology based on semi-conducting materials.

Evidence of short chains in liquid sulfur.

High energy x-ray pair distribution function measurements show the average coordination number of the first shell in liquid sulfur is 1.86 ± 0.04 across the λ-transition, not precisely 2.0 as widely accepted. This indicates that upon melting, liquid sulfur does not comprise solely of S8 rings but also possesses a significant number of short chains. Intensities of the pre-peak and first diffraction peak of the x-ray structure factor and third peak height of the pair distribution function all show deviations at the λ-transition temperature Tλ, associated with the break-up of S8 rings and the start of oligomer polymerization. A significant number of non-bonded or loosely bonded "interstitial atoms," with an average coordination number of 0.20 ± 0.005, are also observed in the so-called "forbidden zone" between the first and second shells upon melting. The number of interstitial atoms is found to decrease to a minimum at the λ-transition, but the majority persist into the high temperature polymerized liquid. The existence of short chains and nearby interstitial atoms represent the two main factors required to initiate the S8-ring to chain transition, as proposed by recent molecular dynamics simulations.

Research on nanocutting mechanism of polycrystalline γ-TiAl alloy at different temperatures

The γ-TiAl alloy is widely used in the aerospace industry due to its remarkable properties. However, its deformation mechanism during nanocutting is significantly influenced by temperature variations. This study utilizes molecular dynamics simulations to investigate the nanocutting processes of polycrystalline γ-TiAl alloy across a range of low and high temperatures. The focus is on how the initial equilibrium temperature affects cutting force, cutting temperature, Von Mises stress, shear strain, atomic phase transformation, and dislocation evolution during the nanocutting of the alloy.The results indicate that at lower temperatures, a decrease in initial equilibrium temperature leads to a gradual increase in the number of atoms in intermediate states, accompanied by diminished heat diffusion. Conversely, in high-temperature cutting scenarios, the initial equilibrium temperature is negatively correlated with the cutting force (Fx); specifically, the average Fx at 300K is 1.72 times that at 1050K. At elevated temperatures, as the initial equilibrium temperature increases, the chip formation mode transitions from fracture to shear, resulting in higher internal Von Mises stress and shear strain within the chips, as well as a wider shear line. Additionally, further increases in the initial equilibrium temperature lead to a broader atomic flow bandwidth in the shear region.At 173K, the counts of BCC and HCP structured atoms reach their minima, comprising 62.5 % and 55 % of their respective maximum values. Moreover, the densities of 1/2<110> (perfect) dislocations and 1/3<111> (Frank) dislocations decrease with rising initial equilibrium temperatures, showing growth rates exceeding 80 % as the temperature increases from 300K to 1050K.

Pressure-Induced Structural Phase Transitions and Photoluminescence Properties of Micro/Nanocrystals HoF3.

HoF3 crystals of varying sizes and morphologies were synthesized by controlling the amount of water. As the water content gradually decreased, the size of the crystals reduced, transforming from microcrystals to approximately 100 nm nanocrystals with unique morphologies. At room temperature, the pressure-induced phase transitions, and photoluminescence (PL) properties of HoF3 micro/nanocrystals are studied using in situ high-pressure PL technique. The PL spectra show that the HoF3 micro/nanocrystals exhibit two structural phase transformations at 5 (6 GPa for NCs) and 12 GPa. Nanoparticles have higher fluorescence intensity, which initially increases and then decreases with changes in pressure. Based on first-principles calculations, HoF3 transforms from an orthorhombic structure to a hexagonal structure during the phase transition, with the coordination number of holmium atoms increasing from 9 to 11. The high-pressure Raman spectra on lattice modes also confirmed the existence of the two phase transitions. This work not only provides precise structural changes but also facilitates the understanding of two typical structures of rare-earth trifluoride (REF3), which may play an important role in the application of the RE family.

An abinitio approach to the Hugoniot.

The Hugoniot is the equation of state of a shock-compressed material and is a key part of high-pressure physics. One way of calculating it is via the Hugoniostat that has significant computational advantages over direct calculation via non-equilibrium molecular dynamics. We introduce a number of improvements to the Hugoniostat, which significantly reduce the run time and the number of atoms required for converged results. Consequently, abinitio Hugoniot calculations are tractable. We illustrate the benefits through simple model potentials and with density functional theory calculations of argon.