A new theoretical approach to the encapsulation of small molecules in zeolites

We present a new theoretical method to study the encapsulation of small molecules such as H₂, O₂, N₂, Ar and CH₄ in the Cs₃Na₉-A zeolite. To study the properties of encapsulated molecules, we used the Fermi-Dirac like statistics. The density of states, the distribution function, average binding energy and the average activation energy of encapsulated molecules are calculated. As the number of encapsulated molecules in zeolite cavities increases, the higher energy states in the cavities are gradually filled and, consequently, the activation energy for decapsulation is lowered. We also calculated the fraction of molecules with higher energy than their activation energy, revealing that the activation energy for decapsulation depends not only on the temperature but also on the number of the encapsulated molecules.     

Electrostatic potential of several small molecules from density functional theory

A number of density functional theory (DFT) methods were used to calculate the electrostatic potential for the series of molecules N2, F2, NH3, H2O, CHF3, CHCl3, C6H6, TiF4, CO(NH2)2 and C4H5N3O compared with QCISD (quadratic configuration interaction method including single and double substitutions) results. Comparisons were made between the DFT computed results and the QCISD ab initio ones and MP2 ab initio ones, compared with the root-mean-square deviation and electrostatic potential difference contours figures. It was found that the hybrid DFT method B3LYP, yields electrostatic potential in good agreement with the QCISD results. It is suggest this is a useful approach, especially for large molecules that are difficult to study by ab initio methods.     

几个小分子静电势的密度泛函理论计算

运用多种密度泛函理论(DFT)方法和从头算(ab initio)方法,研究了具有代表性的一系列分子的静电势,选择QCISD计算出的分子静电势为标准静电势,通过比较多种DFT法和QCISD从头算,以及它们之间的均方根偏差和静电势差值曲线图,结果表明B3LYP-DFT法与QCISD-ab initio法计算结果较吻合,暗示了B3LYP-DFT法在得到分子静电势时是一个有用的工具,尤其对于从头计算难以进行研究的大分子体系.     

Complex pole approach in thermodynamic description of fluid mixtures with small number of molecules

The subject matter of classical thermodynamics is the asymptotic behavior of equilibrium systems in thermodynamic limit, for small molecular systems, when transition to thermodynamic limit is impossible, the extension of thermodynamics is required. This work studies novel approach for the evaluation of partition functions of small systems by complex pole analysis. Several cases for molecular systems in small cavities are studied numerically. In particular size-dependent additional pressure for small systems is evaluated analytically and numerically. Similar approach was developed earlier in nuclear physics for finite systems of nucleons. The obtained results correspond to published experimental data and molecular dynamics simulations.     

Machine learning potential aided structure search for low-lying candidates of Au clusters

A machine learning (ML) potential for Au clusters is developed through training on a dataset including several different sized clusters. This ML potential accurately covers the whole configuration space of Au clusters in a broad size range, thus expressing a good performance in search of their global minimum energy structures. Based on our potential, the low-lying structures of 17 different sized Au clusters are identified, which shows that small sized Au clusters tend to form planar structures while large ones are more likely to be stereo, revealing the critical size for the two-dimensional (2D) to three-dimensional (3D) structural transition. Our calculations demonstrate that ML is indeed powerful in describing the interaction of Au atoms and provides a new paradigm on accelerating the search of structures.     

Prediction of antischistosomal small molecules using machine learning in the era of big data

Molecular Diversity - Schistosomiasis is a neglected tropical disease caused by helminths of the Schistosoma genus. Despite its high morbidity and socio-economic burden, therapeutics are just a...     

Machine learning approach for the prediction and optimization of thermal transport properties

Traditional simulation methods have made prominent progress in aiding experiments for understanding thermal transport properties of materials, and in predicting thermal conductivity of novel materials. However, huge challenges are also encountered when exploring complex material systems, such as formidable computational costs. As a rising computational method, machine learning has a lot to offer in this regard, not only in speeding up the searching and optimization process, but also in providing novel perspectives. In this work, we review the state-of-the-art studies on material’s thermal properties based on machine learning technique. First, the basic principles of machine learning method are introduced. We then review applications of machine learning technique in the prediction and optimization of material’s thermal properties, including thermal conductivity and interfacial thermal resistance. Finally, an outlook is provided for the future studies.     

Subfemtomole detection of small molecules with microsphere sensors

We investigated the feasibility of using a silica microsphere sensor for detection of small molecules. Using the silica molecules (60 Da) at the sphere's surface as a model system, we measured the spectral shifts in the whispering-gallery modes (WGMs) when the sphere size was decreased by a hydrofluoric acid (HF) solution. The results demonstrate that our sensor is capable of detecting a 4 pm (or 0.01 layer of silica) decrease in sphere radius, corresponding to a change of 0.4 fmol silica molecule. These results suggest that small molecules can be detected in trace quantities at the surface of an optical microsphere sensor.     

Algebraic approach to thermodynamic properties of diatomic molecules

A simple model extending Lie algebraic techniques is applied to the analysis of thermodynamic vibrational properties of diatomic molecules. Local anharmonic effects are described by means of a Morse-like potential and the corresponding anharmonic bosons are associated with the SU(2) algebra. The total number of anharmonic bosons, fixed by the potential shape, is determined for a large number of diatomic molecules. A vibrational high-temperature partition function and the related thermodynamic functions are derived and studied in terms of the parameters of the model. The idea of a critical temperature is introduced in relation to the specific heat. A physical interpretation in terms of a quantum deformation associated with the model is given.     

A two-density approach to the general many-body problem and a proof of principle for small atoms and molecules

An extended electron model fully recovers many of the experimental results of quantum mechanics while it avoids many of the pitfalls and remains generally free of paradoxes. The formulation of the manybody electronic problem here resembles the Kohn–Sham formulation of standard density functional theory. However, rather than referring electronic properties to a large set of single electron orbitals, the extended electron model uses only mass density and field components, leading to a substantial increase in computational efficiency. To date, the Hohenberg–Kohn theorems have not been proved for a model of this type, nor has a universal energy functional been presented. In this paper, we address these problems and show that the Hohenberg–Kohn theorems do also hold for a density model of this type. We then present a proof-of-concept practical implementation of this method and show that it reproduces the accuracy of more widely used methods on a test-set of small atomic systems, thus paving the way for the development of fast, efficient and accurate codes on this basis.     

The calculation of potential energy curves of diatomic molecules: Application to halogen molecules

Methods for computing the vibrational turning points of diatomic molecules are summarized. An extension of the technique described by Vanderslice et al. is used to derive simple analytical expressions for calculation of the turning points from spectroscopic data. For most molecular states, the method gives results in agreement with those from sophisticated numerical procedures. Recently available spectroscopic data have been used to determine the potential energy curves for the¹∑⁺_g and ³Π(0⁺_u) states of Cl₂ and Br₂.     

Statistical mechanics approach to a reinforcement learning model with memory

We introduce a two-player model of reinforcement learning with memory. Past actions of an iterated game are stored in a memory and used to determine player’s next action. To examine the behaviour of the model some approximate methods are used and confronted against numerical simulations and exact master equation. When the length of memory of players increases to infinity the model undergoes an absorbing-state phase transition. Performance of examined strategies is checked in the prisoner’ dilemma game. It turns out that it is advantageous to have a large memory in symmetric games, but it is better to have a short memory in asymmetric ones.     

双原子分子激发态势能的自旋相关局域Hartree-Fock密度泛函理论方法

基于自旋相关局域Hartree-Fock (SLHF)势函数,本文提出了一种计算双原子分子激发态势能的密度泛函理论(DFT)方法,并将该方法应用于和的激发态势能曲线的计算。在只考虑交换能的情况下,本文的DFT计算结果与文献中精确方法和Hartree-Fock (HF)方法的结果符合的非常好,说明采用SLHF势函数作为交换势的DFT方法是一个很好的计算激发态势能的方法。本文还计算和探讨了电子的关联势函数和关联能,发现传统的近似方法在较大核间距的情况下大大低估了电子的关联能.     

Optimal approach to rotational state reconstruction of linear molecules

We present a simulation for the reconstruction of the rotational quantum state of linear molecules to retrieve the density matrix. An optimal approach in the sense of minimal error limit is proposed, in which a variable set of angular frequency is properly chosen and the least square inversion is then applied. This approach of reconstruction from time-dependent molecular-axis angular distribution is proved adaptable for various object states, which has a good numerical stability independent of the selected rotational space.     

Morphometric approach to the solvation free energy of complex molecules

We show that the solvation free energy of a complex molecule such as a protein can be calculated using only four geometrical measures of the molecular structure and corresponding thermodynamical coefficients. We compare results from this morphometric approach to those obtained by an elaborate statistical-mechanical theory in liquid state physics for a large variety of different structures of protein G and find excellent agreement. Since the computational time is drastically reduced, the new approach provides a practical and efficient way for calculating the solvation free energy which can be employed when this quantity has to be calculated for a large number of structures, as in a simulation study of protein folding.     

代数方法计算正四面体分子伸缩振动能谱

用推广的U(2)代数模型,对正四面体分子的伸缩振动能谱进行了理 论研 究,该模型成功地应用到SnD4的最新观测到的高分辨能谱数据,所得计算值与实验值的标 准偏差是0.124 cm-1。     

A new approach to the treatment of rotational spectra of molecules with small moments of inertia applied to the PH3 molecule in the ground state

A new approach to the treatment of rotational spectra of molecules with small moments of inertia is considered based on a representation of the effective rotational Hamiltonian operator in the form of a Pade operator. An extended set of high-precision data on transition frequencies in the rotational spectrum of the PH₃ molecule in the ground vibrational state is analyzed. The fitting of these data within experimental error demonstrates the advantages of the new approach. Frequencies of the Q-branch forbidden transitions |K| = 3 ← 6, first measured in this work, represent an essential part of the data under consideration.     

A local approach to the computation of correlation energies of molecules

A new variational approach is introduced for the calculation of correlation energies of molecules. It is based on the local character of the correlated electron motion. Based on the approach we calculate correlation energies for simple systems. These include various Hubbard models as well as a model of the H₆-ring for which exact results are available. Our finding is that the proposed approach appears to be simpler and more economical for numerical work than conventional CI-methods. More than 90% of the correlation energy is obtained in all cases considered.     

Multifrequency species classification of acoustic-trawl survey data using semi-supervised learning with class discovery

Acoustic surveys often use multifrequency backscatter to estimate fish and plankton abundance. Direct samples are used to validate species classification of acoustic backscatter, but samples may be sparse or unavailable. A generalized Gaussian mixture model was developed to classify multifrequency acoustic backscatter when not all species classes are known. The classification, based on semi-supervised learning with class discovery, was applied to data collected in the eastern Bering Sea during summers 2004, 2007, and 2008. Walleye pollock, euphausiids, and two other major classes occurring in the upper water column were identified.     

New approach to surface ionization and drift-tube spectroscopy of organic molecules

A new physical model of ionization of organic molecules from the class of amines on the oxidized surface of transition metals is suggested. According to this model, the process involves the capture of protons or hydroxyl groups forming on the oxide surface upon water molecule adsorption. The adequacy of the model is demonstrated experimentally with test amines, such as Novocaine (procaine), bencaine, Dimedrol (diphenylhydramine), etc. A theory of drift motion of ion beams that includes the space charge effect is proposed. It is shown that the quantity P _i=μj/ε₀ v _g ² (where μ is the ion mobility, j is the ion current density, ɛ₀ is the permittivity, and v _g is the longitudinal velocity of an ionized gas) plays the role of perveance for intense drift ion beams. A new type of drift-tube spectrometer that uses an ion source due to surface ionization is developed.