Ab initio calculations of the Ar-ethane intermolecular potential energy surface using bond function basis sets.

J Comput Chem

Department of Chemistry, School of Chemistry, Chemical Engineering and Materials Science, Soochow University, Suzhou, Jiangsu 215123, People's Republic of China.

Published: March 2013


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

The intermolecular potential energy surface (PES) of argon with ethane has been studied by ab initio calculations at the levels of second-order Møller-Plesset perturbation (MP2) theory and coupled-cluster theory with single, double, and noniterative triple configurations (CCSD(T)) using a series of augmented correlation-consistent basis sets. Two sets of bond functions, bf1 (3s3p2d) and bf2 (6s6p4d2f), have been added to the basis sets to show a dramatic and systematic improvement in the convergence of the entire PES. The PES of Ar-ethane is characterized by a global minimum at a near T-shaped configuration with a well depth of 0.611 kcal mol(-1), a second minimum at a collinear configuration with a well depth of 0.456 kcal mol(-1), and a saddle point connecting the two minima. It is shown that an augmented correlation-consistent basis set with a set of bond functions, either bf1 or bf2, can effectively produce results equivalent to the next larger augmented correlation-consistent basis set, that is, aug-cc-pVDZ-bf1 ≈ aug-cc-pVTZ, aug-cc-pVTZ-bf1 ≈ aug-cc-pVQZ. Very importantly, the use of bond functions improves the PES globally, resulting accurate potential anisotropy. Finally, MP2 method is inadequate for accurate calculations, because it gives a potentially overestimated well depth and, more seriously, a poor potential anisotropy.

Download full-text PDF

Source
http://dx.doi.org/10.1002/jcc.23179DOI Listing

Publication Analysis

Top Keywords

basis sets
12
augmented correlation-consistent
12
correlation-consistent basis
12
bond functions
12
well depth
12
initio calculations
8
intermolecular potential
8
potential energy
8
energy surface
8
functions bf1
8

Similar Publications

Objectives: Lymph node metastasis (LNM) is an important factor affecting the stage and prognosis of patients with lung adenocarcinoma. The purpose of this study is to explore the predictive value of the stacking ensemble learning model based on F-FDG PET/CT radiomic features and clinical risk factors for LNM in lung adenocarcinoma, and elucidate the biological basis of predictive features through pathological analysis.

Methods: Ninety patients diagnosed with lung adenocarcinoma who underwent PET/CT were retrospectively analyzed and randomly divided into the training and testing sets in a 7:3 ratio.

View Article and Find Full Text PDF

We introduce an extended formulation of the non-Markovian stochastic Schrödinger equation with complex frequency modes (extended cNMSSE), designed for simulating open quantum system dynamics under arbitrary spectral densities. This extension employs non-exponential basis sets to expand the bath correlation functions, overcoming the reliance of the original cNMSSE on exponential decompositions of the spectral density. Consequently, the extended cNMSSE is applicable to environments beyond those characterized by Debye-type spectral densities.

View Article and Find Full Text PDF

Temporal basis function models for closed-loop neural stimulation.

J Neural Eng

September 2025

Department of Computer Science and Engineering College of Engineering, University of Washington, Box 352350, Seattle, WA 98195-2350, USA, Seattle, Washington, 98105, UNITED STATES.

Unlabelled: Closed-loop neural stimulation provides novel therapies for neurological diseases such as Parkinson's disease (PD), but it is not yet clear whether artificial intelligence (AI) techniques can tailor closed-loop stimulation to individual patients or identify new therapies. Further advancements are required to address a number of difficulties with translating AI to this domain, including sample efficiency, training time, and minimizing loop latency such that stimulation may be shaped in response to changing brain activity.

Approach: we propose temporal basis function models (TBFMs) to address these difficulties, and explore this approach in the context of excitatory optogenetic stimulation.

View Article and Find Full Text PDF

When calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a slowly converging quadrature error when approximating an integral in the reciprocal space by a finite sum. The singularity subtraction (SS) method offers a systematic approach for reducing this quadrature error and thus the FSE. In this work, we first investigate the performance of the SS method in the simplest setting, aiming at reducing the FSE in exact exchange calculations by subtracting the Coulomb contribution with a single, adjustable Gaussian auxiliary function.

View Article and Find Full Text PDF

CELLM: Bridging Natural Language Processing and Synthetic Genetic Circuit Design with AI.

ACS Synth Biol

September 2025

Facultad de Ingeniería y Ciencias, Universidad Diego Portales, Av. Ejército Libertador 441, 8370191 Santiago, RM, Chile.

The complexity of the genetic circuit design limits accessibility and efficiency in synthetic biology. This study presents an integrated system that combines Cello software with large language models (DeepSeek-R1, Phi-4) and the LangChain framework in Python, which allows the creation, analysis, and optimization of genetic circuits using natural language instructions. automates the translation of textual descriptions into functional designs using Cello v2.

View Article and Find Full Text PDF