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For the publication of research results, the chemical sciences community has had a long history of requiring authors to provide sufficient data so that their research results and procedures can be (1) understood, (2) critically evaluated, and (3) replicated by other competent scientists. The emergence of computational chemistry as a distinct area of research presents new challenges in defining criteria to meet these obligations. While much of the long-standing paradigm for experimental chemistry can be directly transferred to computational chemistry, some differences are apparent. A computational study does not give a product for which one can measure physical properties, nor are percent yields and recoveries available to demonstrate experimental success. Nonetheless, it is imperative that computational results be able to withstand the same scientific scrutiny as experimental ones. Like all fields of scientific endeavor, computational chemistry is also a dynamic science. The continuous and dramatic improvements in computational algorithms and increases in computing power over the last decade have made possible the study of chemical problems for which solutions by computational means previously were unattainable. Moreover, advances in computer technology have also changed the way these computational studies are carried out. For any new study, the traditional search for the nearest energy minimum may no longer be adequate, fewer assumptions and approximations may be acceptable, and even the nature of the data to be stored and reported may have evolved. For example, many computer algorithms have become sufficiently fast and convenient that it is more efficient to repeat some part of the overall calculation than to save and record the corresponding data that it generates. This document has been developed to provide guidance to chemists who employ computations of molecular structure, properties, reactivity, and dynamics as either a part or as the main thrust of a research report. It is derived in part from earlier work carried out by the Provisional Section Committee on Medicinal Chemistry of IUPAC (Gund, P.; Barry, D. C.; Blaney, J. M.; Cohen, C. N. J. Med. Chem., 1988, 31 , 2230–2234). ©1998 IUPAC 相似文献
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Summary An account is given of experience gained in implementing computational chemistry application software, including quantum chemistry and macromolecular refinement codes, on distributed memory parallel processors. In quantum chemistry we consider the coarse-grained implementation of Gaussian integral and derivative integral evaluation, the direct-SCF computation of an uncorrelated wavefunction, the 4-index transformation of two-electron integrals and the direct-CI calculation of correlated wavefunctions. In the refinement of macromolecular conformations, we describe domain decomposition techniques used in implementing general purpose molecular mechanics, molecular dynamics and free energy perturbation calculations. Attention is focused on performance figures obtained on the Intel iPSC/2 and iPSC/860 hypercubes, which are compared with those obtained on a Cray Y-MP/464 and Convex C-220 minisupercomputer. From this data we deduce the cost effectiveness of parallel processors in the field of computational chemistry. 相似文献
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The combinatorial invariant and covariant are introduced as practical tools for analysis of conical intersections in molecules. The combinatorial invariant is a quantity depending on adiabatic electronic states taken at discrete nuclear configuration points. It is invariant to the phase choice (gauge) of these states. In the limit that the points trace a loop in nuclear configuration space, the value of the invariant approaches the corresponding Berry phase factor. The Berry phase indicates the presence of an odd or even number of conical intersections on surfaces bounded by these loops. Based on the combinatorial invariant, we develop a computationally simple and efficient method for locating conical intersections. The method is robust due to its use of gauge invariant nature. It does not rely on the landscape of intersecting potential energy surfaces nor does it require the computation of nonadiabatic couplings. We generalize the concept to open paths and combinatorial covariants for higher dimensions obtaining a technique for the construction of the gauge-covariant adiabatic-diabatic transformation matrix. This too does not make use of nonadiabatic couplings. The importance of using gauge-covariant expressions is underlined throughout. These techniques can be readily implemented by standard quantum chemistry codes. 相似文献
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Klaus Roth Prof. 《Chemie in Unserer Zeit》2007,41(5):400-409
Bread is regarded as an ultimate “bioproduct without any chemistry.” This is simply not true because chemistry is the basis for the entire bread-manufacturing process from the grain right up to the freshly baked loaf. Its chemical reactions are very complex and we only have a rough idea of what's really going on when kneading the dough and baking the bread. Therefore, attempts of chemists with laboratory but not cuisine experience to produce bread according to scientific principles may lead to more or less edible and digestible products but they cannot compete with the masterpieces of a trained and experienced baker. But that's how it is. Chemistry is necessary for a culinary wonder but sometimes though it is better to let craftspeople with professional experience create the chemical masterpieces and then lean back and simply enjoy things! 相似文献
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Henry'F. Schaefer 《中国化学会会志》1996,43(2):109-115
Computational quantum chemistry has advanced over the past two decades to the point of recognition as a valuable co-laborer with experiment. Several examples demonstrate this point. For each of the next 40 years, we predict that an additional 1% of chemical research will shift from experiment to computation. Thus by the year 2036 we foresee a picture of chemical research in which 50% of the effort is computational in nature. 相似文献
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Chemometrics is the application of statistical and mathematical methods to chemical problems to permit maximal collection and extraction of useful information. The development of advanced chemical instruments and processes has led to a need for advanced methods to design experiments, calibrate instruments, and analyze the resulting data. For many years, there was the prevailing view that if one needed fancy data analyses, then the experiment was not planned correctly, but now it is recognized that most systems are multivariate in nature and univariate approaches are unlikely to result in optimum solutions. At the same time, instruments have evolved in complexity, computational capability has similarly advanced so that it has been possible to develop and employ increasing complex and computationally intensive methods. In this paper, the development of chemometrics as a subfield of chemistry and particularly analytical chemistry will be presented with a view of the current state-of-the-art and the prospects for the future will be presented. 相似文献
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可见光催化作为当前国际学术研究前沿热点,吸引了化学工作者的广泛关注,而在本科生有机化学教学实验中鲜有涉及。本实验将通过模块设计,将有机光催化剂4CzIPN的制备与表征、光电性能研究及光其催化反应性能研究融入到本科实验教学之中,是对现有碎片化实验课的升级尝试与创新,属于典型的科教融合的教学案例,实验过程中涉及多种实验技能以及仪器分析手段,对于学生系统性熟悉科研流程、理解化学反应过程、提升综合科研素养以及培养创新实验探究能力具有重要意义。 相似文献
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A technique for computation of the neutralization curves of acid-base solutions, based on an optimization search method, has been developed. The criterion function is the absolute value of the calculated difference between the numbers of positive and negative charges present in the solutions. This technique is generally applicable for solution chemistry, but because of its speed of resolution and its accuracy, it is particularly useful in the control of a real-time process by a computer. 相似文献
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Andrew R. Bressette 《The Chemical Educator》2000,5(3):133-135
In recent years there has been increasing movement toward laboratory exercises that are inquiry-based, requiring students to assume more active roles in the learning process. A laboratory experiment was developed in this light, framed around a simple question, “Which freezes faster, hot water or cold water?” The experiment was used at the beginning of the general chemistry year-long course sequence and served as an introduction to the scientific process. Students were each asked to develop a hypothesis and then design a simple experiment to determine which freezes faster, hot water or cold water, using small cold baths to freeze the water. A strength of this experiment is that students not only design and perform the experiments, but at the end they evaluate each other’s methods. 相似文献
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Tunneling in experiments (TUNNEX) is a free open-source program with an easy-to-use graphical user interface to simplify the process of Wentzel-Kramers-Brillouin (WKB) computations. TUNNEX aims at experimental chemists with basic knowledge of computational chemistry, and it offers the computation of tunneling half-lives, visualization of data, and exporting of graphs. It also provides a helper tool for executing the zero-point vibrational energy correction along the path. The program also enables computing high-level single points along the intrinsic reaction path. TUNNEX is available at https://github.com/prs-group/TUNNEX . As the WKB approximation usually overestimates tunneling half-lives, it can be used to screen tunneling processes before proceeding with elaborate kinetic experiments or higher-level tunneling computations such as instanton theory and small curvature tunneling approaches. © 2018 Wiley Periodicals, Inc. 相似文献
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Juan Andrés Paul W. Ayers Roberto A. Boto Ramon Carbó-Dorca Henry Chermette Jerzy Cioslowski Julia Contreras-García David L. Cooper Gernot Frenking Carlo Gatti Farnaz Heidar-Zadeh Laurent Joubert Ángel Martín Pendás Eduard Matito István Mayer Alston J. Misquitta Yirong Mo Julien Pilmé Paul L. A. Popelier Martin Rahm Eloy Ramos-Cordoba Pedro Salvador W. H. Eugen Schwarz Shant Shahbazian Bernard Silvi Miquel Solà Krzysztof Szalewicz Vincent Tognetti Frank Weinhold Émilie-Laure Zins 《Journal of computational chemistry》2019,40(26):2248-2283
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Scientific software engineering is a distinct discipline from both computational chemistry project support and research informatics. A scientific software engineer not only has a deep understanding of the science of drug discovery but also the desire, skills and time to apply good software engineering practices. A good team of scientific software engineers can create a software foundation that is maintainable, validated and robust. If done correctly, this foundation enable the organization to investigate new and novel computational ideas with a very high level of efficiency. 相似文献
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