Gaussian 16 是 Gaussian 系列電子結構程序的最新版本，被全世界的化學家、化學工程師、生物化學家、物理學家和其他科學家使用。Gaussian 16 提供了一系列先進的建模功能。您可以使用它來研究您感興趣的現實世界化學問題，即使是在普通的計算機硬件上，也可以解決它們的復雜性。
● Gaussian 16 可生成準確、可靠且完整的模型，無需偷工減料。
● 多種方法使 Gaussian 16 適用于各種化學條件、問題規模和化合物。
● Gaussian 16 在單 CPU、多處理器和多核、集群/網絡和 GPU 計算環境中提供最先進的性能。
● 設置計算簡單明了，甚至復雜的技術也是完全自動化的。靈活、易于使用的選項使您可以在需要時完全控制計算細節。
● 計算結果通過GaussView 6以自然直觀的圖形形式呈現。
Gaussian 16 從量子力學的基本定律出發，預測了各種化學環境中化合物和反應的能量、分子結構、振動頻率和分子性質。Gaussian 16 模型可應用于穩定物質和難以或不可能通過實驗觀察的化合物，無論是由于其性質（例如毒性、可燃性、放射性）還是其固有的短暫性質（例如短命中間體和過渡結構）。
使用 Gaussian 16，您可以徹底研究您感興趣的化學問題。例如，您不僅可以快速可靠地最小化分子結構，還可以預測過渡態的結構，并驗證預測的駐點實際上是最小值或過渡結構（視情況而定）。您可以按照固有反應坐標 (IRC) 繼續計算反應路徑，并確定哪些反應物和產物通過給定的過渡結構連接。一旦您全面了解了勢能面，就可以準確預測反應能量和勢壘。您還可以預測各種化學性質。
● Molecular mechanicsEGF: Amber, UFF, Dreiding
● Semi-empirical methodsEGF?: AM1, PM6, PM7, DFTB, among others
● Hartree-FockEGF
● Density functional (DFT) methodsEGF, with support for a plethora of published functionals; long-range and empirical dispersion corrections are available where defined
● Complete active space self-consistent field (CASSCF)EGF, including RAS support and conical intersection optimizations
● M?ller-Plesset perturbation theory: MP2EGF, MP3EG, MP4(SDQ)EG, MP4(SDTQ)E, MP5E
● Coupled cluster: CCDEG, CCSDEG, CCSD(T)E
● Brueckner doubles: BDEG, BD(T)E
● Outer Valence Green’s Function (OVGF): ionization potentials and electron affinities
● High accuracy energy models: G1-G4, CBS series and W1 series, all with variants
● Excited state methods: TD-DFTEGF, EOM-CCSDEG?and SAC-CIEG
EEnergies;?GAnalytic gradients;?FAnalytic frequencies;?F?Reimplemented with analytic frequencies.
A wide range of Gaussian results can be examined with GaussView’s visualization capabilities:
● Molecule annotations and/or property-specific coloring: e.g., atomic charges, bond orders, NMR chemical shifts
● Plots, including NMR, vibrational and vibronic spectra
● Surfaces or contours: e.g., molecular orbitals, electron density, spin density. Properties such as the electrostatic potential can be visualized as a colorized density surface.
● Animations: e.g., normal modes, IRC paths, geometry optimizations
This graph plots the bond strength in second and third row hydride compounds (experiment: [CRC00]), which generally increases across the periodic table, with the strongest bond occurring in the element just before the noble gas. The plot has a similar overall shape for both rows, but the values for the third row are higher, due to the additional shielding from the nucleus by the filled second shell. The images show the electrostatic potential for each compound mapped onto an isodensity surface. The H2?surface illustrates the covalent nature of this bond; the bonds in the other hydride compounds are ionic. The negative electrostatic potential (red) is localized on the hydrogen atom at the beginning of each row, and it moves to the substituent as the atomic number increases within a row. Thus, hydride bond strengths increase across a period (row) and decrease as you go down a group (column), due to changes in electronegativity.
C60?was detected in IR observations of the Iris nebula (NGC 7023) in 2004 [Werner04,?Sellgren10]. The inset graph shows the peak locations identified from the data (solid bars) superimposed on the spectrum predicted by the APFD/6-311+G(2d,p) model chemistry. The strongest peaks (purple) differ from the laboratory IR spectrum by 0.03-0.06 μm.
Organophosphorous compounds are commonly used as pesticides (among many other applications). These compounds adversely affect human health, due to both their inherent toxicity and from the harmful products created during combustion (e.g., as a result of burning previously-treated plant material). The decomposition of these compounds is difficult to study experimentally; thermochemical data for them is scarce. However, high accuracy thermochemistry predictions can bridge this gap and allow the thermal stability of the relevant compounds and combustion products to be studied. For example, this graph plots the heat capacity as a function of temperature for two such compounds: the pesticide glyphosate and the more benign flame retardant compound dimethyl methylphosphonate (DMMP). It also reports their heats of formation (kcal/mol), as predicted by the CBS-QB3 calculations of Khalfa and coworkers [Khalfa15]. Their paper presents computed results for a large number of trivalent and pentavalent phosphorus compounds, data which enables them to propose 83 original groups for use in the semi-empirical group contribution method of Benson, and thereby allows them to evaluate the thermochemical properties of some common pesticides, herbicides and related compounds.
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