Free rotation and the electric moment of organic molecules

1934 ◽  
Vol 30 ◽  
pp. 804 ◽  
Author(s):  
C. T. Zahn
Keyword(s):  
Organic Molecules ◽  
Free Rotation ◽  
Electric Moment

High Resolution Replication of Organoclay Surfaces

1982 ◽  
Vol 40 ◽  
pp. 576-577
Author(s):  
W. W. Barker ◽  
W. E. Rigsby ◽  
V. J. Hurst ◽  
W. J. Humphreys
Keyword(s):  
Clay Mineral ◽  
Organic Molecule ◽  
Organic Molecules ◽  
X Ray Diffraction ◽  
Xrd Pattern ◽  
X Ray ◽  
Naturally Occurring ◽  
Silicate Layers ◽  
Mineral Identification

Experimental clay mineral-organic molecule complexes long have been known and some of them have been extensively studied by X-ray diffraction methods. The organic molecules are adsorbed onto the surfaces of the clay minerals, or intercalated between the silicate layers. Natural organo-clays also are widely recognized but generally have not been well characterized. Widely used techniques for clay mineral identification involve treatment of the sample with H2 O2 or other oxidant to destroy any associated organics. This generally simplifies and intensifies the XRD pattern of the clay residue, but helps little with the characterization of the original organoclay. Adequate techniques for the direct observation of synthetic and naturally occurring organoclays are yet to be developed.

Direct phase determination in electron crystallography: small organic molecules

1992 ◽  
Vol 50 (2) ◽  
pp. 1166-1167
Author(s):  
Douglas L. Dorset
Keyword(s):  
Organic Molecules ◽  
Data Sets ◽  
Temperature Structure ◽  
3D Analysis ◽  
Intensity Data ◽  
Electron Crystallography ◽  
Phase Determination ◽  
Measured Intensity ◽  
3D Data

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.

A MOLECULAR DYNAMICS STUDY OF ELECTRONIC SPUTTERING OF LARGE ORGANIC MOLECULES

1989 ◽  
Vol 50 (C2) ◽  
pp. C2-33-C2-35 ◽  
Author(s):  
D. FENYÖ ◽  
B. U.R. SUNDQVIST ◽  
B. KARLSSON ◽  
R. E. JOHNSON
Keyword(s):  
Molecular Dynamics ◽  
Organic Molecules

Imine as a Linchpin Approach for Distal C(sp2)–H Functionalization

2020 ◽  
Author(s):  
Sukdev Bag ◽  
Sadhan Jana ◽  
Sukumar Pradhan ◽  
Suman Bhowmick ◽  
Nupur Goswami ◽  
...  
Keyword(s):  
Organic Molecules ◽  
Bond Activation ◽  
Bond Formation ◽  
Ancillary Ligand ◽  
Significant Challenge ◽  
Site Selectivity ◽  
Directing Group ◽  
Covalently Linked ◽  
Complex Organic ◽  
Post Functionalization

<p>Despite the widespread applications of C–H functionalization, controlling site selectivity remains a significant challenge. Covalently attached directing group (DG) served as an ancillary ligand to ensure proximal <i>ortho</i>-, distal <i>meta</i>- and <i>para</i>-C-H functionalization over the last two decades. These covalently linked DGs necessitate two extra steps for a single C–H functionalization: introduction of DG prior to C–H activation and removal of DG post-functionalization. We introduce here a transient directing group for distal C(<i>sp<sup>2</sup></i>)-H functionalization <i>via</i> reversible imine formation. By overruling facile proximal C-H bond activation by imine-<i>N</i> atom, a suitably designed pyrimidine-based transient directing group (TDG) successfully delivered selective distal C-C bond formation. Application of this transient directing group strategy for streamlining the synthesis of complex organic molecules without any necessary pre-functionalization at the distal position has been explored.</p>

Extending the Applicability of the ANI Deep Learning Molecular Potential to Sulfur and Halogens

2020 ◽  
Author(s):  
Christian Devereux ◽  
Justin Smith ◽  
Kate Davis ◽  
Kipton Barros ◽  
Roman Zubatyuk ◽  
...  
Keyword(s):  
Drug Development ◽  
Autonomous Vehicles ◽  
Potential Energy Surfaces ◽  
Organic Molecules ◽  
Chemical Elements ◽  
Molecular Potential ◽  
Wide Range ◽  
Energy Surfaces ◽  
New Applications ◽  
Physical Phenomena

<p>Machine learning (ML) methods have become powerful, predictive tools in a wide range of applications, such as facial recognition and autonomous vehicles. In the sciences, computational chemists and physicists have been using ML for the prediction of physical phenomena, such as atomistic potential energy surfaces and reaction pathways. Transferable ML potentials, such as ANI-1x, have been developed with the goal of accurately simulating organic molecules containing the chemical elements H, C, N, and O. Here we provide an extension of the ANI-1x model. The new model, dubbed ANI-2x, is trained to three additional chemical elements: S, F, and Cl. Additionally, ANI-2x underwent torsional refinement training to better predict molecular torsion profiles. These new features open a wide range of new applications within organic chemistry and drug development. These seven elements (H, C, N, O, F, Cl, S) make up ~90% of drug like molecules. To show that these additions do not sacrifice accuracy, we have tested this model across a range of organic molecules and applications, including the COMP6 benchmark, dihedral rotations, conformer scoring, and non-bonded interactions. ANI-2x is shown to accurately predict molecular energies compared to DFT with a ~10<sup>6</sup> factor speedup and a negligible slowdown compared to ANI-1x. The resulting model is a valuable tool for drug development that can potentially replace both quantum calculations and classical force fields for myriad applications.</p>

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