Facile Access to AgOCF 3 and Its New Applications as a Reservoir for OCF 2 for the Direct Synthesis of N−CF 3 , Aryl or Alkyl Carbamoyl Fluorides

2020 ◽  
Vol 26 (10) ◽  
pp. 2183-2186 ◽  
Author(s):  
Abdurrahman Turksoy ◽  
Thomas Scattolin ◽  
Samir Bouayad‐Gervais ◽  
Franziska Schoenebeck
Keyword(s):  
Direct Synthesis ◽  
New Applications

scholarly journals High-silica, heulandite-type zeolites prepared by direct synthesis and topotactic condensation

2015 ◽  
Vol 3 (24) ◽  
pp. 12890-12897 ◽  
Author(s):  
Joel E. Schmidt ◽  
Dan Xie ◽  
Mark E. Davis
Keyword(s):  
Thermal Stability ◽  
Direct Synthesis ◽  
High Silica ◽  
New Applications

High-silica heulandites prepared via topotactic condensation and direct synthesis that exhibit robust thermal stability, opening possibilities for new applications.

1250-kilovolt scanning transmission electron microscope

1984 ◽  
Vol 42 ◽  
pp. 624-625
Author(s):  
T. Imura ◽  
S. Maruse ◽  
K. Mihama ◽  
M. Iseki ◽  
M. Hibino ◽  
...  
Keyword(s):  
High Voltage ◽  
Electron Probe ◽  
Scanning Transmission Electron Microscope ◽  
Pressure Vessels ◽  
Practical Applications ◽  
Voltage Generator ◽  
Transmission Electron ◽  
Scanning Transmission ◽  
New Applications ◽  
High Voltage Generator

Ultra high voltage STEM has many inherent technical advantages over CTEM. These advantages include better signal detectability and signal processing capability. It is hoped that it will explore some new applications which were previously not possible. Conventional STEM (including CTEM with STEM attachment), however, has been unable to provide these inherent advantages due to insufficient performance and engineering problems. Recently we have developed a new 1250 kV STEM and completed installation at Nagoya University in Japan. It has been designed to break through conventional engineering limitations and bring about theoretical advantage in practical applications.In the design of this instrument, we exercised maximum care in providing a stable electron probe. A high voltage generator and an accelerator are housed in two separate pressure vessels and they are connected with a high voltage resistor cable.(Fig. 1) This design minimized induction generated from the high voltage generator, which is a high frequency Cockcroft-Walton type, being transmitted to the electron probe.

IN-BEAM NUCLEAR MAGNETIC RESONANCE OF β-ACTIVE NUCLEI PRODUCED BY CAPTURE OF POLARIZED NEUTRONS - SOME NEW APPLICATIONS

1982 ◽  
Vol 43 (C7) ◽  
pp. C7-305-C7-308
Author(s):  
H. Ackermann ◽  
B. Bader ◽  
P. Freiländer ◽  
P. Heitjans ◽  
G. Kiese ◽  
...  
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Polarized Neutrons ◽  
New Applications ◽  
Nuclear Magnetic

WHO WHO'S STRATEGY IN THE NATIONAL MEDICINE SECTOR FOR 2013-2023 AND NEW APPLICATIONS OF PHYTOTIC PRODUCTION IN THE CARPATHIANS

Fitoterapia ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 74-75
Author(s):  
O. I. Voloshуn ◽  
◽  
M. M. Stovpyuk ◽  
O. V. Hyndych ◽  
L. O. Voloshina ◽  
...  
Keyword(s):  
The Carpathians ◽  
New Applications

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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