Quenching rates and critical densities of c-C3H2

2019 ◽  
Vol 15 (S350) ◽  
pp. 148-151
Author(s):  
Malek Ben Khalifa ◽  
Emna Sahnoun ◽  
Silvia Spezzano ◽  
Laurent Wiesenfeld ◽  
Kamel Hammami ◽  
...  
Keyword(s):  
Potential Energy Surfaces ◽  
Full Potential ◽  
Thermodynamical Equilibrium ◽  
Medium Temperature ◽  
Permanent Electric Dipole Moment ◽  
Temperature Regimes ◽  
Wide Range ◽  
History Of ◽  
Energy Surfaces ◽  
Local Thermodynamical Equilibrium

AbstractCyclopropenylidene,, is a simple hydrocarbon, ubiquitous in astrophysical gases, and possessing a permanent electric dipole moment. Its readily observed multifrequency rotational transitions make it an excellent probe for the physics and history of interstellar matter. The collisional properties of with He are presented here. We computed the full Potential Energy Surfaces, and we perform quantum scattering in order to provide rates of quenching and excitation for low to medium temperature regimes. We discuss issues with the validity of the usual Local Thermodynamical Equilibrium assumption, and also the intricacies of the spectroscopy of an asymmetric top. We present the wide range of actual critical densities, as recently observed.

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>

scholarly journals De novo exploration and self-guided learning of potential-energy surfaces

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Noam Bernstein ◽  
Gábor Csányi ◽  
Volker L. Deringer
Keyword(s):  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Materials Science ◽  
De Novo ◽  
Interatomic Potential ◽  
Single Point ◽  
Small Unit ◽  
Wide Range ◽  
Unit Cells ◽  
Energy Surfaces

Abstract Interatomic potential models based on machine learning (ML) are rapidly developing as tools for material simulations. However, because of their flexibility, they require large fitting databases that are normally created with substantial manual selection and tuning of reference configurations. Here, we show that ML potentials can be built in a largely automated fashion, exploring and fitting potential-energy surfaces from the beginning (de novo) within one and the same protocol. The key enabling step is the use of a configuration-averaged kernel metric that allows one to select the few most relevant and diverse structures at each step. The resulting potentials are accurate and robust for the wide range of configurations that occur during structure searching, despite only requiring a relatively small number of single-point DFT calculations on small unit cells. We apply the method to materials with diverse chemical nature and coordination environments, marking an important step toward the more routine application of ML potentials in physics, chemistry, and materials science.

scholarly journals When Are Two Hydrogen Bonds Better than One? Accurate First-Principles Models Explain the Balance of Hydrogen Bond Donors and Acceptors Found in Proteins

2020 ◽  
Author(s):  
Vyshnavi Vennelakanti ◽  
Helena W. Qi ◽  
Rimsha Mehmood ◽  
Heather Kulik
Keyword(s):  
Hydrogen Bonds ◽  
Potential Energy Surfaces ◽  
Predictive Accuracy ◽  
Protein Structures ◽  
Geometric Constraints ◽  
Model Systems ◽  
Electronic Effects ◽  
Many Body ◽  
Wide Range ◽  
Energy Surfaces

<p>Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (i.e., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4,000 HBs, of which > 500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O–H···O HBs than N–H···O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction. </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>

scholarly journals Identifying and tracing potential energy surfaces of electronic excitations with specific character via their transition origins: application to oxirane

2015 ◽  
Vol 17 (18) ◽  
pp. 12065-12079 ◽  
Author(s):  
Jian-Hao Li ◽  
T. J. Zuehlsdorff ◽  
M. C. Payne ◽  
N. D. M. Hine
Keyword(s):  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Specific Character ◽  
Electronic Excitations ◽  
Wide Range ◽  
Energy Surfaces

We show that the transition origins of electronic excitations identified by quantified natural transition orbital (QNTO) analysis can be employed to connect potential energy surfaces (PESs) according to their character across a wide range of molecular geometries.

scholarly journals The Institute of Economics of the Ural Branch of the Russian Academy of Sciences: Past and Present Research

2021 ◽  
Vol 18 (1) ◽  
pp. 1-28
Author(s):  
V. L. Bersenev ◽  
◽  
V. St. Bochko ◽  
M. Vl. Vlasov ◽  
V. V. Sukhikh ◽  
...  
Keyword(s):  
Political Economy ◽  
Economic Thought ◽  
Economic Research ◽  
Full Potential ◽  
Social Infrastructure ◽  
Russian Academy Of Sciences ◽  
Wide Range ◽  
History Of ◽  
Academy Of Sciences

The article describes the contribution made by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences (RAS) (Ekaterinburg, Russia) to the development of economic theory. It is shown how the Institute’s history of research fits into the long-standing tradition of economic thought, which studied the role of people both as agents of economic activity and as its objects. The article traces back the development of economic thought from Antiquity, through the modern period and the heyday of political economy in the nineteenth century, to the contemporary stage. Throughout its history, economic research dealt with such problems as human behaviour within the system of economic relationships, social policies as a form of public support of the manufacturing sector, labour as a way of realizing people’s full potential, and so on. The history of the Institute of Economics of the Ural Branch of the RAS started in the 1970s. The research was conducted in a number of areas, in particular the development of social infrastructure, methods of evaluation of living and materialized labour, the evolution of ownership during economic reforms, institutional support of economic transformations and the role of human agents in economy in twenty-first century Russia. Moreover, as the study makes clear, on researchers’ own initiative, a number of other projects were realized, covering a wide range of topics, from political economy of socialism to cliometrics.

scholarly journals When Are Two Hydrogen Bonds Better than One? Accurate First-Principles Models Explain the Balance of Hydrogen Bond Donors and Acceptors Found in Proteins

2020 ◽  
Author(s):  
Vyshnavi Vennelakanti ◽  
Helena W. Qi ◽  
Rimsha Mehmood ◽  
Heather Kulik
Keyword(s):  
Hydrogen Bonds ◽  
Potential Energy Surfaces ◽  
Predictive Accuracy ◽  
Protein Structures ◽  
Geometric Constraints ◽  
Model Systems ◽  
Electronic Effects ◽  
Many Body ◽  
Wide Range ◽  
Energy Surfaces

<p>Hydrogen bonds (HBs) play an essential role in the structure and catalytic action of enzymes, but a complete understanding of HBs in proteins challenges the resolution of modern structural (i.e., X-ray diffraction) techniques and mandates computationally demanding electronic structure methods from correlated wavefunction theory for predictive accuracy. Numerous amino acid sidechains contain functional groups (i.e., hydroxyls in Ser/Thr or Tyr and amides in Asn/Gln) that can act as either HB acceptors or donors (HBA/HBD) and even form simultaneous, ambifunctional HB interactions. To understand the relative energetic benefit of each interaction, we characterize the potential energy surfaces of representative model systems with accurate coupled cluster theory calculations. To reveal the relationship of these energetics to the balance of these interactions in proteins, we curate a set of 4,000 HBs, of which > 500 are ambifunctional HBs, in high-resolution protein structures. We show that our model systems accurately predict the favored HB structural properties. Differences are apparent in HBA/HBD preference for aromatic Tyr versus aliphatic Ser/Thr hydroxyls because Tyr forms significantly stronger O–H···O HBs than N–H···O HBs in contrast to comparable strengths of the two for Ser/Thr. Despite this residue-specific distinction, all models of residue pairs indicate an energetic benefit for simultaneous HBA and HBD interactions in an ambifunctional HB. Although the stabilization is less than the additive maximum due both to geometric constraints and many-body electronic effects, a wide range of ambifunctional HB geometries are more favorable than any single HB interaction. </p>

Recent Applications of High Resolution Electron Microscopy to Crystalline Arrays of Virus Particles

1978 ◽  
Vol 36 (3) ◽  
pp. 470-482 ◽  
Author(s):  
R.W. Horne
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Analytical Techniques ◽  
Staining Technique ◽  
High Resolution Electron Microscopy ◽  
Optical Diffraction ◽  
Full Potential ◽  
Virus Particles ◽  
Resolution Electron ◽  
Wide Range

The technique of surrounding virus particles with a neutralised electron dense stain was described at the Fourth International Congress on Electron Microscopy, Berlin 1958 (see Home & Brenner, 1960, p. 625). For many years the negative staining technique in one form or another, has been applied to a wide range of biological materials. However, the full potential of the method has only recently been explored following the development and applications of optical diffraction and computer image analytical techniques to electron micrographs (cf. De Hosier & Klug, 1968; Markham 1968; Crowther et al., 1970; Home & Markham, 1973; Klug & Berger, 1974; Crowther & Klug, 1975). These image processing procedures have allowed a more precise and quantitative approach to be made concerning the interpretation, measurement and reconstruction of repeating features in certain biological systems.

Group Experiences and Individual Differences in Stuttering

2019 ◽  
Vol 62 (12) ◽  
pp. 4335-4350 ◽  
Author(s):  
Seth E. Tichenor ◽  
J. Scott Yaruss
Keyword(s):  
Individual Differences ◽  
Support Groups ◽  
Support Group ◽  
Affective States ◽  
Life Outcomes ◽  
Self Help ◽  
Wide Range ◽  
Group Experiences ◽  
History Of ◽  
Adults Who Stutter

Purpose This study explored group experiences and individual differences in the behaviors, thoughts, and feelings perceived by adults who stutter. Respondents' goals when speaking and prior participation in self-help/support groups were used to predict individual differences in reported behaviors, thoughts, and feelings. Method In this study, 502 adults who stutter completed a survey examining their behaviors, thoughts, and feelings in and around moments of stuttering. Data were analyzed to determine distributions of group and individual experiences. Results Speakers reported experiencing a wide range of both overt behaviors (e.g., repetitions) and covert behaviors (e.g., remaining silent, choosing not to speak). Having the goal of not stuttering when speaking was significantly associated with more covert behaviors and more negative cognitive and affective states, whereas a history of self-help/support group participation was significantly associated with a decreased probability of these behaviors and states. Conclusion Data from this survey suggest that participating in self-help/support groups and having a goal of communicating freely (as opposed to trying not to stutter) are associated with less negative life outcomes due to stuttering. Results further indicate that the behaviors, thoughts, and experiences most commonly reported by speakers may not be those that are most readily observed by listeners.

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