scholarly journals A New Generation of Chirped Pulse Rotational Spectroscopy with Applications to Structure Determination and Astrochemistry

2011 ◽  
Author(s):  
Justin Lindsay Neill
Author(s):  
Ranil M Gurusinghe ◽  
Nureshan Dias ◽  
Ritter Krueger ◽  
Arthur G. Suits

1977 ◽  
Vol 16 (12) ◽  
pp. 3219-3222 ◽  
Author(s):  
Dietrich. Schwoch ◽  
Anton B. Burg ◽  
Robert A. Beaudet

2020 ◽  
Vol 22 (16) ◽  
pp. 8933-8939
Author(s):  
Begüm Rukiye Özer ◽  
In Heo ◽  
Jong Chan Lee ◽  
Christian Schröter ◽  
Thomas Schultz

Isotope-selective rotational spectroscopy allows determination of molecular structure independent of assumptions or theoretical predictions.


2019 ◽  
Vol 21 (35) ◽  
pp. 18911-18919
Author(s):  
Kin Long Kelvin Lee ◽  
Sven Thorwirth ◽  
Marie-Aline Martin-Drumel ◽  
Michael C. McCarthy

Rotational spectra of three Ge carbides, linear GeC4, GeC5, and GeC6 have been observed using chirped pulse and cavity Fourier transform microwave spectroscopy via laser ablation, guided by new high-level quantum chemical calculations.


2017 ◽  
Vol 8 (24) ◽  
pp. 6180-6188 ◽  
Author(s):  
Daniel P. Zaleski ◽  
Lawrence B. Harding ◽  
Stephen J. Klippenstein ◽  
Branko Ruscic ◽  
Kirill Prozument

2011 ◽  
Vol 269 (1) ◽  
pp. 21-29 ◽  
Author(s):  
Justin L. Neill ◽  
Steven T. Shipman ◽  
Leonardo Alvarez-Valtierra ◽  
Alberto Lesarri ◽  
Zbigniew Kisiel ◽  
...  

2021 ◽  
Author(s):  
Lia Yeh ◽  
David Patterson ◽  
Jieyu Yan ◽  
Lincoln Satterthwaite ◽  
Dylan Finestone

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2251
Author(s):  
Giuseppe Di Modica ◽  
Luca Evangelisti ◽  
Luca Foschini ◽  
Assimo Maris ◽  
Sonia Melandri

In the last years, the development of broadband chirped-pulse Fourier transform microwave spectrometers has revolutionized the field of rotational spectroscopy. Currently, it is possible to experimentally obtain a large quantity of spectra that would be difficult to analyze manually due to two main reasons. First, recent instruments allow obtaining a considerable amount of data in very short times, and second, it is possible to analyze complex mixtures of molecules that all contribute to the density of the spectra. AUTOFIT is a spectral assignment software application that was developed in 2013 to support and facilitate the analysis. Notwithstanding the benefits AUTOFIT brings in terms of automation of the analysis of the accumulated data, it still does not guarantee a good performance in terms of execution time because it leverages the computing power of a single computing machine. To cater to this requirement, we developed a parallel version of AUTOFIT, called HS-AUTOFIT, capable of running on high-performance computing (HPC) clusters to shorten the time to explore and analyze spectral big data. In this paper, we report some tests conducted on a real HPC cluster aimed at providing a quantitative assessment of HS-AUTOFIT’s scaling capabilities in a multi-node computing context. The collected results demonstrate the benefits of the proposed approach in terms of a significant reduction in computing time.


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