Experimental investigations and ab initio studies of selenium(ii) dialkanethiolates, Se(SR)2

2004 ◽  
pp. 3765-3771 ◽  
Author(s):  
Holger Fleischer ◽  
Stefan Glang ◽  
Dieter Schollmeyer ◽  
Norbert W. Mitzel ◽  
Michael Bühl
2011 ◽  
Vol 115 (45) ◽  
pp. 22451-22460 ◽  
Author(s):  
Witold Piskorz ◽  
Filip Zasada ◽  
Paweł Stelmachowski ◽  
Oliver Diwald ◽  
Andrzej Kotarba ◽  
...  

2013 ◽  
Vol 1581 ◽  
Author(s):  
Peter Entel ◽  
Vladimir V. Sokolovskiy ◽  
Vasiliy D. Buchelnikov ◽  
Denis Comtesse ◽  
Mehmet Acet

ABSTRACTThe structural, electronic and magnetic properties of functional Ni-Mn-(Ga, In, Sn) and Pt-Ni-(Ga, Sn) alloys are studied by first-principles and Monte Carlo tools. The ab initio calculations give a basic understanding of the underlying physics which is associated with the complex magnetic behavior arising from the competition of ferro- and antiferromagnetic interactions for excess Mn atoms in the unit cell. We show that the resulting complex magnetic ordering is the driving mechanism of structural transformations and multifunctional properties of Heusler alloys associated with magnetic shape-memory, magnetocaloric and elastocaloric effects. The thermodynamic properties can be calculated by using the ab initio magnetic exchange parameters in finite-temperature Monte Carlo simulations. Entropy and specific heat changes associated with the magnetic changes and emergence of microstructure across the magnetostructural transition are pointed out. We show how to optimize the functional properties by tuning the compositional changes, for example, a magnetic shape-memory effect of more than 14% can be achieved in Pt-Ni-Mn-Ga alloys. The theoretical studies are accompanied by experimental investigations.


1999 ◽  
Vol 38 (16) ◽  
pp. 3725-3729 ◽  
Author(s):  
Holger Fleischer ◽  
Sandra Stauf ◽  
Dieter Schollmeyer

2021 ◽  
pp. 160244
Author(s):  
Parveen Akhtar ◽  
M. Junaid Iqbal Khan ◽  
Zarfishan Kanwal ◽  
Shahid M. Ramay ◽  
Asif Mahmood ◽  
...  

2021 ◽  
pp. 138938
Author(s):  
Parveen Akhtar ◽  
M. Junaid Iqbal Khan ◽  
Shahid M. Ramay ◽  
Asif Mahmood ◽  
Murtaza Saleem ◽  
...  

2021 ◽  
Author(s):  
Alon Grinberg Dana ◽  
Haoyang Wu ◽  
Duminda Ranasinghe ◽  
Frank C. Pickard IV ◽  
Geoffrey P. F. Wood ◽  
...  

While different flavors of API stress testing systems have been used in experimental investigations for decades, the detailed kinetics of such systems as well as the chemical composition of prominent reactive species, specifically reactive oxygen species, are unknown.<br>As a first step toward understanding and modeling API oxidation in stress testing, we investigated a typical radical "soup" solution an API is subject to during stress testing.<br>Here we applied ab-initio electronic structure calculations to automatically generate and refine a detailed chemical kinetics model, taking a fresh look at API oxidation.<br>We generated a detailed kinetic model for a representative azobisisobutyronitrile (AIBN)/H<sub>2</sub>O/CH<sub>3</sub>OH stress-testing system with varied co-solvent ratio (50%/50% -- 99.5%/0.5% vol. water/methanol) and for representative pH values (4--10) at 40oC stirred and open to the atmosphere.<br>At acidic conditions hydroxymethyl alkoxyl is the dominant alkoxyl radical, and at basic conditions, for most studied initial methanol concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl radical, albeit at an overall lower concentration.<br>At acidic conditions the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl radicals are relatively high and comparable, while at both neutral and basic pH conditions, superoxide becomes the prominent radical in the system.<br>The present work reveals the prominent species in a common model API stress testing system at various co-solvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates usage of novel software tools for automated chemical kinetic model generation and ab-initio refinement.


2021 ◽  
Author(s):  
Ruben Van Lommel ◽  
Jonathan Bock ◽  
Constantin Daniliuc ◽  
Ulrich Hennecke ◽  
Frank De Proft

The halolactonization reaction is one of the most common electrophilic addition reactions to alkenes. The mechanism is generally viewed as a two-step pathway, which involves the formation of an ionic...


2021 ◽  
Author(s):  
Alon Grinberg Dana ◽  
Haoyang Wu ◽  
Duminda Ranasinghe ◽  
Frank C. Pickard IV ◽  
Geoffrey P. F. Wood ◽  
...  

While different flavors of API stress testing systems have been used in experimental investigations for decades, the detailed kinetics of such systems as well as the chemical composition of prominent reactive species, specifically reactive oxygen species, are unknown.<br>As a first step toward understanding and modeling API oxidation in stress testing, we investigated a typical radical "soup" solution an API is subject to during stress testing.<br>Here we applied ab-initio electronic structure calculations to automatically generate and refine a detailed chemical kinetics model, taking a fresh look at API oxidation.<br>We generated a detailed kinetic model for a representative azobisisobutyronitrile (AIBN)/H<sub>2</sub>O/CH<sub>3</sub>OH stress-testing system with varied co-solvent ratio (50%/50% -- 99.5%/0.5% vol. water/methanol) and for representative pH values (4--10) at 40oC stirred and open to the atmosphere.<br>At acidic conditions hydroxymethyl alkoxyl is the dominant alkoxyl radical, and at basic conditions, for most studied initial methanol concentrations, cyanoisopropyl alkoxyl becomes the dominant alkoxyl radical, albeit at an overall lower concentration.<br>At acidic conditions the levels of cyanoisopropyl peroxyl, hydroxymethyl peroxyl, and hydroperoxyl radicals are relatively high and comparable, while at both neutral and basic pH conditions, superoxide becomes the prominent radical in the system.<br>The present work reveals the prominent species in a common model API stress testing system at various co-solvent and pH conditions, sets the stage for an in-depth quantitative API kinetic study, and demonstrates usage of novel software tools for automated chemical kinetic model generation and ab-initio refinement.


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