Protonation and phase effects on the NMR chemical shifts of imidazoles and pyrazoles: experimental results and GIAO calculationsElectronic supplementary information (ESI) available: absolute and relative shieldings calculated at the B3LYP/6-311++G**//B3LYP/6-311++G** level for compounds V to XXI as well as pyrazole and 3,5-dimethylpyrazole dimers, trimers and tetramers (420 shieldings). See http://www.rsc.org/suppdata/nj/b2/b210251j/

2003 ◽  
Vol 27 (4) ◽  
pp. 734-742 ◽  
Author(s):  
Rosa M. Claramunt ◽  
Concepción López ◽  
María Ángeles García ◽  
Gleb S. Denisov ◽  
Ibon Alkorta ◽  
...  
Keyword(s):  
Chemical Shifts ◽  
Experimental Results ◽  
Supplementary Information ◽  
Nmr Chemical Shifts

scholarly journals Is (benzene)Cr(CO)3 really more aromatic than benzene?

2017 ◽  
Vol 95 (3) ◽  
pp. 263-270 ◽  
Author(s):  
Amnon Stanger
Keyword(s):  
Local Ring ◽  
Excellent Agreement ◽  
Ring Current ◽  
Chemical Shifts ◽  
Experimental Results ◽  
Nmr Chemical Shifts ◽  
Ring Currents ◽  
Global And Local

(benzene)Cr(CO)3 was claimed to be more aromatic than benzene, based on the central 1H Me chemical shifts in dimethyldihydropyrene annulated to it. In this paper, several dihydropyrenes are computationally investigated. NICS-scan methods are used to assess the ring current properties, and NMR calculations are used for obtaining NMR chemical shifts. The parent and four benz-annulated dihydropyrenes show excellent agreement with the experimental results, reported by R. Mitchell in several papers. The effect of annulating the antiaromatic cyclobutadiene was shown to be larger than that of benzene and to change the type of ring currents; while benz-annulated dihydropyrenes maintain local 14-annulene and local benzenic ring currents, the cyclobutadiene-annulated dihydropyrenes show global (and local) ring currents. A NICS-scan study of (benzene)Cr(CO)3 and a NICS-XY-scan study of the (CO)3Cr(C6H4)-annulated to dihydropyrene show that the benzene in the Cr complex is at most aromatic as benzene, probably somewhat less. A detailed study of the 1H chemical shifts suggests that the experimental results were somewhat misinterpreted, and that (benzene)Cr(CO)3 is at most as aromatic as benzene.

Relativistic and Dynamic effects are needed to correctly model the 1H NMR Chemical Shifts of an Iridium Polyhydride Cluster

2020 ◽  
Author(s):  
Abril C. Castro ◽  
David Balcells ◽  
Michal Repisky ◽  
Trygve Helgaker ◽  
Michele Cascella
Keyword(s):  
1H Nmr ◽  
Chemical Shifts ◽  
Dynamic Effects ◽  
Nmr Chemical Shifts

Accurate prediction of 195Pt NMR chemical shifts for a series of Pt(ii) and Pt(iv) antitumor agents by a non-relativistic DFT computational protocol

2014 ◽  
Vol 43 (14) ◽  
pp. 5409-5426 ◽  
Author(s):  
Athanassios C. Tsipis ◽  
Ioannis N. Karapetsas
Keyword(s):  
Dft Calculations ◽  
Anticancer Agents ◽  
Antitumor Agents ◽  
Chemical Shifts ◽  
Accurate Prediction ◽  
Nmr Chemical Shifts ◽  
Relativistic Dft ◽  
Square Planar ◽  
Wide Range ◽  
Computational Protocol

Exhaustive benchmark DFT calculations reveal that the non-relativistic GIAO-PBE0/SARC-ZORA(Pt)∪6-31+G(d)(E) computational protocol predicts accurate 195Pt NMR chemical shifts for a wide range of square planar Pt(ii) and octahedral Pt(iv) anticancer agents.

scholarly journals How the Multiplicity of Suggested Information Affects the Behavior of a User in a Recommender System

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 741
Author(s):  
Yuseok Ban ◽  
Kyungjae Lee
Keyword(s):  
High Precision ◽  
Recommender System ◽  
Visual Information ◽  
Experimental Results ◽  
Supplementary Information ◽  
Digital Platform ◽  
Different Types ◽  
Types Of Information

Many researchers have suggested improving the retention of a user in the digital platform using a recommender system. Recent studies show that there are many potential ways to assist users to find interesting items, other than high-precision rating predictions. In this paper, we study how the diverse types of information suggested to a user can influence their behavior. The types have been divided into visual information, evaluative information, categorial information, and narrational information. Based on our experimental results, we analyze how different types of supplementary information affect the performance of a recommender in terms of encouraging users to click more items or spend more time in the digital platform.

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