From owner-chemistry.,at,.ccl.net Tue Sep 15 03:51:01 2015 From: "Peter Jarowski peterjarowski=gmail.com" To: CCL Subject: CCL: Case Studies of QM Computational Chemistry in Reactivity Message-Id: <-51738-150915034650-26199-8mP5W3uUFnTp8/ljjoOc3g ~~ server.ccl.net> X-Original-From: Peter Jarowski Content-Type: multipart/alternative; boundary=001a113ac3422a8809051fc462f7 Date: Tue, 15 Sep 2015 09:46:44 +0200 MIME-Version: 1.0 Sent to CCL by: Peter Jarowski [peterjarowski()gmail.com] --001a113ac3422a8809051fc462f7 Content-Type: text/plain; charset=UTF-8 Dear CCLers: I want to thank everyone for their responses to my question. In general, for theorists, we were able to stay on topic. When we forayed the discussion was quite heated, interesting and fun to watch. For my part, I am about to publish a paper with atomic charge analysis and now I am worried! I hope I land on the right side in the review process:) I am now writing again to see if we can refine the discussion further as I have enough responses regrading key examples of the utility of QM in predicting experimental (kinetic) outcomes. I have built a 9 question (not 10 as promised by Survey Monkey) survey to help us see where QM is in industry. Each question has an "other" section so please feel free to fill in. Once I have at least 50 respondents I will publish the metrics here on CCL. Here is the link: https://www.surveymonkey.com/r/35QL9ZH It will take a few minutes and should be rewarding to all. I look forward to your responses. For data scientists I think a more formulaic and quantifiable approach makes sense. Best Regards, Peter --001a113ac3422a8809051fc462f7 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Dear CCLers:

I want to th= ank everyone for their responses to my question. In general, for theorists,= we were able to stay on topic. When we forayed the discussion was quite he= ated, interesting and fun to watch. For my part, I am about to publish a pa= per with atomic charge analysis and now I am worried! I hope I land on the = right side in the review process:)

I am now writing again to s= ee if we can refine the discussion further as I have enough responses regra= ding key examples of the utility of QM in predicting experimental (kinetic)= outcomes.

I have built a 9 question (not 10 as promised by Su= rvey Monkey) survey to help us see where QM is in industry. Each question h= as an "other" section so please feel free to fill in. Once I have= at least 50 respondents I will publish the metrics here on CCL.

Here is the link:

https://www.surveymonkey.com/r/35QL9ZH

It wi= ll take a few minutes and should be rewarding to all.

I = look forward to your responses. For data scientists I think a more formulai= c and quantifiable approach makes sense.

Best Regards,
Peter


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