Google AI Blog: Digitizing Smell: Using Molecular Maps to Understand Odor
https://ai.googleblog.com/2022/09/digitizing-smell-using-molecular-maps.html?m=1

A Web Tool for Calculating Substituent Denoscriptors Compatible with Hammett Sigma Constants
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The electron-donating and -accepting power of organic substituents is an important parameter affecting many properties of parent molecules, most notably their reactivity and pKa of ionisable groups. These substituent properties are described by Hammett σ constants obtained by measuring ionization constants of substituted benzoic acids. Although values of the Hammett σ constants have been measured for the most common functional groups, data for many important substituents are not available. In the present study, a method to calculate substituent denoscriptors compatible with the Hammett σ constants using quantum-chemically derived parameters is described. On this basis, a free web tool allowing to calculate electronic and hydrophobic substituent denoscriptors is made available at the link below:

https://peter-ertl.com/molecular/substituents/sigmas.html

Theory here: https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/cmtd.202200041

Orbital Optimized Density Functional Theory for Electronic Excited States
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Is this a revolution for theoretical excited-state chemistry?

https://pubs.acs.org/doi/10.1021/acs.jpclett.1c00744

To publish in academia is hard (and there is bias involved to make it harder)
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In a new study, the same paper as subjected to 534 reviewers. The name of the main author was changed to a novice scientist or to a high level (Nobel laureate) scientist. Depending just on the author’s name THE SAME paper was well reviewed (if the author is famous) or rejected if the author is not famous.

Preprint here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4190976

Breakthrough reported in machine learning-enhanced quantum chemistry
https://phys.org/news/2022-09-breakthrough-machine-learning-enhanced-quantum-chemistry.html

2 PhD positions theoretical & computational chemistr/physics @ University of Parma

Topics:
(a) Theoretical and computational approaches to molecular functional materials for application in organic electronics (mainly OLED): photophysics and environmental effects
(b) Theoretical and computational approaches to Chiral Induced Spin Selectivity (CISS) effect

Background: Master degree in chemistry, or in physics or in material science (or similar)

Duration: 3 years
Estimate starting date: January, 1st 2023
Monthly fellowship ≈ 1150€

For information: cristina.sissa@unipr.it; anna.painelli@unipr.it

OPEN ACCESS
Best-Practice DFT Protocols for Basic Molecular Computational Chemistry
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Many chemical investigations are supported by routine calculations of molecular structures, reaction energies, barrier heights, and spectroscopic properties. Most of these quantum-chemical calculations apply various combinations of DFT-based methods. This Scientific Perspective provides best-practice protocols and guidance in the choice of robust method combinations to deal with many day-to-day challenges in computational chemistry and discusses representative examples.

https://onlinelibrary.wiley.com/doi/10.1002/anie.202205735

First organic magnesium electride is stable at room temperature | Research | Chemistry World
https://www.chemistryworld.com/news/first-organic-magnesium-electride-is-stable-at-room-temperature/4016043.article

#workshop #virtual #genomics #beginner #level

Virtual workshop on Introduction to fundamentals and Bash Scripting for Genomics.

This two-day workshop focuses on the basics of genomics and using Linux for genomics. Further, It will provide concepts, and hands-on training on Linux commands noscripts and basics of genomics, such as designing experiments, accessing datasets from different databases, and data uploading to resources like NCBI.

🎙Our speakers, Dr. Meenakshi I (NCBS, India) & Dr.Samdani A (ICOA, France), carry Ph.D. degrees in Bioinformatics with rich of experience in Genomics.

✍️Who can apply?
Anyone interested in learning the basics of Linux and genomics study design and managing sequencing data. The workshop assumes that learners have no or little experience with Linux systems

✳️It is free for Undergraduate students.

👨‍💻For more info & registration, visit our site at https://www.nyberman.com/internship-trainings/workshop

📢«««««««
Channel @llbschool
Forum @letslearnbioinformatics

Artificial intelligence reduces a 100,000-equation quantum physics problem to only four equations
https://phys.org/news/2022-09-artificial-intelligence-equation-quantum-physics.html

Quantum developer tools for chemistry - Q# Blog
https://devblogs.microsoft.com/qsharp/quantum-developer-tools-for-chemistry/

A collective effort for building DFT | Nature Computational Science
https://www.nature.com/articles/s43588-022-00294-1

Scientist resolves one of the holy grails of physical chemistry after 17 years of research
https://phys.org/news/2022-09-scientist-holy-grails-physical-chemistry.html

Paper by team claiming to have achieved superconductivity at room temperature retracted
https://phys.org/news/2022-09-paper-team-superconductivity-room-temperature.html

- Visualizing Generic Reaction Patterns -

Reaction schemes for organic molecules play a crucial role in modern in silico drug design processes. In contrast to the classical drawn reaction diagrams, computational chemists prefer SMARTS based line notations due to a substantially increased expressiveness and precision. They are used to search databases, calculate synthesizability, generate new molecules, or simulate novel reactions. Working with computer-readable representations of reaction schemes can be challenging due to the complexity of the features to be represented. Line representations of reaction schemes can often be cryptic, even to experienced users. To simplify the work with Reaction SMARTS for synthetic, computational, and medicinal chemists, we introduce a visualization technique for reaction schemes and provide a respective tool, called ReactionViewer.

https://pubs.acs.org/doi/full/10.1021/acs.jcim.2c00992