Sounds like performance is not an issue.

 

I just noticed that WebPlotDigitizer has recently been updated.

It is often necessary to reverse engineer images of data visualizations to extract the underlying numerical data. WebPlotDigitizer is a semi-automated tool that makes this process extremely easy.

More details on the Data Analysis Tools Page.

 

A couple of the Apps on the Mobile Science site have been updated.

Most notably the Human Anatomy Atlas, which is currently the fifth most viewed app on the site.

What’s New Jul 27, 2020 Version 2021.1.64 Introducing Visible Body User Accounts! With your VB User Account, you can:

• Save and share all your newly created custom interactive content!
• Make 3D Views and Tours that include tags, 3D drawings, and notes, and edit them whenever you want.
• Share your 3D views with other Atlas 2021.1 users.

Note: Visible Body accounts have replaced iCloud in Human Anatomy Atlas 2021.1 or later.

 

Registration is open!!

• Event 3rd RSC-BMCS / RSC-CICAG Artificial Intelligence in Chemistry
• Dates Monday-Tuesday, 28th-29th September 2020
• Format A virtual event
• Organisers RSC BMCS and RSC CICAG (Royal Society of Chemistry’s Biological and Medicinal Chemistry Sector, and Chemical Information and Computer Applications Group)
• Websites https://www.maggichurchouseevents.co.uk/bmcs. Also https://www.rsc.org/events/detail/42785/3rd-rsc-bmcs-rsc-cicag-artificial-intelligence-in-chemistry
• Twitter #AIChem20

Synopsis.
Artificial Intelligence is presently experiencing a renaissance in development of new methods and practical applications to ongoing challenges in Chemistry. Following the successes of two “Artificial Intelligence in Chemistry” meetings in 2018 and 2019, we are pleased to announce that the Biological & Medicinal Chemistry Sector (BMCS) and Chemical Information & Computer Applications Group (CICAG) of the Royal Society of Chemistry are once again organising a conference to present the current efforts in applying these new methods. The meeting will be held over two days and combine aspects of artificial intelligence and deep machine learning methods to applications in chemistry

The Call for Abstracts is Open.
Applications for both oral and poster presentations are invited. Posters will be displayed during a dedicated poster session and, at the time of submission, applicants are asked if they wish to provide a two-minute lightning oral presentation. The closing date for all submissions is Friday, 31st July.

There will be a mix of plenary and keynote talks as well as poster sessions with some lightning poster talks. There will also be exhibitor sessions, and we are currently exploring options for providing breakout rooms for discussions.

Confirmed Speakers
Teaching neural network to attach and detach electrons from molecules
Keynote: Olexandr Isayev, Carnegie Mellon, US

DNA-encoded small molecules libraries meet machine learning
Keynote: Patrick Riley, Google, US

Artificial neural network enhanced synthesis and retrosynthesis prediction
Esben Jannik Bjerrum, AstraZeneca, SE

Machine learning for free energy calculations
Hannah Bruce McDonald, Memorial Sloan Kettering Cancer Center, US

Data driven representations for predicting molecular properties: benchmarking and applications in generative chemistry
Jessica Lanini, Novartis, CH

Using machine learning for molecular dynamics simulations
Sereina Riniker, ETH Zürich, CH

Registration Participation is free of charge, although registration is required so we can ensure the numbers are covered by the virtual meeting software license:
- online via this link (no payment required) I

AI - second announcement

 

A new version of MOPAC has been released full details are in this publication "A New Release of MOPAC Incorporating the INDO/S Semiempirical Model with CI Excited States" DOI.

We have incorporated the semiempirical INDO/S Hamiltonian into a new release of MOPAC2016, which has long been at the forefront of semiempirical quantum chemical methods (SEQMs). Our new code enables the calculation of excited states using the INDO/S Hamiltonian combined with a configuration interaction approach using single excitations (CIS), single and double excitations (CISD), or multiple reference determinants (MRCI) where reference determinants are generated using a complete active space (CAS) approach. The capacity to perform excited-state calculations beyond the CIS level makes INDO/CI one of the few low-cost computational methods capable of accurately modeling states with substantial double-excitation character. Solvent corrections to the ground-state and excited-state energies can be computed using the COSMO implicit solvent model, incorporating state-specific corrections to the excited states based on the solvent refractive index. We demonstrate that this code produces physically reasonable electronic structures, absorption spectra, and solvatochromic shifts at low computational costs for systems up to hundreds of atoms, and for both organic molecules and metal clusters.

The release notes are here.

And downloads here.