Computational and Quantum Chemistry – Telegram
Computational and Quantum Chemistry
3.99K subscribers
48 photos
100 videos
177 files
1.6K links
A group dedicated to everything about theoretical and computational/quantum chemistry.
Please, write in English only. Keep on-topic. Be respectful always.
Download Telegram
Should automatic AI text-generator tools like ChatGPT be allowed in scientific writing?
Anonymous Poll
30%
No
39%
Yes
31%
Yes, since explicitly credited
Professor Dr. Rodolfo Goetze Fiorot from Universidade Federal Fluminense (Rio de Janeiro/Brazil) is recruiting a researcher, with a PhD for a maximum of 7 years, to submit a new FAPERJ project in theoretical chemistry for reaction mechanisms. The deadline is January 26th and interested parties should write to rodolfofiorot@id.uff.br.
👍5
Conquest v1.1 released

We are very pleased to announce the release of v1.1 of CONQUEST, a large-scale and linear scaling DFT code, capable of modelling thousands of atoms with exact diagonalisation and millions of atoms with linear scaling. This is the first full release of CONQUEST, featuring a significant number of changes:

* Reworking output completely for clarity and concision
* Implementation of the stabilised quasi-Newton method (SQNM) for robust, efficient structural optimisation
* Compatibility with LibXC v5 and ASE
* Implementation of spin polarisation for multi-site orbitals
* Updates to pseudopotential and pseudo-atomic orbital (PAO) generation and defaults for better accuracy and robustness
* Post-processing tools for DOS, charge density and STM image simulation (VESTA, Gaussian, VMD compatible)
* Identified and fixed many bugs

CONQUEST is freely available under an MIT licence. It runs well on a wide range of hardware, from laptops to HPC centres, and we encourage the community to use the code widely. Interested developers are always welcome to join the team - please contact one of us for more in-depth discussion.

CONQUEST GitHub: https://github.com/OrderN/CONQUEST-release
CONQUEST manual: https://conquest.readthedocs.io/en/latest/index.html
🔥2👍1👏1👌1
The 2023 Virtual Winter School on Computational Chemistry will begin next Monday, February 6th. Don’t miss the chance to register to this free online event! There will be lectures from prominent computational scientists, Q&A sessions, and two official workshops ministered by Q-Chem and Tinker.

https://winterschool.cc/
👍1
Simons - 2023 - Why Is Quantum Chemistry So Complicated.pdf
2.5 MB
Why Is Quantum Chemistry so Complicated? - Jack Simons
👍6
GROMACS 2023 is available!
As always, we’ve got several useful performance improvements, with or without GPUs, all enabled and automated by default. In addition, several new features are available for running simulations. We are extremely interested in your feedback on how well the new release works on your simulations and hardware. The new features are:

* The SYCL GPU implementation, which is the GPU portability layer that supports all major GPU platforms, has received major extensions in support for both platforms and features. To ensure portability in practice, the GROMACS GPU portability layer is actively developed with multiple SYCL implementations (hipSYCL, oneAPI DPC++, IntelLLVM) and regularly tested on multiple GPU backends.
* SYCL supports more GPU offload features: bonded forces and direct GPU-GPU communication with GPU-aware MPI.
* SYCL hardware support includes AMD (including RDNA support added here) and Intel for production as well as NVIDIA GPUs (not for production).
* SYCL optimizations targeting important HPC platforms.
* PME decomposition has been optimized and extended to support offloading the entire PME calculation to multiple GPUs, including the FFT computation; when combined with cuFFTmp or heFFTe this enables much improved strong scaling (experimental feature).
* CUDA Graph support has been added to execute GPU-resident single-/multi-GPU simulations using thread-MPI entirely on the GPU to improve performance (experimental feature).
* Apple M1/M2 GPUs are now supported via the OpenCL GPU backend.
* New ensemble temperature mdp options allow setting the temperature of the ensemble for simulations without temperature coupling or with different reference temperatures.
* With gmx dssp, GROMACS now has a native implementation of the DSSP algorithm, which replaces gmx do_dssp.

https://manual.gromacs.org/current/download.html
👍4👌3
acs.chemrev.1c00107.pdf
12.3 MB
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems - Chem. Rev. 2021, 121, 16, 9816–9872
2