Fast cheminformatics fingerprint search, anywhere you use Python

Chemfp is an analytics platform for cheminformatics fingerprints. It contains command-line tools and an extensive Python library for fingerprint generation, high-performance similarity search, diversity selection, and exploratory research.

Its market-leading performance and comprehensive API make it easy for you to add fast similarity search anywhere you use Python.

Why chemfp?
* Do you want single-threaded search of 1M 1024-bit fingerprints in under 10 milliseconds?
* Do you want to make a sparse similarity matrix from 1M 2048-bit fingerprints in less than 30 minutes on a four core machine?
* Do you want to include fingerprint similarity results in your Python web application?
* Do you do MaxMin or sphere exclusion diversity selection?
... with fast reload times during development, and without the complexity of using a dedicated search server?
* Do you work with fingerprints from multiple chemistry toolkits, or have custom fingerprint types?
* Do you want command-line tools with sub-second similarity search times?
* Do you program in Python and want to write new fingerprint analysis programs?
* Do you want the option to have the source code with no time-based licensing?

https://chemfp.com/index.html

Theoretical calculations predicted now-confirmed tetraneutron, an exotic state of matter
https://phys.org/news/2022-06-theoretical-now-confirmed-tetraneutron-exotic-state.html

Electrons take the fast and slow lanes at the same time
https://phys.org/news/2022-06-electrons-fast-lanes.html

Watch "This insane machine can see ATOMS!" on YouTube
https://youtu.be/eYVNZgnQ8gE

Many recent density functionals are numerically unstable
(Susi Lehtola, Miguel A. L. Marques)
—
Most computational studies in chemistry and materials science are based on the use of density functional theory. Although the exact density functional is unknown, several density functional approximations (DFAs) offer a good balance of affordable computational cost and semi-quantitative accuracy for applications. The development of DFAs still continues on many fronts, and several new DFAs aiming for improved accuracy are published every year. However, the numerical stability of these DFAs is an often overlooked problem. In this work, we look at all 592 DFAs for three-dimensional systems available in Libxc 5.2.2 and examine the convergence of the density functional total energy based on tabulated atomic Hartree-Fock wave functions. We show that several recent DFAs, including the celebrated SCAN family of functionals, suffer from strong numerical instabilities that make the functionals unsuitable for high-precision studies. In fact, their convergence with respect to quadrature is impractically slow, requiring thousands of radial quadrature points to achieve reliable total energies. These results suggest that numerical stability should be a core consideration in the development of new density functionals.

https://arxiv.org/abs/2206.14062#

Scientists Synthesize New Carbon Material: A Two-Dimensional Monolayer Polymeric Fullerene
https://scitechdaily.com/scientists-synthesize-new-carbon-material-a-two-dimensional-monolayer-polymeric-fullerene/

PhD position - University of Amsterdam

Do you want to do a PhD in supramolecular catalysis and sustainable chemistry? We are hiring! Check out the details: https://vacatures.uva.nl/UvA/job/PhD-Position-in-Homogeneous-Catalysis/749824902/

DFT Exchange: Sharing Perspectives on the Workhorse of Quantum Chemistry and Materials Science

In this paper, the history, present status, and future of density-functional theory (DFT) is informally reviewed and discussed by 70 workers in the field, including molecular scientists, materials scientists, method developers and practitioners. The format of the paper is that of a roundtable discussion, in which the participants express and exchange views on DFT in the form of 300 individual contributions, formulated as responses to a preset list of 26 questions. Supported by a bibliography of 776 entries, the paper represents a broad snapshot of DFT, anno 2022.

https://chemrxiv.org/engage/chemrxiv/article-details/62974da519595958f0bcc339

Opeb Access - Tutorial Review -
The devil in the details: A tutorial review on some undervalued aspects of density functional theory calculations

Density functional theory (DFT) has become ubiquitous for chemical applications in research and in education. The exact functional at the foundation of DFT is unfortunately unknown, and issues arise when choosing an approximation for a specific application. With this tutorial review, we tackle the selection problem and many related ones, such as the choices of a basis set and of an integration grid, that are often overlooked by occasional practitioners and by more experienced users as well. We offer a practical approach in the form of a commented notebook containing 12 experiences that can be run on a simple computer in just a few hours. We propose this review as a primary source for those who are willing to include DFT in their everyday research or teaching activities in a way that reflects the research advances of the field in the last couple of decades.

https://onlinelibrary.wiley.com/doi/10.1002/qua.26332

Physicists detect a new type of molecular bond – Physics World
https://physicsworld.com/a/physicists-detect-a-new-type-of-molecular-bond/

Virtual Winter School on Computational Chemistry - Africa Edition
Date: 05.08.2022
Time: 09:00 - 18:30 CEST

In association with VCCA-2022 the organising committee of the Virtual Winter School on Computational Chemistry will be holding a one-day satellite symposium on Friday August 5. This one-day event will be hosted in the VWSCC's space, kindly sponsored by Gather, and will be a condensed version of our annual VWSCC event, focusing on showcasing African science to the rest of the world. Since 2015 through VWSCC we have endeavoured to bring our speakers to the rest of the world virtually. In this event we hope the global community will come to see what is happening in Africa. The day will be a mixture of invited talks, poster presentations and panel discussions on topics such as getting jobs, forming collaborations, computing resources, education…

The format of the day (in CEST/CAT) will be:
09:00 - 12:00 Invited talks - more information coming soon
Break
14:00 - 15.30 Panel discussion sessions - more information coming soon
Break
17:00 - 18:30 Single-Figure Presentations

SFPs (single figure presentations) submissions are particularly encouraged from researchers working at African institutions, especially students. You will be given the opportunity to give a flash presentation of your work in our virtual poster room and mingle with other attendees. There will be prizes of speaking slots at the next edition of the Virtual Winter School.

Everyone is welcome to participate and we hope to see representation from as many countries as possible.

Registration is free, but mandatory. Read more end register here: https://winterschool.cc/africa-calling

Potential energy surfaces of water mapped for the first time
https://phys.org/news/2022-07-potential-energy-surfaces.html

A celebrated AI has learned a new trick: How to do chemistry
https://phys.org/news/2022-06-celebrated-ai-chemistry.html

CP2K v2022.1 is available

CP2K is the popular quantum chemistry and solid state physics software package. And, yes, it changed the numbering scheme.

* Migrate tensor operations to new sparse matrix library DBM (#1863)
* Add HIP support for PW (#1864)
* Drop support for GCC 5 (#1878)
* Add GAPW Voronoi integration (#1919)
* Remove deprecated sections LIBXC and KE_LIBXC (#1921)
* Add LibXC equivalents to ADMM exchange potentials (#1972)
* Improve support for metaGGA functionals (#1974)
* Use SPLA for offloading dgemm on GPUs in the mp2 module (#1951)
* TDDFT: enable state following using transition charge finger print (#1991)
* Add barostat for frozen atoms in absolute coordinate (#2000)
* Fix linkage of COSMA (#2021)
* Migrate to centralized __OFFLOAD_CUDA/HIP flags (#2027)
* Add low-scaling SOS-Laplace MP2 forces (#2031)
* Refactoring of basis set optimization code (#2068)
* Add k-points for the GW self-energy (#2073)
* CDFT: forces based on Hirshfeld partitioning (#2111)
* RPA: Add low-scaling gradients (#2131)
* MP2: Add more solvers (#2142)
* GW: Add 4-center Hartree-Fock and ADMM for exchange self-energy (#2145)
* Print vibrational modes for Newton-X (#2146)
* Add partially occupied Wannier states (#2154)
* Add GAPW_XC for TDDFPT energies (#2178)

https://github.com/cp2k/cp2k/releases/tag/v2022.1

Open Access - Completing density functional theory by machine learning hidden messages from molecules
—
Kohn–Sham density functional theory (DFT) is the basis of modern computational approaches to electronic structures. Their accuracy heavily relies on the exchange-correlation energy functional, which encapsulates electron–electron interaction beyond the classical model. As its universal form remains undiscovered, approximated functionals constructed with heuristic approaches are used for practical studies. However, there are problems in their accuracy and transferability, while any systematic approach to improve them is yet obscure. In this study, we demonstrate that the functional can be systematically constructed using accurate density distributions and energies in reference molecules via machine learning. Surprisingly, a trial functional machine learned from only a few molecules is already applicable to hundreds of molecules comprising various first- and second-row elements with the same accuracy as the standard functionals. This is achieved by relating density and energy using a flexible feed-forward neural network, which allows us to take a functional derivative via the back-propagation algorithm. In addition, simply by introducing a nonlocal density denoscriptor, the nonlocal effect is included to improve accuracy, which has hitherto been impractical. Our approach thus will help enrich the DFT framework by utilizing the rapidly advancing machine-learning technique.

https://www.nature.com/articles/s41524-020-0310-0

xtb version 6.5.1 is out
* Fixes for Windows build (#629)
* Allow finding of installed test-drive dependencies (#633)
* Calculate number of electrons before restart (#638)
* Copy number of bonds for writing (#637)
* Declare optional arguments in C-API (#636)
* Fix MKL finding with Intel 2021 and newer (#640)
* Added rr-ho interpolation for heat capacity in thermo module (#644)
* Turn off GFN-FF fragmentation if it is not needed (#654)
* Make c-api example MSVC compatible (#648)
* Fixes Orca sanity check (#658)
* Resolve out-of-bounds access in ONIOM (#661)

https://github.com/grimme-lab/xtb/releases/tag/v6.5.1

Chemists change the bonds between atoms in a single molecule for the first time
https://phys.org/news/2022-07-chemists-bonds-atoms-molecule.html

Rational Density Functional Selection Using Game Theory

Theoretical chemistry has a paradox of choice due to the availability of a myriad of density functionals and basis sets. Traditionally, a particular density functional is chosen on the basis of the level of user expertise (i.e., subjective experiences). Herein we circumvent the user-centric selection procedure by describing a novel approach for objectively selecting a particular functional for a given application. We achieve this by employing game theory to identify optimal functional/basis set combinations. A three-player (accuracy, complexity, and similarity) game is devised, through which Nash equilibrium solutions can be obtained. This approach has the advantage that results can be systematically improved by enlarging the underlying knowledge base, and the deterministic selection procedure mathematically justifies the density functional and basis set selections.

https://pubs.acs.org/doi/10.1021/acs.jcim.7b00542