RF Diffusion now free and open source – Baker Lab
https://www.bakerlab.org/2023/03/30/rf-diffusion-now-free-and-open-source/

There is a new release of Quantum ESPRESSO

Exciting news for all Quantum ESPRESSO users! The latest version, 7.2, is now available with a range of new features, bug fixes and improvements.

QUANTUM ESPRESSO v.7.2 release notes: https://www.quantum-espresso.org/release-notes/release-notes-QE7-2.html

Webinar: Advancing Magnetic Memory Technology with Atomistic Modeling of Novel Materials & Concepts (April 26)
Join this free event on April 26 2023 to discover how experts from Martin-Luther-Universitat Halle Wittenberg and Synopsys QuantumATK use ab initio DFT modeling of MTJs to guide and accelerate the technological development of magnetic memory.

* Date: 26th April, 2023
* Time 1: 9 am CEST (Europe) / 12.30 pm IST (India) / 3 pm CST (China) / 4 pm KST (South Korea) / 4 pm JST (Japan)
* Time 2: 9 am PDT (US West Coast) / 12 pm EDT (US East Coast) / 6 pm CEST (Europe)
* Duration: 1 hour (including Q&A session)

Learn about:

- Investigating the potential of novel magnetic tunnel junction (MTJ) materials and concepts for improved magnetic memory performance.
- Generating realistic MTJ structures with Machine-Learned Force Fields.
- Evaluating the performance based on calculated MTJ spintronic properties, such as tunnel magnetoresistance (TMR), current rectification, spin-transfer torque (STT), Heisenberg exchange, Gilbert damping, and Curie temperature.

# Synopsys Webinar Speakers:

# Invited Speaker:
* Dr. Ersoy Sasioglu, Senior Research Scientist, Martin-Luther-Universitat Halle Wittenberg, Germany.
* Dr. Sasioglu will introduce a new MTJ concept based on novel half-metallic magnets and spin-gapless semiconducting Heusler compounds. The new MTJ concept exhibits a significant advantage due to the current rectification functionality and reconfigurable I-V characteristics, therefore showing potential for logic-in-memory computing. Proposed MTJ devices have been simulated with QuantumATK, realized experimentally, and patented.

# Synopsys Speaker:
* Dr. Troels Markussen, Manager R&D, Synopsys QuantumATK.
* Dr. Markussen will present a study of investigating different capping layer materials in a double spin-torque MTJ for STT-MRAM.

This Synopsys Webinar is the first one in the Synopsys Webinar Series on Advancing Magnetic Memory Technology with Atomistic Modeling.

The second Synopsys webinar "Advancing MRAM Technology with Atomistic Spin Dynamics Simulations" will take place on May 24, 2023. It will focus on simulating MTJs with the atomistic spin dynamics code Vampire. Invited speaker Dr. Richard Evans, Associate Professor, Developer of Vampire software, University of York, UK.

You are welcome to ask questions throughout the webinar or at the end during the Q&A session.
Contact us for more information at quantumatk@synopsys.com.

REGISTER: https://register.gotowebinar.com/#rt/9013806649862345305?source=psik-1

The Electron Is So Round That It’s Ruling Out New Particles | Quanta Magazine
https://www.quantamagazine.org/the-electron-is-so-round-that-its-ruling-out-new-particles-20230410/

Do you struggle understanding the number of roots to use on a CAS calculation? (You are not alone).
This paper explains how this works and even give a table for each electronic configuration:

📄 OPEN ACCESS - Assessment of minimal active space CASSCF-SO methods for calculation of atomic Slater–Condon and spin–orbit coupling parameters in d- and f-block ions (Dalton Trans., 2021,50, 14130-14138)

🔗 https://pubs.rsc.org/en/content/articlelanding/2021/DT/D1DT02346B

The original paper by Mulliken that is the foundation of Molecular Orbital Theory: Phys Rev 40, 55–62 (1932)

Scientists use computational modeling to design “ultrastable” materials | MIT News | Massachusetts Institute of Technology
https://news.mit.edu/2023/scientists-computational-modeling-design-ultrastable-materials-0404

X-rays reveal electronic details of nickel-based superconductors
https://phys.org/news/2023-04-x-rays-reveal-electronic-nickel-based-superconductors.html

A machine learning model for identifying new compounds to fight against global warming
https://phys.org/news/2023-04-machine-compounds-global.html

Heaviest Schrödinger cat achieved by putting a small crystal into a superposition of two oscillation states
https://phys.org/news/2023-04-heaviest-schrdinger-cat-small-crystal.html