Stop polling, start reacting! 🛑
Tomorrow at 03:00 PM (UTC-3), I’m hosting a SouJava Live with @hectorvent. We’re diving into reactive systems and how to transform the way we interact with data persistence.
📺 Join us live on the SouJava YouTube channel: youtube.com/watch?v=iFNitm6y…#Java#ReactiveSystems#Backend#Database
Reactive Chemistry at Unrestricted Coupled Cluster Level: High-throughput Calculations for Training Machine Learning Potentials
1. A groundbreaking study by Allen et al. presents a novel approach to accurately model chemical reactions at the atomistic level using high-level electronic structure theory. The authors develop an automated workflow to create a dataset of gas-phase reactions with energies and forces calculated at the gold-standard level of unrestricted CCSD(T), overcoming previous computational challenges.
2. The study highlights the significant limitations of commonly used Density Functional Theory (DFT) in accurately describing reactive systems, particularly in bond breaking and making energetics. The new dataset provides a detailed analysis of the differences between DFT and unrestricted CCSD(T) descriptions across a wide range of chemical reactions.
3. A key innovation is the development of a transferable machine learning interatomic potential (MLIP) trained on the high-fidelity UCCSD(T) data. This MLIP demonstrates substantial improvements in force accuracy and activation energy reproduction compared to DFT-trained models, with over 0.1 eV/Å improvement in force accuracy and over 0.1 eV in activation energy.
4. The authors introduce practical adaptations for large-scale coupled cluster calculations, including basis set corrections for forces and strategies to identify and filter out problematic structures. These advancements enable the creation of a high-quality dataset containing over 3,000 configurations of organic molecules with up to 16 atoms.
5. The study employs active learning techniques to efficiently explore reactive space, starting from existing datasets and using methods like the dimer method, NEB, and SEGS to generate new structures. This approach ensures that the dataset captures a diverse range of chemical reactions and geometries.
6. The MLIP trained on UCCSD(T) data not only outperforms DFT-trained models but also shows improved performance over DFT calculations themselves in several cases. This highlights the potential of MLIPs to revolutionize reactive simulations by offering both high accuracy and computational efficiency.
7. The authors emphasize the importance of robust and efficient quantum chemistry software for creating highly accurate datasets at the CCSD(T) level. They suggest that future work could focus on expanding these techniques to the condensed phase and developing automated approaches for multi-reference calculations.
📜Paper: arxiv.org/abs/2509.10872v1#ComputationalChemistry#MachineLearning#QuantumChemistry#ReactiveSystems#HighThroughputCalculations
The end of the year was so intense that I almost forgot to express my gratitude to BR-BIT (especially to Leonildo V., Marlon B., and Alan R.) for the opportunity to contribute to their initiatives.
BR-BIT is modernizing its solutions by building a distributed, scalable platform designed to become a market differentiator for prison systems in Brazil. Over a four-day workshop, we explored several aspects of distributed reactive systems, fostering rich discussions and strategic insights.
Thank you for the collaboration and for trusting me to be part of this journey.
Looking forward to seeing the impact of these initiatives!
#ReactiveDDD#ReactiveSystems#DistributedSystems#EventDriven#EventSourcing#CQRS#DomainDrivenDesign#DDDesign#Microservices
It is fascinating how the community around reactive systems is evolving. I want to thank Sam Hatoum and Raf Lefever for their significant contribution (which helped me explain the event-sourced systems).
"Investing in scale and real reliability can be made at various system levels. Much of this is seen at the edge, especially in the infrastructure, by combining different tools or explicitly relying on a specific capability to solve a business problem (vendor lock-in). However, another plausible alternative is incorporating these characteristics into the application's nature (behavior over state)."
TAR represents a paradigm shift, without a doubt. As with any paradigm shift, considerable resistance is likely, which is to be expected. However, a reactive system inherently achieves greater efficiency by optimizing the interactions between its components, regardless of whether they are distributed (tell, don't ask).
Image credit: Sam Hatoum
#EventSourcing#EventDriven#ReactiveSystems#DistributedSystems#ReactiveDDD#CQRS
In this session with @sascha242, you learn how users adopt reactive patterns for their high-performance applications and have a look at typical, well-architected implementations on #AWS. Join #SAGconf now and learn about the building of #reactivesystems: ow.ly/D1DI50GhMnk
Getting in the topic of #reactivesystems before our panel discussion - 📺 watch a talk by @pdolega, @lukasz_bialy & Marcin Zagórski.
👉 Beyond the hype: reactive vs traditional microservices 👉 bit.ly/2Sr6v4f