Automate SIESTA DFT workflow creation, SCF setup, and geometry optimization on HPC.
npx skills add https://github.com/Hello-QM/catgo-LRG --skill siesta
Please help me install this Agent Skill. Skill: siesta Source: https://github.com/Hello-QM/catgo-LRG/tree/main/.claude/skills/siesta Command: npx skills add https://github.com/Hello-QM/catgo-LRG --skill siesta
Generate and manage SIESTA DFT calculations for NAO-based, linear-scaling, or user-requested runs.
Set up a SIESTA workflow on the HPC by providing the input template and pseudopotentials, then execute the calculation.
High-intent search queries and answers about installing and using this skill.
Automating SIESTA DFT calculations on an HPC cluster requires providing input templates and .psf or .psml pseudopotentials, then executing the run through CatGo's workflow engine, which manages SCF setups and geometry optimizations.
You need linear-scaling DFT for large systems when standard computational methods become too resource-intensive. The SIESTA workflow supports NAO-based linear-scaling scenarios specifically designed to handle these large-system calculations efficiently on HPC infrastructure.
Yes, running SIESTA workflows requires pseudopotentials in either .psf or .psml formats. Additionally, you must have SIESTA binaries installed on the HPC cluster and integrate with CatGo's workflow engine to execute the calculations properly.
The best way to set up SCF and geometry optimization in SIESTA is by using an automated workflow engine like CatGo. This approach handles the generation of input templates and manages the NAO-based DFT calculation steps from initial SCF setup through final geometry relaxation.
Yes, you can use NAO basis sets for user-requested SIESTA calculations. The workflow automation supports NAO-based DFT, allowing researchers to generate and manage tailored runs on an HPC cluster by supplying the appropriate pseudopotentials and input templates.
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