February 2026 monthly summary focused on advancing platform integration, stabilizing the CI/testing pipeline, and preparing for a formal release. Delivered concrete platform expansion, improved test reliability, clarified user guidance, and established release readiness for the 1.2.x line, contributing to shorter cycle times and stronger product stability.

January 2026 monthly summary for Quantum-Accelerators/quacc and FAIR-Chem/fairchem focused on version governance, reliability hardening, and configurability improvements across key VASP workflows. Delivered sequential version bumps across the quacc release series (1.1.2 → 1.1.3 → 1.1.4 → 1.1.5) and companion progression of TorchSim/TochSim-related releases to 1.1.7, with a PyMatGen update to 2025.10.7. Changelog maintenance ensured accurate, consistent release notes for 1.1.4–1.1.5 and related changes. Major reliability/workflow hygiene improvements include hardened Custodian error folder handling, robust Jobflow I/O behavior, and bug fixes in data preparation and adsorption handling. A new VASP configurability flag (pp_version) was added to FAIR-Chem/fairchem input sets to explicitly specify pseudopotential versions, improving reproducibility. This work strengthens automation, reduces pipeline risk, and accelerates user adoption of the latest release, while laying groundwork for upcoming tutorials and schema updates.

December 2025 (Quantum-Accelerators/quacc): Delivered a targeted set of environment, release, and reliability improvements that enhance stability, onboarding, and developer velocity. Key outcomes include a project-wide Python/environment upgrade, disciplined release hygiene, and reliability improvements across VASP parameter handling and testing. Documentation and compatibility notes were expanded to support static calculations and datasets, with clearer guidance for pseudopotentials. CI tooling enhancements and observability improvements were introduced, including pre-commit CI triggers and INFO-level logging for VASP pseudos with corresponding tests. Covalent support was removed to reduce maintenance surface. Collectively, these efforts improve stability, traceability, and time-to-value for users and contributors.

Monthly Summary for 2025-11 (Quantum-Accelerators/quacc) Overall focus: deliver reliable, scalable features and maintainability enhancements that unlock business value through improved workflow reliability, compatibility, and developer experience. Highlights include new input handling capabilities for VASP workflows, targeted bug fixes in phonon workflow deserialization, and infrastructure upgrades that reduce maintenance overhead and accelerate adoption of upcoming atomate2 integrations. Key features delivered (business value): - VASP input handling enhancements: added a dedicated path to convert VASP input generators to VaspInputSet for better compatibility with atomate2 integration and MPtoASEConverter improvements, enabling more robust, scalable automation for materials workflows. - Static OMat recipe for fairchem: introduced a static OMat recipe to enable static calculations with materials-science-oriented settings, expanding the repertoire of ready-to-run analyses. - Clear setup messaging for atomate2: improved user setup experience by clarifying installation steps for the atomate2 dependency, reducing onboarding time and support overhead. - Maintenance and infrastructure updates: consolidated maintenance changes including dependency bumps, CI/workflow improvements, test configuration tweaks, and documentation tooling upgrades to improve reliability and consistency across the project. Major bugs fixed: - Phonon workflow deserialization bug: fixed (de)serialization by avoiding passing the Phonopy object directly to a @job-decorated function, improving stability of phonon-related workflows and unit tests. Overall impact and accomplishments: - Improved reliability and scalability of core workflows, with stronger integration support for atomate2 and related tooling, enabling researchers to run larger, more complex simulations with fewer failures. - Reduced friction for contributors and users through clearer setup guidance and maintained CI/test infrastructure, supporting faster iteration and higher code quality. Technologies/skills demonstrated: - Python, VASP workflow tooling, Phonopy, VaspInputGenerator, VaspInputSet, atomate2 integration, MPtoASEConverter, OMat, fairchem, CI/CD, dependency management, unit testing.

October 2025 was focused on delivering stability, usability, and documentation improvements across two repositories (Quantum-Accelerators/quacc and FAIR-Chem/fairchem), with a measurable emphasis on reliability for high-throughput workflows and developer experience. Key features and improvements were shipped for VASP/Custodian integration, VASP parameter handling, and YAML/configuration workflows, complemented by CI/versioning updates and linting refinements. Notable outcomes include enhanced convergence handling for gradient data, updated default symmetry precision to promote stable calculations, and a more flexible VASP parameter management model. Documentation and remote jobflow YAML corrections improve reproducibility and onboarding. A targeted bug fix in FAIR-Chem corrected the ORCA script path reference to ensure reproducible results. Overall, these efforts reduce runtime failures, streamline configuration, and accelerate delivery of research workflows.

In September 2025, Quantum-Accelerators/quacc delivered robust VASP parameter handling and algorithm improvements, expanded the feature set, improved code quality, and enhanced packaging and documentation. The work prioritized reliability, maintainability, and clear release readiness to accelerate users' scientific workflows and reduce operational friction.

Month: 2025-08 | Quantum-Accelerators/quacc — concise monthly summary focused on business value, technical achievements, and impact. Key features delivered: - MP sets updated for MP24: Updated MP recipes to match MP24 settings, enabling accurate MP simulations and reproducibility; closes issue #2019. (Commit: a191e6780fce160c7cb1d7163b17e27bf3edcamed) - Add D3(BJ) parameters for HSE06: Extends functional parameterization to improve accuracy for HSE06 calculations. (Commit: 76a3b83bfa75f2670556bf96369998ee8af8acd4) - Build/configuration centralization: Consolidated updates to pyproject.toml across changes, improving packaging and consistency; supports newtonnet and downstream tooling. (Commits: 572223222674d23f36b0bfd41eafbdf1ae1a9b26; 47e6043f400ad7c3a27d4bbaefb666249d228882; 37bc10b96a2b4ee36ea3041bd81f9a6d186dd303) - Documentation expansion: Updated executors and wflow engines docs to streamline onboarding and usage. (Commits: fd09ece2cfc981da910307d0704e959fa8b7955e; 070f736953fb51338a3859b529c7c6022ec6372a; d5b2da42669603cb3656683effe0220e93771734; b21ed4490491f5f5fb04d91d2fe2ae4cf74bbc14) - Changelog and version discipline: Updated CHANGELOG and versioning across releases, clarifying changes for 1.0.x stream. (Commits: 976a749730312d609bbaf65664e5c852c5e1ae2e; 1e934cd780b9e7fabbd049d0813a3d59071af060; 4b476ad8f0b858904688dae13d800bcd1076d316; 5fb11de2f89f44dd382d452e9409dd5583b4ff71; 05a0e0e1ce0e7b69eb108099eaabf383ebe98ed0; a48d28590275d857313c8990b2417399c00643e7; 3c2ca5675b44371f9911639eb9e495dcfab7d899) - Default algorithms and set naming: Introduced default Fast algorithm and renamed DefaultSetPBE to DefaultSetGGA with new DefaultSetMetaGGA and DefaultSetHybrid for clarity and performance. (Commits: 1478fca70cfafcad611dd118f7df59a10aa1010d; 4d435dc2a1c6c9b32357e5bb5d7ba23daec5175a) - MP converter robustness and dependencies: Increased robustness of MP converter; updated Matgl dependency to GitHub source; updated typing hints; added legacy MP recipes back to preserve compatibility. (Commits: 409531c1a3ceac233844d2c507acba0751b06561; f4f8a303d35ae52d1f3ebf4f685f0c0f77c40e9e; e3c56da0d57458a4df7f834c090f13ea8e946b00; 28613b65af9fcc38b3400ef26e1d7f8df31ea9ba) Major bugs fixed: - Remove unused code: Cleaned up dead paths to simplify maintenance and reduce surface area. (Commit: 108e56c527ec396cc3afbb1d37a766ad9423b5ed) - O2 not triplet warning: Added warning when O2 is not triplet to prevent misconfigurations. (Commit: 52f8060a7e0ca5082d398529cd544f339bde1a90) - Monty copy_r deprecation: Replaced deprecated copy_r usage to maintain compatibility with newer Monty versions. (Commit: 99588012e543d630b9909dc57fccd782d14aa2e7) - Testing infrastructure: Re-enabled Windows tests and added Python 3.13 test support to broaden CI coverage. (Commits: 2c00c6267628dbda07e2ebacc530914345411ca9; 3850599d6c8130b850de358344e549b647333925; ca2995ab1416ca8620d01f3169313305deb5e02c) - Dependency hygiene: Removed maggma as a core dep; updated Custodian lower bound. (Commits: 8912854f6b9f80e1f924eb1dcaebf4fb384a6955; 384ad9a5807cbabc3fef52eeb8b7539fabdeb4dc) Overall impact and accomplishments: - Improved accuracy, reliability, and maintainability of the quacc stack, enabling faster, reproducible MP calculations and HSE06 workflows for customers. - Strengthened CI, packaging, and release discipline, reducing onboarding time and version drift across environments. - Delivered a clearer default behavior and naming scheme to help users select optimal configurations with minimal guesswork. Technologies/skills demonstrated: - Python, packaging and dependency management (pyproject.toml), CI/test automation across Windows and Python 3.13 - Scientific software workflows (MP, D3(BJ) parameters, VASP input sets) - Documentation best practices and changelog governance - YAML configuration management ( RosenSet.yaml, QMOFSet.yaml )

July 2025 (2025-07) performance snapshot for Quantum-Accelerators/quacc. Key delivery focused on expanding fast-config capabilities, strengthening result reliability, and improving maintainability through CI and documentation work.

June 2025 monthly summary for Quantum-Accelerators/quacc: Delivered a set of feature-focused improvements, reliability hardening, and release/documentation work that collectively increase accuracy, stability, and deployment readiness. Highlights include accuracy-driven algorithm switching and tighter integration with external tools, along with a consolidated release process and improved developer docs.

May 2025 (2025-05) monthly summary for Quantum-Accelerators/quacc: Delivered significant build/config improvements, new capabilities, and a series of critical bug fixes, driving reliability, performance, and scalability for simulation workflows. Key features delivered include build/config maintenance, VASP command checks, RosenSets enhancements, and FAIR chem v2 integration, complemented by updated dependencies and thorough documentation. Major bugs addressed improved input processing accuracy and stability, including k-points parsing, reciprocal-unit KPOINTS, and reverting Fairchem v2 to restore compatibility.

April 2025 performance snapshot across Quantum-Accelerators/quacc and PrefectHQ/prefect, delivering high-impact features, stabilizing core results, and strengthening data governance and release readiness. Key efficiencies gained include more robust result typing, configurable optimization, and deterministic persistence flows, enabling faster scientific cycles and clearer governance for production workflows.

Concise March 2025 monthly summary for two active repositories (Quantum-Accelerators/quacc and FAIR-Chem/fairchem). Delivered end-to-end features, stability improvements, and documentation updates with a clear focus on business value, maintainability, and reproducibility.

February 2025 — Delivered a set of targeted features and bug fixes across Quantum-Accelerators/quacc. Key features: LELF handling corrections including a correctness fix and reduced verbosity; NCORE handling improvements; VASP integration updates via vasp.py; r2SCAN parameterization with automatic D4 and a D4 handling fix. Supporting work: extensive pyproject.toml/configuration updates, CHANGELOG/test schema updates, HPC test script enhancements, and documentation updates (codes.md, wflow_engines, CHANGELOG). Major bugs fixed: incorrect LELF handling and D4 handling in r2SCAN. Overall impact: enhanced correctness, stability, and maintainability, enabling faster scientific experimentation and more reliable builds. Technologies demonstrated: Python code improvements, build/config tooling (pyproject.toml, dependencies, CI YAML), HPC scripting, testing, and documentation.

January 2025 (2025-01) — Quantum-Accelerators/quacc: Focused on stability, compatibility, and release-readiness through targeted core-workflow improvements, test-automation enhancements, and comprehensive configuration/documentation maintenance. Key features were delivered with minimal disruption to existing users, while major bugs were resolved to reduce CI failures and improve reliability. These efforts position the project for smoother releases and easier onboarding for new contributors. Overview of work: - Key features delivered - Major bugs fixed - Overall impact and accomplishments - Technologies/skills demonstrated

December 2024 highlights for Quantum-Accelerators/quacc: Expanded model versatility and improved conversion stability to accelerate user adoption and reduce maintenance overhead. Key features include MLP Model Compatibility Expansion adding SevenNet and Orb models as MLPs with accompanying license access notes and release notes updates; robustness fixes to MPtoASEConverter, addressing None inputs, enforcing atom sorting, and correcting DFT+U parameter handling for MP-derived atoms; and ASE 3.24.0+ compatibility with release lifecycle updates, including dependency bumps and synchronized versioning (0.11.9/0.11.10). These changes collectively enhance integration with downstream workflows, improve data integrity in atom-to-ASE conversions, and streamline future releases.