Synopsys QuantumATK X-2025.06

Description

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QuantumATK X‑2025.06 – Cutting-Edge Atomic-Scale Simulation Software by Synopsys

Elevate your materials research, nanotechnology, and electronic device modeling with QuantumATK X‑2025.06, the latest and most powerful release from Synopsys. QuantumATK is a comprehensive atomic-scale simulation platform that combines density functional theory (DFT), semi-empirical methods, and machine-learned potentials (MLPs) to provide highly accurate, scalable, and efficient simulations for complex material systems.

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Key Features and Highlights

• High-Performance GPU & CPU Acceleration: Run DFT and semi-empirical simulations up to 10× faster with optimized multi-node and multi-GPU support, dramatically reducing computation time for large-scale simulations.

• Advanced Machine-Learned Potentials: Seamlessly train and apply MACE, DeepMD, ORB, SevenNet, and CHGNet models for precise simulations of large systems. Supports simulations up to 1 million atoms, enabling studies of realistic material properties.

• Accelerated Simulation Methods: Utilize Accelerated Collective Variable Hyperdynamics (CVHD) and Adaptive Kinetic Monte Carlo (AKMC) techniques for efficient modeling of room-temperature diffusion, reaction kinetics, and rare events.

• Enhanced NEB and Transition State Calculations: Optimized Nudged Elastic Band (NEB) methods and Dimer/Lanczos integrations offer 2–3× faster reaction path optimization, improving reliability for complex chemical and material reactions.

• Surface Process and 2D Material Simulations: Accurately simulate complex substrates including U-shaped surfaces and advanced 2D materials. Variable time-step molecular dynamics ensures realistic modeling of impact and deposition processes.

• Improved Geometry Optimization & PDOS Calculations: Optimized algorithms provide faster and more accurate calculations for SCF, geometry optimization, PDOS, FatBandstructure, and MAE analysis.

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System Requirements

• Operating Systems: Windows 10/11, Ubuntu Linux 20.04+, CentOS 8 or newer

• Hardware Recommendations: Multi-core CPU (8+ cores), NVIDIA GPU with CUDA 11+, 16 GB RAM minimum, SSD storage for large datasets

• Software Dependencies: Python 3.9+, MPI libraries for parallel execution

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Bug Fixes and Stability Enhancements

• Resolved SCF convergence issues for large supercells, ensuring reliable electronic structure calculations.

• Fixed memory leaks in PDOS, FatBandstructure, and MAE modules for improved performance.

• Optimized geometry optimization stability for MetaGGA and GGA+U methods, reducing simulation errors.

• Enhanced NEB and transition state search stability, ensuring accurate reaction path modeling.

• Addressed minor interface and scripting issues to improve user workflow efficiency.

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Release Name: QuantumATK X-2025.06

• Release Type: Feature release (the “X” designation), representing the latest major version.

• Highlights of the X-2025.06 update include:

  • Substantial GPU acceleration for DFT and semi-empirical calculations (over 10× speed-up in key performance metrics like SCF, bandstructure, PDOS, PLDOS, and transmission spectrum), including support for multi-node and multi-GPU scaling.

  • Major CPU performance enhancements: ~2× faster SCF and geometry optimizations using MetaGGA, GGA, Hubbard U; up to ~5× faster PDOS, FatBandstructure, and MAE analysis.

  • Enhanced support for machine-learned potentials (MLPs), including training frameworks for MACE models, interfaces to DeepMD, ORB, SevenNet, CHGNet, and multi-GPU acceleration enabling large-scale simulations (e.g., 100,000 atoms with MACE, 1,000,000 atoms with MTPs).

  • New simulation methods for room-temperature diffusion: Accelerated Collective Variable Hyperdynamics (CVHD) and Adaptive Kinetic Monte Carlo (AKMC) with Lanczos and ARTn methods.

  • Improvements to surface process simulations, including support for complex substrate shapes (like U-shaped or 2D materials), and variable time-step MD for accurate modeling of impact processes.

  • Upgraded Nudged Elastic Band (NEB) method with sequential IDDP setup, faster reaction path optimization, and 2–3× faster transition state searches when combined with Dimer and Lanczos techniques.

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QuantumATK X‑2025.06 empowers scientists, engineers, and researchers in materials science, electronics, nanotechnology, and chemistry to perform fast, scalable, and reliable atomic-scale simulations. With its advanced GPU acceleration, machine-learned potential support, and state-of-the-art simulation methods, it is the ideal solution for tackling complex materials and device modeling challenges while significantly reducing computational time.

Experience the next generation of atomic-scale simulation with QuantumATK X‑2025.06 and unlock the full potential of your research.

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⭐️⭐️⭐️⭐️⭐️5/5

*”As a materials scientist and developer working extensively with atomic-scale simulation software, I have found QuantumATK X‑2025.06 to be an indispensable tool for my research. The combination of DFT, semi-empirical methods, and machine-learned potentials (MLPs) allows me to model complex materials and nanostructures with unparalleled accuracy and efficiency. The GPU and CPU acceleration significantly reduces computation times, even for large-scale systems with tens of thousands of atoms.

The enhanced NEB and transition state calculations, along with advanced surface process simulation capabilities, make studying reaction pathways and 2D materials much more straightforward. I also appreciate the stability improvements and bug fixes in this release, which ensure reliable SCF convergence and smooth workflow integration.

QuantumATK X‑2025.06 is ideal for materials science, nanotechnology, and electronic device modeling, delivering fast, scalable, and highly accurate simulations. I highly recommend it to any researcher or engineer looking for a robust, professional-grade atomic-scale simulation platform.”*