Download QuantumATK Y-2026.03 + license
QuantumATK Nanolab Y-2026.03 full crack license download, latest version of the QuantumATK atomic-scale modeling platform or virtual nanolab includes many new exciting features and performance improvements for chemist. For advanced semiconductor technology development application for materials development application. We have completely cracked both Linux and Windows versions.
Key Features and Applications of QuantumATK NanoLab software
- Atomic and Molecular Modeling: Ability to create and simulate complex atomic and molecular structures.
- Electronic and Transport Properties Calculations: Supports density functional theory (DFT) calculations to investigate the electronic properties of materials.
- Development of new materials: To develop materials with specific electronic, mechanical or optical properties.
- Semiconductor Device Simulation: Allows simulation of semiconductor devices such as transistors and solar cells.
- Supports various environments: QuantumATK is used in various environments such as academic, industrial, and commercial research.
- Use of Python scripting: QuantumATK software provides the ability to execute Python scripts, which allows you to automate complex and computational processes.
- Advanced Data Analysis: Using QuantumATK’s advanced data analysis tools, you can investigate various material properties more accurately, such as electronic, mechanical, thermal, etc.
- Design of semiconductor devices: Simulation of electronic devices at the atomic level to improve performance and efficiency.
- Research in nanotechnology: Investigation and design of nanoscale structures and nanomaterials.
- Multiple simulation methods in one platform
- Multiphysics: electronic, optical, mechanical, thermal
- Integration with TCAD
- Fast customized and novel solutions
Some of the QuantumATK Calculators
- DFT LCAO: Simulation engine for density functional theory (DFT) using pseudo-potentials and linear combinations of atomic orbitals (LCAO) basis sets.
- NEGF: Module for nanoscale device and transport simulations using non-equilibrium Green’s function (NEGF) methodology.
- Surface NEGF: Module for modeling of surfaces beyond the slab approximation. Allows for treating electro-chemical reactions and surface states. Uses either DFT-LCAO.
- DFT Plane Wave: Simulation engine for DFT using pseudo-potentials and plane-wave basis sets.
- Semi Empirical: Semi-empirical simulation engine using DFTB, extended Hückel, Slater-Koster, and other tight-binding models.
- Force Field: Simulation engine for atomic-scale simulations (e.g. molecular dynamics) using classical potentials such as bonded and reactive force fields.
- ML Force Fields: Machine-Learned Force Fields providing near-ab initio accuracy for large realistic system sizes and dynamical simulation time-scales greatly exceeding those accessible to Density Functional Theory (DFT).
What’s New in QuantumATK V-2023.09 (Highlights)
Machine-Learned Force Field Training
- Enhanced ease-of-use of training ML FFs with new predefined Workflow Builder blocks for
- active learning simulations and training sets.
- New ML-FF training template for defect structures.
Process Simulations
- Accelerated molecular dynamics for crystallization.
- Thermochemistry pyrolysis to predict gas phase composition in surface processing.
- Integrated workflow and analysis of charged point defects and defect diffusion.
Interface Modeling
- New interactive Interfaces Builder for multilayer structures.
- High-k Metal Gate (HKMG) and Magnetoresistive RAM (MRAM) Builders as Workflow
- Builder blocks can be part of simulation workflows.
- New Projected Phonon DOS analysis.
Device Channel Material Design
- Major speedup in bandstructure simulations with Semi-Empirical Tight-Binding models for up to million atoms.
- Efficient and simplified deformation potential extraction for large nanostructures to evaluate electron-phonon coupling.
Nanodevice Modeling
- New analysis of spectral and thermal current and conductance in Transmission Analyzer.
- More interactive IV Characteristics Analyzer and possibility to analyze inelastic current.
STT-MRAM Memory Design
- New Finite Bias Spin Transfer Torque (STT) Study Object and Analyzer to evaluate the write performance of STT-MRAM.
- New Heisenberg Exchange Analyzer for exchange couplings and Curie temperature.
What’s New in QuantumATK W-2024.09 (Highlights)
Many-Body Perturbation Theory GW Advancements
- 10x memory reduction and large speed-up due to the new parallelization strategy.
- Enabled very accurate G0W0 calculations of electronic structure properties at a moderate computational cost for molecules, 2D, 3D systems and interfaces with hundreds of atoms.
- Added support for polarized spin, noncollinear spin and spin-orbit.
DFT & Semi-Empirical Model Improvements
- New finite difference linear response method for automatic ab initio extraction of Hubbard U parameters in DFT+U.
- New Local TB09 MGGA DFT functional with automatic calculation of material specific and position dependent c-parameters in bulk semiconductor and insulator materials and interfaces.
- New SiGe tight-binding model with strain corrections.
Machine-Learned Force Field Enhancements
- Pretrained universal Neural Network MACE-MP (new) and M3GNet potentials can now simulate bulk materials, devices, slabs and molecules for rapid exploration of new applications.
- 10-15x faster fitting of accurate and efficient Moment Tensor Potentials (MTPs).
- Up to 2x more accurate MTPs for complex multi-element systems in machine learning.
Ion Dynamics Improvements
- New quasi-harmonic free energy optimization and thermodynamic integration methods for obtaining solid and liquid phase diagrams.
- Two new semi-grand canonical Monte Carlo methods for simulating thermodynamics and composition of miscible and immiscible alloys.
- New Gruneneisen coefficient study object to predict the thermal conductivity and expansion coefficient of solids.
Defects & Surface Process Simulation Updates
- Extended defect analysis framework to include trap levels residing at interfaces between different materials.
- New real space self-energy method for obtaining PDOS of single defects in an infinite crystal using open boundary conditions.
- New gas phase decomposition analysis module including reaction kinetics to guide selection of precursor gas molecules and thus growth in CVD or ALD.
NanoLab GUI Advancements
- Enabled generation of multiple initial amorphous structures and NEB paths at once.
- More convenient way to set up various hook functions in MD and TFMC simulations: pre-step (e.g., strain), post-step (e.g., Plumed metadynamics, steered MD) & measure hooks (e.g., error prediction analysis in MD simulations with MTPs).
- New array jobs feature to efficiently setup, run & gather data for many similar simulations iterated over configurations, NEBs, and calculator settings.
Synopsys QuantumATK X-2025.06 Release Notes
GPU Acceleration of DFT and Semi-Empirical
- On average 10x+ speed-up of the most time-consuming parts of bulk and NEGF device calculations, including SCF, bandstructure, PDOS, PLDOS, and transmission spectrum.
- Support for multi-node and multi-GPU with linear acceleration with the number of GPUs.
- Shifting the run-time for 5,000 atoms with DFT or 30,000 atoms with Semi-Empirical NEGF from days to just a few hours.
DFT Performance Improvements on CPU
- ~2x speed-up for all SCF & geometry optimization with MetaGGA, GGA, and Hubbard U for small/medium system sizes (a few hundred atoms).
- Up to ~5x faster PDOS, FatBandstructure and MAE analysis, with speed-up increasing with the number of projections.
Broader Machine-Learned Potentials (MLP) Support
- Framework for training new and fine-tuning universal MACE models for a specific system/process with improved accuracy.
- Interface for import, rapid testing and usage of emerging MLP models, based on DeepMD, ORB, SevenNet, MACE, CHGNet, etc.
- Multi-GPU acceleration of MLPs enables large scale MD simulations, e.g. 100,000 atoms with MACE and 1,000,000 atoms with MTPs.
Room-Temperature Diffusion
- New methods for simulating room-temperature diffusion and extracting diffusion coefficients:
- Accelerated Collective Variable Hyperdynamics (CVHD) gives up to 300x speed-up over standard MD to capture rare events.
- Adaptive Kinetic Monte Carlo (AKMC) with new Lanczos and ARTn saddle search methods iteratively probes new states, possible transitions, and energy barriers between them.
Surface Process Simulation Improvements
- Support for complex substrate shapes, such as U-shaped and 2D materials, in deposition/etching processes.
- MD simulations with variable time-step for accurate modeling of impact surface processes without having to use a small time-step for the entire simulation.
Improved NEB Method for Reaction Barriers
- New sequential IDDP method for setting up complex reaction paths in NEB.
- New techniques to improve and speed-up NEB reaction path optimization.
- 2-3x faster refinement of transition state search and reaction barrier calculations when combining NEB with new Dimer and Lanczos methods for saddle point search.
What’s New in QuantumATK Y-2026.03 (Highlights)
The QuantumATK Y-2026.03 release introduces a wide range of innovations focused on performance, scalability, usability, and advanced modeling capabilities.
1. High-Performance Computing (HPC) Optimization
- Improved parallel scaling across multi-core CPUs and clusters
- Enhanced GPU acceleration (CUDA-enabled) for key solvers
- Optimized memory usage for simulations involving thousands of atoms
- More efficient job distribution for large research environments
2. Breakthrough Quantum Transport Improvements
- Upgraded NEGF (Non-Equilibrium Green’s Function) algorithms
- Improved stability for device simulations under bias conditions
- Enhanced modeling of 2D materials, tunneling devices, and nanoscale transistors
- Faster simulation of electron transport in realistic device geometries
3. Advanced Quantum Mechanics Enhancements
- Improved DFT solvers with enhanced convergence stability for complex systems
- Expanded support for hybrid and meta-GGA exchange-correlation functionals
- More accurate band structure and density of states calculations
- Enhanced treatment of spin-polarized and magnetic systems
4. Unified Multi-Scale Simulation Environment
QuantumATK integrates multiple simulation approaches within a single environment:
- Quantum mechanical simulations (DFT)
- Semi-empirical methods (Slater-Koster, Tight-Binding)
- Classical atomistic simulations (Molecular Dynamics)
This allows seamless transitions from atomic-scale physics to device-level modeling, reducing the need to use multiple software tools.
5. Performance & Efficiency Improvements
QuantumATK Y-2026.03 delivers significant performance and efficiency improvements, including:
- Faster self-consistent field (SCF) convergence
- Reduced computational time for large-scale DFT simulations
- Lower memory consumption for complex systems
- Improved data handling and faster read/write operations
- Enhanced restart capabilities for long-running simulations
6. AI & Machine Learning Integration
QuantumATK Y-2026.03 introduces emerging capabilities for machine learning and data-driven simulations:
- Early-stage support for machine learning interatomic potentials
- Accelerated simulation workflows using data-driven models
- Reduced computational cost for large-scale molecular systems
7. Next-Generation NanoLab Interface
- Redesigned NanoLab GUI with improved usability
- Faster project handling and visualization
- Smart automation tools for repetitive workflows
- Built-in scripting environment using the Python API
8. Detailed New Features & Functional Upgrades
- Automated Workflow Builder
- Create, manage, and reuse complex simulation pipelines with minimal manual intervention.
- Enhanced Materials Database Integration
- Quickly access and import validated material structures and properties.
- Improved Geometry Optimization Algorithms
- Faster relaxation of atomic structures with improved numerical stability.
- Advanced Phonon & Vibrational Analysis Tools
- Provides deeper insights into the thermal and mechanical properties of materials.
- Expanded Visualization Capabilities
- High-quality rendering of atomic structures, electron densities, and device geometries.
- Better API Extensibility
- Advanced Python scripting capabilities for custom workflows, automation, and integration with external pipelines.
9. Bug Fixes & Stability Enhancements
This release places a strong focus on robustness and reliability:
- Fixed rare convergence instabilities in advanced DFT calculations
- Resolved NanoLab crashes during intensive visualization tasks
- Improved compatibility with latest Linux distributions and compilers
- Eliminated memory leaks in long-running batch simulations
- Enhanced MPI stability for distributed computing environments
- Improved error messages and debugging tools
Core Highlights
QuantumATK Y-2026.03 combines improvements across quantum mechanics, quantum transport, machine learning, HPC, visualization, and workflow automation, providing a more powerful and efficient environment for advanced atomic-scale and device-level simulations.
QuantumATK W-2024.09 + license
QuantumATK X-2025.06 + license
QuantumATK Y-2026.03 + license
Details of QuantumATK software
- Operating System: Windows (Download Linux Version)
- Crack: Full Version
- Active: With licence
- Licence Type: Single User for 1 PC
- File Size: 2.52 GB + 3.75 GB
- License validity: Permanent and perpetual
Comments