Convenient access to bonded potentials in the GUI and possibility to edit all terms, including torsion potentials.New bonded OPLS potential for common electrolytes and OPLS-Min potential for use with custom charges and simpler type assignments.Improved move, measurement and atom wrapping tools.Improved plugin for adsorbing molecules onto a surface and a new nanoparticle builder for creating a nanoparticle electrode.Apply constraints and point defect symmetry to reduce the computational cost of defect diffusion simulations, e.g.Easier set-up of individual defect migration paths.Defect and dopant simulation improvements.Plot band edges in projected DOS, local DOS and projected local density of states analyzers.Part of the insightful electronic and vibrational analysis of systems with defects, amorphous materials, surfaces and interfaces, e.g., in HKMG and 3D-NAND memory stacks.New inverse participation ratio (IPR) analysis object to evaluate localized states.Accurate large-scale simulations of electronic properties orders of magnitude faster compared to HSE06-PlaneWave.Geometry optimization with stress and spin-polarization is now available with HSE06-LCAO.Available with LCAO basis sets for efficient large-scale simulations with modest hardware.HSE06-DDH method is based on using improved material-specific fractions of exact exchange, automatically calculated from density for each material (in an interface).HKMGs) structures comprised of multiple layers with different band gaps using the dielectric dependent hybrid HSE06 (HSE06-DDH) method. Fast and highly accurate electronic properties of materials, interfaces, and gate stack (e.g.Examples include amorphous HfO2 and GST phase-change materials, HKMG stacks, etc.Use ML MTPs for obtaining realistic crystalline, amorphous materials, interface, gate stack structures, simulating dopant diffusion, thermal transport, and crystallization.Use MTPs with MD, nudged elastic band and accelerated MD methods, such as force-bias Monte Carlo, now also with pressure control, to sample rare events and unlock slow mechanisms.Employ provided MTP potentials for Si or develop potentials for new materials and problems using automated training and simulation workflows.Obtain realistic amorphous material and liquid structures, in particular, at high temperatures.Active learning MTP simulations to automatically add DFT training data during molecular dynamics (MD) simulations.For cases where no conventional potentials exist or need better accuracy.One of the most accurate and efficient ML potentials on the market.Trained on a dataset of ab-initio calculations.100-1000x faster generation of realistic structures of complex multi-element crystalline, amorphous materials & interfaces, defect and dopant migration barriers, thermal transport, crystallization vs.

Quantumwise atomistix toolkit crack