The ASAP (Atomistic Simulation Advanced Platform) software package is a product of SIMUNE

ASAP HTEP (High Throughput Electronic Properties) A set of robust workflows for screening new materials, offering batch job management and analysis capabilities. With a powerful structure builder for constructing, visualising and manipulating 1D, 2D and 3D materials. ASAP HTEP is especially useful for molecular electronics, enabling easy computation and comparison of electronic properties across a set of molecules, including charge, HOMO and LUMO energy levels.

ASAP Pro Containing all the features of HTEP, ASAP Pro comes with additional functionalities, such as an extended range of project types and a broader set of analysis tools. AI-supported ASAP Pro workflows are designed to enhance the user experience in material design for numerous applications, including automotive, electronic and chemical industries, energy applications as well as biological and pharmaceutical applications.

ASAP Pro Transport A collection of additional automated workflows for ASAP Pro, specifically designed to compute and analyse electronic nanotransport using the DFT+NEGF formalism.

The Transport package incorporates a device builder for constructing electrodes of various shapes and cross-sections, as well as buffer and scattering regions. This set of workflows automates the device geometry optimisation, as well as the construction and visualisation of the planar and macro-average electrostatic potential across the device. Additionally, they facilitate the visualisation of the transmission function for bulk electrodes, providing spin-resolved plots for transmission and current. This includes spin difference and spin sum plots.

In Tables Table 1 and Table 2, we present an overview of the structure builder features and the type of projects (workflows) implemented in ASAP HTPE, ASAP Pro and ASAP Transport. Table Table 3 provides an overview of the main material properties whose calculations are automated within the various ASAP modules.

Table 1 Overview of the structure builder features implemented in the different ASAP modules. See Chapter The atomic structure builder for further information on ASAP structure builder.

Table 2 Overview of the type of projects integrated in the different ASAP modules.

Table 3 An overview of the main material properties whose calculations are automated within the ASAP subproducts.

Introduction — ASAP User Manual 2024.0 documentation (simuneatomistics.com)

About ASAP

We have developed ASAP in Python 3. It is compatible with Python ≥ 3.6. We use the Python library PySide2 (binding of the GUI toolkit Qt) for GUI rendering. The other main packages and libraries ASAP relies on are:

• The Atomic Simulation Environment, aka ASE (https://wiki.fysik.dtu.dk/ase)
• SciPy (https://scipy.org/)
• Matplotlib (https://matplotlib.org/)

We have implemented a user-friendly graphical user interface designed to help the user in preparing the input file for the selected calculator. ASAP can interface with SIESTA code as well as with the Quantum Espresso computer code.

The SIESTA calculator has been tested on various platforms, including Windows 10 (version 1903 and onwards), Linux distribution (Debian, Ubuntu, CentOS), as well as macOS X versions High Sierra, Yosemite, and Catalina.

If you are preparing an article using ASAP, please include following acknowledgment in your manuscript:

“These studies were performed using some results obtained with the ASAP-YYYY.N (Atomistic Simulation Advanced Platform).”

Here YYYY is the 4-digit representation of the year and N the release index for that year, as for example ASAP-2023.1.

Please find below the references to methodology and software papers:

• E. Artacho, D. Sánchez‐Portal, P. Ordejón, A. García, and J. M. Soler, Linear‐Scaling ab‐initio Calculations for Large and Complex Systems, Phys. Status Solidi B 215, 809 (1999).
• J. M. Soler, E. Artacho, J. D. Gale, A. García, J. Junquera, P. Ordejón and D. Sánchez-Portal, The SIESTA method for ab initio order-N materials simulation J. Phys. Condens. Matter 14, 11, (2002)
• E. Artacho, E. Anglada, O. Diéguez, J. D. Gale, A. García, J. Junquera, R. M. Martin, P. Ordejón, J. M. Pruneda, D. Sánchez-Portal and J. M. Soler, The SIESTA method; developments and applicability, J. Phys. Condens. Matter 20, 064208, (2008).
• A. H. Larsen, J. J. Mortensen, J. Blomqvist, I. E. Castelli, R. Christensen, M. Dulak, J. Friis, M. N. Groves, B.Hammer, C. Hargus, E. D. Hermes, P. C. Jennings, P. B. Jensen,K. Kaasbjerg, J. Kermode, J. R. Kitchin, E. L. Kolsbjerg, J. Kubal, S. Lysgaard, J. B. Maronsson, T. Maxson, T. Olsen, L. Pastewka, A. Peterson, C. Rostgaard, J. Schi?tz, O. Schutt, M. Strange, K.Thygesen, T. Vegge, L. Vilhelmsen, M. Walter, Z. Zeng, and K. W.Jacobsen, The Atomic Simulation Environment — A Python library for working with atoms, J. Phys. Condens. Matter 29, 273002 (2017).

Contact for demo and discussion

[email protected] +91 9900138009