2. NanoDCAL: electronic structure and transport (experimental)

Note

NanoDCAL support is experimental and in active development. The calculation types below have been tested end-to-end, but the backend is evolving. For the full support matrix, see NanoDCAL support (experimental).

LatticeMind’s NanoDCAL backend brings quantum-transport-oriented calculations into the same plain-language workflow. You select it simply by saying “Using NanoDCAL, …” in your prompt. This tutorial walks through a silicon band structure, then points to the full two-probe transport workflow.

2.1. Silicon band structure

Using NanoDCAL, run an SCF and band structure calculation for silicon.

LatticeMind builds the silicon crystal, stages the LCAO basis files with the project, runs the SCF, then computes the band structure along the standard high-symmetry path — and plots it referenced to the Fermi level:

Fig. 2.1.1 Silicon band structure from NanoDCAL, along L–Γ–X–W–K with energies referenced to the Fermi level (dashed line). The indirect gap between the valence-band maximum at Γ and the conduction-band minimum near X is clearly resolved.

2.2. Validate the band-gap interpretation

The plotted zero is the NanoDCAL Fermi energy. The reported silicon gap is obtained from the occupied and unoccupied bands sampled along the full L–Γ–X–W–K path. It is therefore an indirect path-sampled gap, not the energy separation between two states selected at one k-point.

This distinction matters when comparing BandStructure.mat with EigenStates.mat. For example, requesting one state below and one state above the Fermi level on a [1, 1, 1] grid samples two Γ-point states. Their direct separation can be much larger than silicon’s indirect band gap and should not be reported as the PBE fundamental gap.

Before using the value in a manuscript:

• repeat the SCF calculation with a denser k-grid and keep the plotted high-symmetry path unchanged;

• record the exchange-correlation functional and NeutralAtomDatabase basis choice, because both affect the numerical gap;

• confirm that results/analysis_summary.json reports the same band edges visible in the figure; and

• remember that a converged PBE gap is a method-specific result, not an experimental-gap correction.

Tip

Because the LCAO basis travels with the project (nanodcal_basis/), the generated project runs unchanged on another machine — locally or on a remote NanoDCAL server (see Remote & HPC execution). When sharing the generated project, please keep the staged NeutralAtomDatabase files within the scope of your Nanoacademic license.

2.3. Spin-resolved transmission channels

This prompt exercises the transverse-k and spin dimensions in TransmissionChannel.mat:

Using NanoDCAL, run SCF and transmission-channel analysis for
ferromagnetic bcc iron.

LatticeMind plots the channel count on the regular transverse-k mesh and keeps the spin-up and spin-down maps on the same colour scale:

Fig. 2.3.2 NanoDCAL transmission-channel count at the Fermi level for 900 transverse k-points. Separate spin panels preserve the two-dimensional k-space structure instead of flattening it into a sample-index curve.

2.4. How to read and validate the channel map

Each pixel represents one transverse (k1, k2) point at E - EF = 0 eV; the colour gives the number of open transmission channels at that point. Both spin panels use the same colour limits, so their different k-space patterns can be compared directly. The map is not, by itself, a total conductance: a scalar transport value also requires the transverse-k weights and the appropriate energy or bias integration.

Before interpreting the spin contrast, check that:

• the bcc Fe SCF calculation converged to the intended magnetic state;

• both panels use the same energy, transverse mesh, and colour scale;

• the channel pattern and any integrated transport quantity are stable when the transverse mesh is refined beyond the illustrated 30 by 30 grid; and

• the lead and device calculations use compatible cells, basis data, and spin settings.

Use figures/transmission_channels.png in the generated HTML report and the SVG or PDF export when editing a manuscript. The matching results/figure_manifest.json entry records TransmissionChannel.mat as the source and lists the PNG, SVG, and PDF paths, dimensions, and DPI.

2.5. Going further: quantum transport

The same one-line pattern drives full two-probe transport calculations — LatticeMind builds the lead-SCF → device-SCF → property chain automatically:

Using NanoDCAL, run a transmission calculation along z for a homogeneous
aluminum two-probe device.

Start with the zero-bias transmission and inspect Transmission.mat before requesting a bias sweep. A useful follow-up is:

Using NanoDCAL, calculate an I-V curve along z for a homogeneous aluminum
two-probe device from -0.2 V to 0.2 V.

For every transport comparison, keep the device geometry, lead construction, NeutralAtomDatabase basis, transverse k-grid, energy grid, and electronic temperature fixed unless the prompt explicitly studies one of those choices.

See NanoDCAL support (experimental) for the complete list of supported transport, electronic-structure, phonon, and mechanical calculations.

2.6. Three useful follow-up checks

The following prompts exercise different NanoDCAL output families without changing the installation:

1. Using NanoDCAL, calculate total energy, effective potential, electron density, and charge analysis for rocksalt MgO. This produces TotalEnergy.mat, EffectivePotential.mat, TotalElectronDensity.mat, and Charge.mat after one SCF calculation.

2. Using NanoDCAL, calculate the effective mass for GaAs. This produces EffectiveMass.mat and tests the electron/hole dispersion fit and directional masses in units of \(m_e\).

3. Using NanoDCAL, run a conductance calculation along z for a homogeneous aluminum two-probe device. This exercises the lead-SCF, device-SCF, and conductance chain and produces ConductanceAndCurrent.mat.

For each project, inspect /launch-preview before execution. After execution, confirm that calculation_status.json.instances marks every requested deck as succeeded, that the expected .mat files exist, and that results/analysis_summary.json.warnings contains no unexplained parser or physics warning. To test only the updated plotting path, ask LatticeMind to reprocess the existing NanoDCAL outputs without rerunning the solver.

2.7. What you learned

• Selecting NanoDCAL is as simple as saying so in your prompt.

• LatticeMind handles NanoDCAL’s basis staging, multi-step dependencies, and device chains for you.

• Plot-capable results produce a 360 dpi PNG for report.html plus SVG and PDF manuscript exports under figures/.

• results/analysis_summary.json stores numeric summaries and results/figure_manifest.json links each figure to its NanoDCAL .mat source file.