Graphite c-axis PES scans with Quantum ESPRESSO¶
Graphite interlayer binding curves from four density-functional setups.¶
Requires: AMS2026 or later
Related documentation
This report combines two non-optimizing PES scan segments per functional for graphite, scanning the c lattice parameter and plotting the relative energy against the interlayer distance c/2.
Conclusion¶
All curves are referenced to the energy at the longest sampled c value for each functional. The plot order is the reverse order of minimum energy so the legend follows the visible stacking order of the plotted curves.
Relative-energy plot¶
Summary table¶
Functional |
Min at c/2 (A) |
Min rel. energy (meV/atom) |
Ref. point c/2 (A) |
|---|---|---|---|
r2SCAN-D4 / Dojo |
3.350000 |
-57.165492 |
8.000000 |
B86bPBE-XDM / pslibrary-PAW |
3.350000 |
-53.810884 |
8.000000 |
r2SCAN / Dojo |
3.550000 |
-20.923848 |
8.000000 |
PBE / pslibrary-PAW |
4.250000 |
-1.820954 |
8.000000 |
Provenance¶
pbe_psl_paw_seg1: Short-range scan for PBE with pslibrary-PAW.pbe_psl_paw_seg2: Long-range continuation for PBE with pslibrary-PAW.b86bpbe_xdm_psl_paw_seg1: Short-range scan for B86bPBE with QE XDM dispersion and pslibrary-PAW.b86bpbe_xdm_psl_paw_seg2: Long-range continuation for B86bPBE with QE XDM dispersion and pslibrary-PAW.r2scan_dojo_seg1: Short-range scan for r2SCAN with Dojo pseudopotentials.r2scan_dojo_seg2: Long-range continuation for r2SCAN with Dojo pseudopotentials.r2scan_d4_dojo_seg1: Short-range scan for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.r2scan_d4_dojo_seg2: Long-range continuation for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
Calculation inputs¶
pbe_psl_paw_seg1¶
Reason: Short-range scan for PBE with pslibrary-PAW.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft pbe
occupations Smearing
smearing Gaussian
End
EndEngine
pbe_psl_paw_seg2¶
Reason: Long-range continuation for PBE with pslibrary-PAW.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft pbe
occupations Smearing
smearing Gaussian
End
EndEngine
b86bpbe_xdm_psl_paw_seg1¶
Reason: Short-range scan for B86bPBE with QE XDM dispersion and pslibrary-PAW.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft b86bpbe
occupations Smearing
smearing Gaussian
vdw_corr XDM
End
EndEngine
b86bpbe_xdm_psl_paw_seg2¶
Reason: Long-range continuation for B86bPBE with QE XDM dispersion and pslibrary-PAW.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft b86bpbe
occupations Smearing
smearing Gaussian
vdw_corr XDM
End
EndEngine
r2scan_dojo_seg1¶
Reason: Short-range scan for r2SCAN with Dojo pseudopotentials.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
r2scan_dojo_seg2¶
Reason: Long-range continuation for r2SCAN with Dojo pseudopotentials.
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
r2scan_d4_dojo_seg1¶
Reason: Short-range scan for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
EngineAddons
D4Dispersion
Enabled yes
Functional R2SCAN
End
End
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
r2scan_d4_dojo_seg2¶
Reason: Long-range continuation for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
EngineAddons
D4Dispersion
Enabled yes
Functional R2SCAN
End
End
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
Prompts and Python scripts¶
Prompt (instruction for AI agent)
Use $ams2026
Run non-optimizing PES scans where the C coordinate is scaled (LatticeCRange)
from 6.0 to 9.0 in steps of 0.1 angstrom, and then another run where it is
continued from 9.0 to 16.0 in steps of 0.5 angstrom.
Initial graphite system:
```
System
Atoms
C 0 0 1.5
C 0 0 4.5
C 0 1.4202816622064793 1.5
C 1.23 0.7101408311032397 4.5
End
Lattice
2.46 0 0
-1.23 2.130422493309719 0
0 0 6
End
End
```
Use QuantumESPRESSO with 12x12x4 k-points, gaussian smearing 0.001 Ry, energy
cutoff 100 Ry, density cutoff 1000 Ry.
Set `input_dft` explicitly.
Functionals:
- PBE with pslibrary-PAW
- BP86bPBE with pslibrary-PAW and XDM dispersion correction
- r2scan with Dojo
- r2scan with Dojo and D4 Engine addon dispersion correction.
In the report plot a figure with relative energy in meV/atom vs c/2 in angstrom
(c/2 = half c length, this is the interlayer graphite distance), where the
relative energy is energy relative to the energy of the longest c parameter. The
figure should have the plot for all tested functionals, and plot lines and small
points.
Plot the curves in the reverse order of minimum energy so that the order of the
colored lines in the legend matches the order in which they are shown in the
plot.
01-run.py
#!/usr/bin/env amspython
from __future__ import annotations
from dataclasses import dataclass
from scm.base import ChemicalSystem
from scm.input_classes import AMS
from scm.plams import AMSJob, Settings, config, init
SYSTEM_BLOCK = """
System
Atoms
C 0 0 1.5
C 0 0 4.5
C 0 1.4202816622064793 1.5
C 1.23 0.7101408311032397 4.5
End
Lattice
2.46 0 0
-1.23 2.130422493309719 0
0 0 6
End
End
"""
@dataclass(frozen=True)
class FunctionalSpec:
key: str
label: str
input_dft: str
pp_family: str
pp_functional: str
qe_vdw_corr: str | None = None
d4_functional: str | None = None
FUNCTIONALS: tuple[FunctionalSpec, ...] = (
FunctionalSpec(
key="pbe_psl_paw",
label="PBE / pslibrary-PAW",
input_dft="pbe",
pp_family="pslibrary-PAW",
pp_functional="PBE",
),
FunctionalSpec(
key="b86bpbe_xdm_psl_paw",
label="B86bPBE-XDM / pslibrary-PAW",
input_dft="b86bpbe",
pp_family="pslibrary-PAW",
pp_functional="PBE",
qe_vdw_corr="XDM",
),
FunctionalSpec(
key="r2scan_dojo",
label="r2SCAN / Dojo",
input_dft="r2scan",
pp_family="Dojo",
pp_functional="PBE",
),
FunctionalSpec(
key="r2scan_d4_dojo",
label="r2SCAN-D4 / Dojo",
input_dft="r2scan",
pp_family="Dojo",
pp_functional="PBE",
d4_functional="R2SCAN",
),
)
SCAN_SEGMENTS: tuple[tuple[str, float, float, float], ...] = (
("seg1", 6.0, 9.0, 0.1),
("seg2", 9.0, 16.0, 0.5),
)
def npoints(start: float, stop: float, step: float) -> int:
return int(round((stop - start) / step)) + 1
def build_settings(spec: FunctionalSpec, c_start: float, c_stop: float, step: float) -> Settings:
settings = Settings()
settings.input.ams.Task = "PESScan"
settings.input.ams.PESScan.Optimize = "No"
settings.input.ams.PESScan.CalcPropertiesAtPESPoints = "No"
settings.input.ams.PESScan.ScanCoordinate.nPoints = npoints(c_start, c_stop, step)
settings.input.ams.PESScan.ScanCoordinate.LatticeCRange = f"{c_start:.10g} {c_stop:.10g}"
settings.input.QuantumESPRESSO.Pseudopotentials.Family = spec.pp_family
settings.input.QuantumESPRESSO.Pseudopotentials.Functional = spec.pp_functional
settings.input.QuantumESPRESSO.System.input_dft = spec.input_dft
settings.input.QuantumESPRESSO.System.occupations = "Smearing"
settings.input.QuantumESPRESSO.System.smearing = "Gaussian"
settings.input.QuantumESPRESSO.System.degauss = 0.001
settings.input.QuantumESPRESSO.System.ecutwfc = 100.0
settings.input.QuantumESPRESSO.System.ecutrho = 1000.0
if spec.qe_vdw_corr is not None:
settings.input.QuantumESPRESSO.System.vdw_corr = spec.qe_vdw_corr
settings.input.QuantumESPRESSO.K_Points._h = "automatic"
settings.input.QuantumESPRESSO.K_Points._1 = "12 12 4 0 0 0"
if spec.d4_functional is not None:
settings.input.ams.EngineAddons.D4Dispersion.Enabled = "Yes"
settings.input.ams.EngineAddons.D4Dispersion.Functional = spec.d4_functional
AMS.from_settings(settings)
return settings
def main() -> None:
init(folder="01-run_workdir")
config.log.stdout = 1
system = ChemicalSystem(SYSTEM_BLOCK)
for spec in FUNCTIONALS:
for segment_name, c_start, c_stop, step in SCAN_SEGMENTS:
job_name = f"{spec.key}_{segment_name}"
settings = build_settings(spec, c_start, c_stop, step)
job = AMSJob(molecule=system, settings=settings, name=job_name)
print(f"Running {job_name}: {spec.label}, c = {c_start} -> {c_stop} A, step {step} A")
result = job.run()
if not result.ok():
raise RuntimeError(f"Job failed: {job_name}")
if __name__ == "__main__":
main()
report.py
#!/usr/bin/env amspython
from __future__ import annotations
from dataclasses import dataclass
from pathlib import Path
import shutil
import matplotlib.pyplot as plt
import pandas as pd
from scm.base import Units
from scm.plams import AMSJob
ROOT = Path(__file__).resolve().parent
WORKDIR = ROOT / "01-run_workdir"
REPORT_MD = ROOT / "report.md"
REPORT_BK = ROOT / "report.md.bk"
PLOT_PNG = ROOT / "relative_energy_vs_interlayer_distance.png"
N_ATOMS = 4
HARTREE_TO_MEV = Units.conversion_factor("hartree", "eV") * 1000.0
@dataclass(frozen=True)
class JobRef:
name: str
label: str
justification: str
JOB_REFS: tuple[JobRef, ...] = (
JobRef("pbe_psl_paw_seg1", "PBE / pslibrary-PAW, 6.0-9.0 A", "Short-range scan for PBE with pslibrary-PAW."),
JobRef("pbe_psl_paw_seg2", "PBE / pslibrary-PAW, 9.0-16.0 A", "Long-range continuation for PBE with pslibrary-PAW."),
JobRef(
"b86bpbe_xdm_psl_paw_seg1",
"B86bPBE-XDM / pslibrary-PAW, 6.0-9.0 A",
"Short-range scan for B86bPBE with QE XDM dispersion and pslibrary-PAW.",
),
JobRef(
"b86bpbe_xdm_psl_paw_seg2",
"B86bPBE-XDM / pslibrary-PAW, 9.0-16.0 A",
"Long-range continuation for B86bPBE with QE XDM dispersion and pslibrary-PAW.",
),
JobRef("r2scan_dojo_seg1", "r2SCAN / Dojo, 6.0-9.0 A", "Short-range scan for r2SCAN with Dojo pseudopotentials."),
JobRef("r2scan_dojo_seg2", "r2SCAN / Dojo, 9.0-16.0 A", "Long-range continuation for r2SCAN with Dojo pseudopotentials."),
JobRef(
"r2scan_d4_dojo_seg1",
"r2SCAN-D4 / Dojo, 6.0-9.0 A",
"Short-range scan for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.",
),
JobRef(
"r2scan_d4_dojo_seg2",
"r2SCAN-D4 / Dojo, 9.0-16.0 A",
"Long-range continuation for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.",
),
)
def load_job(job_name: str) -> AMSJob:
return AMSJob.load_external(WORKDIR / job_name)
def build_curve(job_names: tuple[str, str], label: str) -> pd.DataFrame:
frames: list[pd.DataFrame] = []
for job_name in job_names:
job = load_job(job_name)
pes = job.results.get_pesscan_results(molecules=False)
c_index = pes["RaveledScanCoords"].index("c")
c_unit = pes["RaveledUnits"][c_index]
c_conversion = Units.conversion_factor(c_unit, "angstrom")
c_values = pd.Series(pes["RaveledPESCoords"][c_index], dtype=float) * c_conversion
energies = pd.Series(pes["PES"], dtype=float)
frames.append(pd.DataFrame({"c_angstrom": c_values, "energy_hartree": energies}))
curve = pd.concat(frames, ignore_index=True)
curve = curve.drop_duplicates(subset="c_angstrom", keep="first").sort_values("c_angstrom").reset_index(drop=True)
reference_energy = curve.loc[curve["c_angstrom"].idxmax(), "energy_hartree"]
curve["c_over_2_angstrom"] = curve["c_angstrom"] / 2.0
curve["relative_mev_per_atom"] = (curve["energy_hartree"] - reference_energy) * HARTREE_TO_MEV / N_ATOMS
curve["functional"] = label
curve["minimum_relative_mev_per_atom"] = curve["relative_mev_per_atom"].min()
return curve
def plot_curves(curves: list[pd.DataFrame]) -> None:
curves_to_plot = sorted(curves, key=lambda df: float(df["minimum_relative_mev_per_atom"].iloc[0]), reverse=True)
plt.figure(figsize=(7.2, 4.8))
for curve in curves_to_plot:
label = str(curve["functional"].iloc[0])
plt.plot(
curve["c_over_2_angstrom"],
curve["relative_mev_per_atom"],
marker="o",
markersize=3,
linewidth=1.4,
label=label,
)
plt.xlabel("c/2 (angstrom)")
plt.ylabel("Relative energy (meV/atom)")
plt.legend(frameon=False)
plt.tight_layout()
plt.savefig(PLOT_PNG, dpi=200)
plt.close()
def build_summary_table(curves: list[pd.DataFrame]) -> pd.DataFrame:
rows: list[dict[str, float | str]] = []
for curve in curves:
minimum_row = curve.loc[curve["relative_mev_per_atom"].idxmin()]
rows.append(
{
"Functional": str(curve["functional"].iloc[0]),
"Min at c/2 (A)": float(minimum_row["c_over_2_angstrom"]),
"Min rel. energy (meV/atom)": float(minimum_row["relative_mev_per_atom"]),
"Ref. point c/2 (A)": float(curve["c_over_2_angstrom"].max()),
}
)
table = pd.DataFrame(rows)
return table.sort_values("Min rel. energy (meV/atom)").reset_index(drop=True)
def render_report(curves: list[pd.DataFrame]) -> None:
if REPORT_MD.exists():
shutil.copy2(REPORT_MD, REPORT_BK)
summary_table = build_summary_table(curves)
provenance_lines: list[str] = []
input_sections: list[str] = []
for job_ref in JOB_REFS:
job = load_job(job_ref.name)
provenance_lines.append(f"- `{job_ref.name}`: {job_ref.justification}")
input_sections.append(f"### `{job_ref.name}`\n\nReason: {job_ref.justification}\n\n```text\n{job.get_input().strip()}\n```")
report_text = "\n".join(
[
"# Graphite c-axis PES scans with QuantumESPRESSO",
"",
"This report combines two non-optimizing PES scan segments per functional for graphite, scanning the c lattice parameter and plotting the relative energy against the interlayer distance c/2.",
"",
"## Conclusion",
"",
"All curves are referenced to the energy at the longest sampled c value for each functional. The plot order is the reverse order of minimum energy so the legend follows the visible stacking order of the plotted curves.",
"",
"## Relative-energy plot",
"",
f"",
"",
"## Summary table",
"",
summary_table.to_markdown(index=False, floatfmt=".6f"),
"",
"## Provenance",
"",
*provenance_lines,
"",
"## Calculation inputs",
"",
*input_sections,
"",
]
)
REPORT_MD.write_text(report_text)
def main() -> None:
curves = [
build_curve(("pbe_psl_paw_seg1", "pbe_psl_paw_seg2"), "PBE / pslibrary-PAW"),
build_curve(("b86bpbe_xdm_psl_paw_seg1", "b86bpbe_xdm_psl_paw_seg2"), "B86bPBE-XDM / pslibrary-PAW"),
build_curve(("r2scan_dojo_seg1", "r2scan_dojo_seg2"), "r2SCAN / Dojo"),
build_curve(("r2scan_d4_dojo_seg1", "r2scan_d4_dojo_seg2"), "r2SCAN-D4 / Dojo"),
]
plot_curves(curves)
render_report(curves)
if __name__ == "__main__":
main()
Original Markdown report
# Graphite c-axis PES scans with QuantumESPRESSO
This report combines two non-optimizing PES scan segments per functional for graphite, scanning the c lattice parameter and plotting the relative energy against the interlayer distance c/2.
## Conclusion
All curves are referenced to the energy at the longest sampled c value for each functional. The plot order is the reverse order of minimum energy so the legend follows the visible stacking order of the plotted curves.
## Relative-energy plot
## Summary table
| Functional | Min at c/2 (A) | Min rel. energy (meV/atom) | Ref. point c/2 (A) |
|:----------------------------|-----------------:|-----------------------------:|---------------------:|
| r2SCAN-D4 / Dojo | 3.350000 | -57.165492 | 8.000000 |
| B86bPBE-XDM / pslibrary-PAW | 3.350000 | -53.810884 | 8.000000 |
| r2SCAN / Dojo | 3.550000 | -20.923848 | 8.000000 |
| PBE / pslibrary-PAW | 4.250000 | -1.820954 | 8.000000 |
## Provenance
- `pbe_psl_paw_seg1`: Short-range scan for PBE with pslibrary-PAW.
- `pbe_psl_paw_seg2`: Long-range continuation for PBE with pslibrary-PAW.
- `b86bpbe_xdm_psl_paw_seg1`: Short-range scan for B86bPBE with QE XDM dispersion and pslibrary-PAW.
- `b86bpbe_xdm_psl_paw_seg2`: Long-range continuation for B86bPBE with QE XDM dispersion and pslibrary-PAW.
- `r2scan_dojo_seg1`: Short-range scan for r2SCAN with Dojo pseudopotentials.
- `r2scan_dojo_seg2`: Long-range continuation for r2SCAN with Dojo pseudopotentials.
- `r2scan_d4_dojo_seg1`: Short-range scan for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
- `r2scan_d4_dojo_seg2`: Long-range continuation for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
## Calculation inputs
### `pbe_psl_paw_seg1`
Reason: Short-range scan for PBE with pslibrary-PAW.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft pbe
occupations Smearing
smearing Gaussian
End
EndEngine
```
### `pbe_psl_paw_seg2`
Reason: Long-range continuation for PBE with pslibrary-PAW.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft pbe
occupations Smearing
smearing Gaussian
End
EndEngine
```
### `b86bpbe_xdm_psl_paw_seg1`
Reason: Short-range scan for B86bPBE with QE XDM dispersion and pslibrary-PAW.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft b86bpbe
occupations Smearing
smearing Gaussian
vdw_corr XDM
End
EndEngine
```
### `b86bpbe_xdm_psl_paw_seg2`
Reason: Long-range continuation for B86bPBE with QE XDM dispersion and pslibrary-PAW.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family pslibrary-PAW
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft b86bpbe
occupations Smearing
smearing Gaussian
vdw_corr XDM
End
EndEngine
```
### `r2scan_dojo_seg1`
Reason: Short-range scan for r2SCAN with Dojo pseudopotentials.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
```
### `r2scan_dojo_seg2`
Reason: Long-range continuation for r2SCAN with Dojo pseudopotentials.
```ams
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
```
### `r2scan_d4_dojo_seg1`
Reason: Short-range scan for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
```ams
EngineAddons
D4Dispersion
Enabled yes
Functional R2SCAN
End
End
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 6 9
nPoints 31
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
```
### `r2scan_d4_dojo_seg2`
Reason: Long-range continuation for r2SCAN with Dojo pseudopotentials and the AMS D4 add-on.
```ams
EngineAddons
D4Dispersion
Enabled yes
Functional R2SCAN
End
End
PESScan
CalcPropertiesAtPESPoints no
Optimize no
ScanCoordinate
LatticeCRange 9 16
nPoints 15
End
End
Task PESScan
System
Atoms
C 0.0000000000 0.0000000000 1.5000000000
C 0.0000000000 0.0000000000 4.5000000000
C 0.0000000000 1.4202816622 1.5000000000
C 1.2300000000 0.7101408311 4.5000000000
End
Lattice
2.4600000000 0.0000000000 0.0000000000
-1.2300000000 2.1304224933 0.0000000000
0.0000000000 0.0000000000 6.0000000000
End
End
Engine QuantumESPRESSO
K_Points automatic
12 12 4 0 0 0
End
Pseudopotentials
Family Dojo
Functional PBE
End
System
degauss 0.001
ecutrho 1000.0
ecutwfc 100.0
input_dft r2scan
occupations Smearing
smearing Gaussian
End
EndEngine
```