6 research outputs found
Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models
The numerical precision of density-functional-theory (DFT) calculations
depends on a variety of computational parameters, one of the most critical
being the basis-set size. The ultimate precision is reached with an infinitely
large basis set, i.e., in the limit of a complete basis set (CBS). Our aim in
this work is to find a machine-learning model that extrapolates finite
basis-size calculations to the CBS limit. We start with a data set of 63 binary
solids investigated with two all-electron DFT codes, exciting and FHI-aims,
which employ very different types of basis sets. A quantile-random-forest model
is used to estimate the total-energy correction with respect to a fully
converged calculation as a function of the basis-set size. The random-forest
model achieves a symmetric mean absolute percentage error of lower than 25% for
both codes and outperforms previous approaches in the literature. Our approach
also provides prediction intervals, which quantify the uncertainty of the
models' predictions
Electronic structure of MoS revisited: a comprehensive assessment of calculations
Two-dimensional MoS combines many interesting properties that make the
material a top candidate for a variety of applications. It exhibits a high
electron mobility comparable to graphene, a direct fundamental band gap,
relatively strongly bound excitons, and moderate spin-orbit coupling. For a
thorough understanding of all these properties, an accurate description of the
electronic structure is mandatory. Surprisingly, published band gaps of MoS
obtained with , the state-of-the-art in electronic-structure calculations,
are quite scattered, ranging from 2.31 to 2.97 eV. The details of
calculations, such as the underlying geometry, the starting point, the
inclusion of spin-orbit coupling, and the treatment of the Coulomb potential
can critically determine how accurate the results are. In this manuscript, we
employ the linearized augmented planewave + local orbital method to
systematically investigate how all these aspects affect the quality of
calculations, and also provide a summary of literature data. We conclude that
the best overall agreement with experiments and coupled-cluster calculations is
found for results with HSE06 as a starting point including spin-orbit
coupling, a truncated Coulomb potential, and an analytical treatment of the
singularity at
Numerical Quality Control for DFT-based Materials Databases
Electronic-structure theory is a strong pillar of materials science. Many
different computer codes that employ different approaches are used by the
community to solve various scientific problems. Still, the precision of
different packages has only recently been scrutinized thoroughly, focusing on a
specific task, namely selecting a popular density functional, and using
unusually high, extremely precise numerical settings for investigating 71
monoatomic crystals. Little is known, however, about method- and code-specific
uncertainties that arise under numerical settings that are commonly used in
practice. We shed light on this issue by investigating the deviations in total
and relative energies as a function of computational parameters. Using typical
settings for basis sets and k-grids, we compare results for 71 elemental and 63
binary solids obtained by three different electronic-structure codes that
employ fundamentally different strategies. On the basis of the observed trends,
we propose a simple, analytical model for the estimation of the errors
associated with the basis-set incompleteness. We cross-validate this model
using ternary systems obtained from the NOMAD Repository and discuss how our
approach enables the comparison of the heterogeneous data present in
computational materials databases.Comment: 7 pages, 4 figure
Maxquant software for ion mobility enhanced shotgun proteomics
Ion mobility can add a dimension to LC-MS based shotgun proteomics which has the potential to boost proteome coverage, quantification accuracy and dynamic range. Required for this is suitable software that extracts the information contained in the four-dimensional (4D) data space spanned by m/z, retention time, ion mobility and signal intensity. Here we describe the ion mobility enhanced MaxQuant software, which utilizes the added data dimension. It offers an end to end computational workflow for the identification and quantification of peptides and proteins in LC-IMS-MS/MS shotgun proteomics data. We apply it to trapped ion mobility spectrometry (TIMS) coupled to a quadrupole time-of-flight (QTOF) analyzer. A highly parallelizable 4D feature detection algorithm extracts peaks which are assembled to isotope patterns. Masses are recalibrated with a non-linear m/z, retention time, ion mobility and signal intensity dependent model, based on peptides from the sample. A new matching between runs (MBR) algorithm that utilizes collisional cross section (CCS) values of MS1 features in the matching process significantly gains specificity from the extra dimension. Prerequisite for using CCS values in MBR is a relative alignment of the ion mobility values between the runs. The missing value problem in protein quantification over many samples is greatly reduced by CCS aware MBR.MS1 level label-free quantification is also implemented which proves to be highly precise and accurate on a benchmark dataset with known ground truth. MaxQuant for LC-IMS-MS/MS is part of the basic MaxQuant release and can be downloaded from http://maxquant.org
Reproducibility in density functional theory calculations of solids
NTRODUCTION The reproducibility of results is one of the underlying principles of science. An observation can only be accepted by the scientific community when it can be confirmed by independent studies. However, reproducibility does not come easily. Recent works have painfully exposed cases where previous conclusions were not upheld. The scrutiny of the scientific community has also turned to research involving computer programs, finding that reproducibility depends more strongly on implementation than commonly thought. These problems are especially relevant for property predictions of crystals and molecules, which hinge on precise computer implementations of the governing equation of quantum physics. RATIONALE This work focuses on density functional theory (DFT), a particularly popular quantum method for both academic and industrial applications. More than 15,000 DFT papers are published each year, and DFT is now increasingly used in an automated fashion to build large databases or apply multiscale techniques with limited human supervision. Therefore, the reproducibility of DFT results underlies the scientific credibility of a substantial fraction of current work in the natural and engineering sciences. A plethora of DFT computer codes are available, many of them differing considerably in their details of implementation, and each yielding a certain “precision” relative to other codes. How is one to decide for more than a few simple cases which code predicts the correct result, and which does not? We devised a procedure to assess the precision of DFT methods and used this to demonstrate reproducibility among many of the most widely used DFT codes. The essential part of this assessment is a pairwise comparison of a wide range of methods with respect to their predictions of the equations of state of the elemental crystals. This effort required the combined expertise of a large group of code developers and expert users. RESULTS We calculated equation-of-state data for four classes of DFT implementations, totaling 40 methods. Most codes agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Even in the case of pseudization approaches, which largely depend on the atomic potentials used, a similar precision can be obtained as when using the full potential. The remaining deviations are due to subtle effects, such as specific numerical implementations or the treatment of relativistic terms. CONCLUSION Our work demonstrates that the precision of DFT implementations can be determined, even in the absence of one absolute reference code. Although this was not the case 5 to 10 years ago, most of the commonly used codes and methods are now found to predict essentially identical results. The established precision of DFT codes not only ensures the reproducibility of DFT predictions but also puts several past and future developments on a firmer footing. Any newly developed methodology can now be tested against the benchmark to verify whether it reaches the same level of precision. New DFT applications can be shown to have used a sufficiently precise method. Moreover, high-precision DFT calculations are essential for developing improvements to DFT methodology, such as new density functionals, which may further increase the predictive power of the simulations