Preface to Special Issue of ChemSusChem on Interfacing Experiment and Theory in the Development of Energy Storage and Devices.

This Editorial discusses the importance of scientists currently working in separate fields-experimental characterization of novel materials and theoretical investigations of electrochemical processes-joining forces to advance the field of energy-storage materials and devices. Some of these efforts are published in this Special Issue by ChemSusChem.

Density Functional Theory: Not Quite the Right Answer for the Right Reason Yet.

More insight or only more parameters? A recent claim that the development of new density functional theory (DFT) functionals is straying from the right path has sparked a lively discussion among theoretical chemists about the future of DFT.

Developing adaptive QM/MM computer simulations for electrochemistry.

We report the development of adaptive QM/MM computer simulations for electrochemistry, providing public access to all sources via the free and open source software development model. We present a modular workflow-based MD simulation code as a platform for algorithms for partitioning space into different regions, which can be treated at different levels of theory on a per-timestep basis. Currently implemented algorithms focus on targeting molecules and their solvation layers relevant to electrochemistry. Instead of using built-in forcefields and quantum mechanical methods, the code features a universal interface, which allows for extension to a range of external forcefield programs and programs for quantum mechanical calculations, thus enabling the user to readily implement interfaces to those programs. The purpose of this article is to describe our codes and illustrate its usage. © 2016 Wiley Periodicals, Inc.

Can dispersion corrections annihilate the dispersion-driven nano-aggregation of non-polar groups? An ab initio molecular dynamics study of ionic liquid systems.

In this study, we aim at understanding the influence of dispersion correction on the ab initio molecular dynamics simulations of ionic liquid (IL) systems. We investigated a large bulk system of the 1-butyl-3-methylimidazolium triflate IL and a small cluster system of ethylamine in ethylammonium nitrate both under periodic boundary conditions. The large system displays several changes upon neglect of dispersion correction, the most striking one is the surprising decrease of the well-known microheterogeneity which is accompanied by an increase of side chain hydrogen atom-anion interplay. For the diffusion coefficient, we observe a correction towards experimental behavior in terms of the cation becoming faster than the anion with dispersion correction. Changes in the electronic structure upon dispersion correction are reflected in larger/smaller dipole moments for anions/cations also seen in the calculated IR spectrum. The energetics of different ion pair dimer subsystems (polar and non-polar) are in accordance with the analysis of the trajectories: A detailed balance in the ionic liquid system determines its particular behavior. While the overall interaction terms for dispersion-corrected calculations are higher, the decrease in microheterogeneity upon inclusion of dispersion interaction becomes obvious due to the relation between all contributions to polar-polar terms. For the small system, we clearly observe the well known behavior that the hybrid functionals show higher reaction barriers than the pure generalized gradient approximation (GGA) functionals. The correction of dispersion reduces the discrepancies in some cases. Accounting for the number of jumps, we observe that dispersion correction reduces the discrepancies from 50% to less than 10%.

Impact of Selected LiPF6 Hydrolysis Products on the High Voltage Stability of Lithium-Ion Battery Cells.

Diverse LiPF6 hydrolysis products evolve during lithium-ion battery cell operation at elevated operation temperatures and high operation voltages. However, their impact on the formation and stability of the electrode/electrolyte interfaces is not yet investigated and understood. In this work, literature-known hydrolysis products of LiPF6 dimethyl fluorophosphate (DMFP) and diethyl fluorophosphate (DEFP) were synthesized and characterized. The use of DMFP and DEFP as electrolyte additive in 1 M LiPF6 in EC:EMC (1:1, by wt) was investigated in LiNi1/3Mn1/3Co1/3O2/Li half cells. When charged to a cutoff potential of 4.6 V vs Li/Li+, the additive containing cells showed improved cycling stability, increased Coulombic efficiencies, and prolonged shelf life. Furthermore, low amounts (1 wt % in this study) of the aforementioned additives did not show any negative effect on the cycling stability of graphite/Li half cells. DMFP and DEFP are susceptible to oxidation and contribute to the formation of an effective cathode/electrolyte interphase as confirmed by means of electrochemical stability window determination, and X-ray photoelectron spectroscopy characterization of pristine and cycled electrodes, and they are supported by computational calculations.

Prospects of Applying Enhanced Semi-Empirical QM Methods for 2101 Virtual Drug Design.

The last five years have seen a renaissance of semiempirical quantum mechanical (SQM) methods in the field of virtual drug design, largely due to the increased accuracy of so-called enhanced SQM approaches. These methods make use of additional terms for treating dispersion (D) and hydrogen bond (H) interactions with an accuracy comparable to dispersion-corrected density functional theory (DFT-D). DFT-D in turn was shown to provide an accuracy comparable to the most sophisticated QM approaches when it comes to non-covalent intermolecular forces, which usually dominate the protein/ligand interactions that are central to virtual drug design. Enhanced SQM methods thus offer a very promising way to improve upon the current state of the art in the field of virtual drug design.

Alternative Single-Solvent Electrolytes Based on Cyanoesters for Safer Lithium-Ion Batteries.

To identify alternative single-solvent-based electrolytes for application in lithium-ion batteries (LIBs), adequate computational methods were applied to screen specified physicochemical and electrochemical properties of new cyanoester-based compounds. Out of 2747 possible target compounds, two promising candidates and two structurally equivalent components were chosen. A constructive selection process including evaluation of basic physicochemical properties as well assessing the compatibility towards graphitic anodes was initiated to identify the most promising candidates. With addition of a film-forming additive in a low concentration, the most promising candidate showed an adequate long-term cycling stability with LiNi1/3 Mn1/3 Co1/3 O2 [NMC(111)] in a full-cell setup using graphite as anode material. The main advantages of the new electrolyte formulation are related to its good thermal behavior, especially with regard to safety in combination with satisfying electrochemical performance.

Recent Progress in Treating Protein-Ligand Interactions with Quantum-Mechanical Methods.

We review the first successes and failures of a "new wave" of quantum chemistry-based approaches to the treatment of protein/ligand interactions. These approaches share the use of "enhanced", dispersion (D), and/or hydrogen-bond (H) corrected density functional theory (DFT) or semi-empirical quantum mechanical (SQM) methods, in combination with ensemble weighting techniques of some form to capture entropic effects. Benchmark and model system calculations in comparison to high-level theoretical as well as experimental references have shown that both DFT-D (dispersion-corrected density functional theory) and SQM-DH (dispersion and hydrogen bond-corrected semi-empirical quantum mechanical) perform much more accurately than older DFT and SQM approaches and also standard docking methods. In addition, DFT-D might soon become and SQM-DH already is fast enough to compute a large number of binding modes of comparably large protein/ligand complexes, thus allowing for a more accurate assessment of entropic effects.

How to estimate solid-electrolyte-interphase features when screening electrolyte materials.

Computational screening of battery electrolyte components is an extremely challenging task because very complex features like solid-electrolyte-interphase (SEI) formation and graphite exfoliation need to be taken into account at least in the final screening stage. We present estimators for both SEI formation and graphite exfoliation based on a combinatorial approach using quantum chemistry calculations on model system reactions, which can be applied automatically for a large number of compounds and thus allows for the systematic first assessment of the relevant properties using screening approaches. The thermodynamic effects are assessed using quantum mechanical calculations, while a more heuristic approach is used to estimate the kinetic effects.

Charting the known chemical space for non-aqueous lithium-air battery electrolyte solvents.

Li-air batteries are very promising candidates for powering future mobility, but finding a suitable electrolyte solvent for this technology turned out to be a major problem. We present a systematic computational investigation of the known chemical space for possible Li-air electrolyte solvents. It is shown that the problem of finding better Li-air electrolyte solvents is not only - as previously suggested - about maximizing Li(+) and O2(-) solubilities, but also about finding the optimal balance of these solubilities with the viscosity of the solvent. As our results also show that trial-and-error experiments on known chemicals are unlikely to succeed, full chemical sub-spaces for the most promising compound classes are investigated, and suggestions are made for further experiments. The proposed screening approach is transferable and robust and can readily be applied to optimize electrolytes for other electrochemical devices. It goes beyond the current state-of-the-art both in width (considering the number of compounds screened and the way they are selected), as well as depth (considering the number and complexity of properties included).

Enhanced semiempirical QM methods for biomolecular interactions.

Recent successes and failures of the application of 'enhanced' semiempirical QM (SQM) methods are reviewed in the light of the benefits and backdraws of adding dispersion (D) and hydrogen-bond (H) correction terms. We find that the accuracy of SQM-DH methods for non-covalent interactions is very often reported to be comparable to dispersion-corrected density functional theory (DFT-D), while computation times are about three orders of magnitude lower. SQM-DH methods thus open up a possibility to simulate realistically large model systems for problems both in life and materials science with comparably high accuracy.

Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: computing infrastructure and collective properties.

A volunteer computing approach is presented for the purpose of screening a large number of molecular structures with respect to their suitability as new battery electrolyte solvents. Collective properties like melting, boiling and flash points are evaluated using COSMOtherm and quantitative structure-property relationship (QSPR) based methods, while electronic structure theory methods are used for the computation of electrochemical stability window estimators. Two application examples are presented: first, the results of a previous large-scale screening test (PCCP, 2014, 16, 7919) are re-evaluated with respect to the mentioned collective properties. As a second application example, all reasonable nitrile solvents up to 12 heavy atoms are generated and used to illustrate a suitable filter protocol for picking Pareto-optimal candidates.

A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+.

We present new dispersion and hydrogen bond corrections to the PM6 method, PM6-D3H+, and its implementation in the GAMESS program. The method combines the DFT-D3 dispersion correction by Grimme et al. with a modified version of the H+ hydrogen bond correction by Korth. Overall, the interaction energy of PM6-D3H+ is very similar to PM6-DH2 and PM6-DH+, with RMSD and MAD values within 0.02 kcal/mol of one another. The main difference is that the geometry optimizations of 88 complexes result in 82, 6, 0, and 0 geometries with 0, 1, 2, and 3 or more imaginary frequencies using PM6-D3H+ implemented in GAMESS, while the corresponding numbers for PM6-DH+ implemented in MOPAC are 54, 17, 15, and 2. The PM6-D3H+ method as implemented in GAMESS offers an attractive alternative to PM6-DH+ in MOPAC in cases where the LBFGS optimizer must be used and a vibrational analysis is needed, e.g., when computing vibrational free energies. While the GAMESS implementation is up to 10 times slower for geometry optimizations of proteins in bulk solvent, compared to MOPAC, it is sufficiently fast to make geometry optimizations of small proteins practically feasible.

Large-scale virtual high-throughput screening for the identification of new battery electrolyte solvents: evaluation of electronic structure theory methods.

The performance of semi-empirical quantum mechanical (SQM), density functional theory (DFT) and wave function theory (WFT) methods is evaluated for the purpose of screening a large number of molecular structures with respect to their electrochemical stability to identify new battery electrolyte solvents. Starting from 100,000 database entries and based on more than 46,000 DFT calculations, 83 candidate molecules are identified and then used for benchmarking lower-level computational models (SQM, DFT) with respect to higher-level WFT reference data. A combination of SQM and WFT methods is suggested as a screening strategy at the electronic structure theory level. Using a subset of over 11,000 typical organic molecules and based on over 22,000 high-level WFT calculations, several simple models are tested for the prediction of ionization potentials (IPs) and electron affinities (EAs). Reference data are made available for the development of more sophisticated QSPR models.

Error estimates for (semi-)empirical dispersion terms and large biomacromolecules.

The first-principles modeling of biomaterials has made tremendous advances over the last few years with the ongoing growth of computing power and impressive developments in the application of density functional theory (DFT) codes to large systems. One important step forward was the development of dispersion corrections for DFT methods, which account for the otherwise neglected dispersive van der Waals (vdW) interactions. Approaches at different levels of theory exist, with the most often used (semi-)empirical ones based on pair-wise interatomic C6R(-6) terms. Similar terms are now also used in connection with semiempirical QM (SQM) methods and density functional tight binding methods (SCC-DFTB). Their basic structure equals the attractive term in Lennard-Jones potentials, common to most force field approaches, but they usually use some type of cutoff function to make the mixing of the (long-range) dispersion term with the already existing (short-range) dispersion and exchange-repulsion effects from the electronic structure theory methods possible. All these dispersion approximations were found to perform accurately for smaller systems, but error estimates for larger systems are very rare and completely missing for really large biomolecules. We derive such estimates for the dispersion terms of DFT, SQM and MM methods using error statistics for smaller systems and dispersion contribution estimates for the PDBbind database of protein-ligand interactions. We find that dispersion terms will usually not be a limiting factor for reaching chemical accuracy, though some force fields and large ligand sizes are problematic.

Comparison of molecular mechanics, semi-empirical quantum mechanical, and density functional theory methods for scoring protein-ligand interactions.

Correctly ranking protein-ligand interactions with respect to overall free energy of binding is a grand challenge for virtual drug design. Here we compare the performance of various quantum chemical approaches for tackling this so-called "scoring" problem. Relying on systematically generated benchmark sets of large protein/ligand model complexes based on the PDBbind database, we show that the performance depends first of all on the general level of theory. Comparing classical molecular mechanics (MM), semiempirical quantum mechanical (SQM), and density functional theory (DFT) based methods, we find that enhanced SQM approaches perform very similar to DFT methods and substantially different from MM potentials.

Empirical hydrogen-bond potential functions--an old hat reconditioned.

The accurate description of hydrogen-bond interactions is of vital importance for the computational modeling of biological systems. Standard force field (FF) as well as semiempirical quantum mechanical (SQM) methods are now known to have considerable problems with the accurate description of hydrogen bonds. It was found that the performance of SQM methods can be greatly improved with empirical hydrogen-bond correction terms. In the first part of this work we review the improvements developed during the recent revival of dedicated hydrogen-bond terms, also in the light of earlier FF-related work. The second part presents new findings connected to open questions in this field, namely, a study on the importance of angular and torsional information, a scheme how to avoid atom-type-defined target angles and a reduced version of our DH(+) model for the application to force-field methods and physically motivated protein-ligand scoring functions. Our results highlight the importance of using a complete geometric description (including angular and torsional coordinates) for the accurate treatment of hydrogen bonding. The reduced DH(+) model-applied to a modified version of the UFF force field-shows a much improved accuracy for non-covalent interactions also with FF methods, with gains in accuracy by more than one order of magnitude.

The lithium-thiophene riddle revisited.

A recent study of the interaction of a lithium atom with the thiophene molecule found a large disagreement between high-level coupled cluster (CCSD(T)/AVTZ) and quantum Monte Carlo (fixed-node diffusion Monte Carlo, or FNDMC) calculations. We address this "lithium-thiophene riddle" by analyzing the influence of crucial FNDMC simulation parameters, namely, the one-electron models, basis sets, and pseudopotentials used for the generation of the trial wave function. These are shown to have a significant impact on the calculated FNDMC interaction energies, and good agreement between CCSD(T) and FNDMC is found when nodal hypersurfaces of sufficient quality are used. On the basis of our proposed consensus reference value, we go on to benchmark the standard toolbox of lower-level quantum chemistry methods for this model interaction. Newly developed dispersion-corrected DFT methods perform reasonably well despite the partial charge transfer character of the interaction and might well be worthy of further study in larger lithium-thiophene systems.

Benchmarking Semiempirical Methods for Thermochemistry, Kinetics, and Noncovalent Interactions: OMx Methods Are Almost As Accurate and Robust As DFT-GGA Methods for Organic Molecules.

Semiempirical quantum mechanical (SQM) methods offer a fast approximate treatment of the electronic structure and the properties of large molecules. Careful benchmarks are required to establish their accuracy. Here, we report a validation of standard SQM methods using a subset of the comprehensive GMTKN24 database for general main group thermochemistry, kinetics, and noncovalent interactions, which has recently been introduced to evaluate density functional theory (DFT) methods ( J. Chem. Theory Comput. 2010 , 6 , 107 ). For all SQM methods considered presently, parameters are available for the elements H, C, N, and O, and consequently, we have extracted from the GMTKN24 database all species containing only these four elements (excluding multireference cases). The resulting GMTKN24-hcno database has 370 entries (derived from 593 energies) compared with 715 entries (derived from 1033 energies) in the original GMTKN24 database. The current benchmark covers established standard SQM methods (AM1, PM6), more recent approaches with orthogonalization corrections (OM1, OM2, OM3), and the self-consistent-charge density functional tight binding method (SCC-DFTB). The results are compared against each other and against DFT results using standard functionals. We find that the OMx methods outperform AM1, PM6, and SCC-DFTB by a significant margin, with a substantial gain in accuracy especially for OM2 and OM3. These latter methods are quite accurate even in comparison with DFT, with an overall mean absolute deviation of 6.6 kcal/mol for PBE and 7.9 kcal/mol for OM3. The OMx methods are also remarkably robust with regard to the unusual bonding situations encountered in the "mindless" MB08-165 test set, for which all other SQM methods fail badly.

A Transferable H-Bonding Correction for Semiempirical Quantum-Chemical Methods.

Semiempirical methods could offer a feasible compromise between ab initio and empirical approaches for the calculation of large molecules with biological relevance. A key problem for attempts in this direction is the rather bad performance of current semiempirical methods for noncovalent interactions, especially hydrogen-bonding. On the basis of the recently introduced PM6-DH method, which includes empirical corrections for dispersion (D) and hydrogen-bond (H) interactions, we have developed an improved and transferable H-bonding correction for semiempirical quantum chemical methods. The performance of the improved correction is evaluated for PM6, AM1, OM3, and SCC-DFTB (enhanced by standard empirical dispersion corrections) with several test sets for noncovalent interactions and is shown to reach the quality of current DFT-D approaches for these types of problems.