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Proton transfer processes in water are of fundamental importance for, among others, electrochemical proton discharge. Empirical valence bond (EVB) approaches were shown in the past to be a versatile tool for modeling complex phenomena such as proton discharge at metal electrodes. By replacing empirical fitting procedures with on-the-fly quantum chemistry (QC) calculations, we arrive at a transferable and systematically tunable description of proton transfer in water with EVB.

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 c...

The development of new electrolytes is a centerpiece of many strategies to improve electrochemical double layer capacitor (EDLC) devices. We present here a computational screening-based rational design approach to find new electrolyte materials. As an example application, the known chemical space of almost 70 million compounds is investigated in search of electrochemically more stable solvents. Cyano esters are identified as especially promising new compound class. Theoretical predictions are validated with subsequent experimental studies on a selected case. These studies show that based on theoretical predictions only, a previously untested, but very well performing compound class was identified. We thus find that our rational design strategy is indeed able to successfully identify completely new materials with substantially improved properties.

Electrochemical double-layer capacitors (EDLCs) are robust, high-power, and fast-charging energy storage devices. Rational design of novel electrolyte materials could further improve the performance of EDLCs. Computational methods offer immense scope in aiding the development of such materials. Trends in experimentally observed operative voltages nevertheless remain difficult to predict and understand. We discuss here the intriguing case of adiponitrile (ADN) versus 2-methyl-glutaronitrile (2MGN) based electrolytes, which result in very different operative voltages in EDLCs despite structural similarity. As a preliminary step, bulk electrolyte effects on electrochemical stability are investigated by ab initio molecular dynamics (AIMD) and static, cluster-based quantum chemistry calculations.

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.

The development of innovative electrolytes is a key aspect of improving electrochemical double layer capacitors (EDLCs). New solvents, new conducting salts as well as new ionic liquids need to be considered. To avoid time-consuming “trial and error” experiments, it is desirable to “rationalize” this search for new materials. An important step in this direction is the systematic application of computational screening approaches. Via the fast prediction of the properties of a large number of compounds, for instance all reasonable candidates within a given compound class, such approaches should allow to identify of the most promising candidates for subsequent experiments. In this work we consider the toy system of all reasonable nitrile solvents up to 12 heavy atoms. To investigate if our recently proposed computational screening strategy is a feasible tool for the purpose of rationalizing the search for new EDLC electrolyte materials, we correlate—in the case of EDLCs for the first time—computational screen...

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.

Computational screening of battery electrolyte components is an extremely challenging task because very complex features like solidelectrolyte-interphase (SEI) formation and graphite exfoliation need to be taken into account at least at the final screening stage. We present estimators for both SEI formation and graphite exfoliation based on a combinatorial approach with quantum chemistry calculations on model system reactions, which can be applied automatically for a large number of compounds and thus allows for a systematic first assessment of the relevant properties within screening approaches. Thermodynamic effects are assessed with quantum mechanical calculations, a more heuristic approach is used to estimate kinetic effects., Comment: Supplementary information available from martin.korth@uni-ulm.de

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.

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.

Diverse LiPF

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.

Author(s): Fechner, Uli; de Graaf, Chris; Torda, Andrew E; Gussregen, Stefan; Evers, Andreas; Matter, Hans; Hessler, Gerhard; Richmond, Nicola J; Schmidtke, Peter; Segler, Marwin HS; Waller, Mark P; Pleik, Stefanie; Shea, Joan-Emma; Levine, Zachary; Mullen, Ryan; van den Broek, Karina; Epple, Matthias; Kuhn, Hubert; Truszkowski, Andreas; Zielesny, Achim; Fraaije, Johannes Hans; Gracia, Ruben Serral; Kast, Stefan M; Bulusu, Krishna C; Bender, Andreas; Yosipof, Abraham; Nahum, Oren; Senderowitz, Hanoch; Krotzky, Timo; Schulz, Robert; Wolber, Gerhard; Bietz, Stefan; Rarey, Matthias; Zimmermann, Markus O; Lange, Andreas; Ruff, Manuel; Heidrich, Johannes; Onlia, Ionut; Exner, Thomas E; Boeckler, Frank M; Bermudez, Marcel; Firaha, Dzmitry S; Holloczki, Oldamur; Kirchner, Barbara; Tautermann, Christofer S; Volkamer, Andrea; Eid, Sameh; Turk, Samo; Rippmann, Friedrich; Fulle, Simone; Saleh, Noureldin; Saladino, Giorgio; Gervasio, Francesco L; Haensele, Elke; Banting, Lee; Whitley, David C; Oliveira Santos, Jana Sopkova-de; Bureau, Ronan; Clark, Timothy; Sandmann, Achim; Lanig, Harald; Kibies, Patrick; Heil, Jochen; Hoffgaard, Franziska; Frach, Roland; Engel, Julian; Smith, Steven; Basu, Debjit; Rauh, Daniel; Kohlbacher, Oliver; Boeckler, Frank M; Essex, Jonathan W; Bodnarchuk, Michael S; Ross, Gregory A; Finkelmann, Arndt R; Goller, Andreas H; Schneider, Gisbert; Husch, Tamara; Schutter, Christoph; Balducci, Andrea; Korth, Martin; Ntie-Kang, Fidele; Gunther, Stefan; Sippl, Wolfgang; Mbaze, Luc Meva'a

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.

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.

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.

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.

Computational modeling of biological systems is a rapidly evolving field that calls for methods that are able to allow for extensive sampling with systems consisting of thousands of atoms. Semiempirical quantum chemical (SE) methods are a promising tool to aid with this, but the rather bad performance of standard SE methods for noncovalent interactions is clearly a limiting factor. Enhancing SE methods with empirical corrections for dispersion and hydrogen-bonding interactions was found to be a big improvement, but for the hydrogen-bonding corrections the drawback of breaking down in the case of substantial changes to the hydrogen bond, e.g., proton transfer, posed a serious limitation for its general applicability. This work presents a further improved hydrogen-bonding correction that can be generally included in parameter fitting procedures, as it does not suffer from the conceptual flaws of previous approaches: hydrogen bonds are now treated as an interaction term between electronegative acceptor and d...

The reaction energies for 34 typical organic isomerizations including oxygen and nitrogen heteroatoms are investigated with modern quantum chemical methods that have the perspective of also being applicable to large systems. The experimental reaction enthalpies are corrected for vibrational and thermal effects, and the thus derived "experimental" reaction energies are compared to corresponding theoretical data. A series of standard AO basis sets in combination with second-order perturbation theory (MP2, SCS-MP2), conventional density functionals (e.g., PBE, TPSS, B3-LYP, MPW1K, BMK), and new perturbative functionals (B2-PLYP, mPW2-PLYP) are tested. In three cases, obvious errors of the experimental values could be detected, and accurate coupled-cluster [CCSD(T)] reference values have been used instead. It is found that only triple-zeta quality AO basis sets provide results close enough to the basis set limit and that sets like the popular 6-31G(d) should be avoided in accurate work. Augmentation of small basis sets with diffuse functions has a notable effect in B3-LYP calculations that is attributed to intramolecular basis set superposition error and covers basic deficiencies of the functional. The new methods based on perturbation theory (SCS-MP2, X2-PLYP) are found to be clearly superior to many other approaches; that is, they provide mean absolute deviations of less than 1.2 kcal mol-1 and only a few (10%) outliers. The best performance in the group of conventional functionals is found for the highly parametrized BMK hybrid meta-GGA. Contrary to accepted opinion, hybrid density functionals offer no real advantage over simple GGAs. For reasonably large AO basis sets, results of poor quality are obtained with the popular B3-LYP functional that cannot be recommended for thermochemical applications in organic chemistry. The results of this study are complementary to often used benchmarks based on atomization energies and should guide chemists in their search for accurate and efficient computational thermochemistry methods.

A diversity-oriented approach for the generation of thermochemical benchmark sets is presented. Test sets consisting of randomly generated "artificial molecules" (AMs) are proposed that rely on systematic constraints rather than uncontrolled chemical biases. In this way, the narrow structural space of chemical intuition is opened up and electronically difficult cases can be produced in an unforeseeable manner. For the calculation of chemically meaningful relative energies, AMs are systematically decomposed into small molecules (hydrides and diatomics). Two different example test sets containing eight-atom, single-reference, main group AMs with chemically very diverse and unusual structures are generated. Highly accurate all-electron, estimated CCSD(T)/complete basis set reference energies are also provided. They are used to benchmark the density functionals S-VWN, BP86, B-LYP, B97-D, PBE, TPSS, PBEh, BH-LYP, B3-PW91, B3-LYP, B2-PLYP, B2GP-PLYP, BMK, MPW1B95, M05, M05-2X, PW6B95, M06, M06-L, and M06-2X. In selected cases, an empirical dispersion correction (DFT-D) has been applied. Due to the composition of the sets, it is expected that a good performance indicates "robustness" in many different chemical applications. The results of a statistical analysis of the errors for the entire set with 165 entries (average reaction energy of 117 kcal/mol, dubbed as the MB08-165 set) perfectly fit to the "Jacob's ladder" metaphor for the ordering of density functionals according to their theoretical complexity. The mean absolute deviation (MAD) decreases very strongly from LDA (20 kcal/mol) to GGAs (MAD of about 10 kcal/mol) but then was less pronounced to hybrid-GGAs (MAD of about 6-8 kcal/mol). The best performance (MAD of 4.1-4.2 kcal/mol) is found for the (fifth-rung) double-hybrid functionals B2-PLYP-D and B2GP-PLYP-D, followed by the M06-2X meta-hybrid (MAD of 4.8 kcal/mol). The significance of the proposed approach for thermodynamic benchmarking is discussed and related to the observed performance ranking also regarding wave function based methods.

The Li-Air battery is a very promising candidate 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 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)., Comment: Supporting Information available from martin.korth@uni-ulm.de

The Hartree-Fock method, two common density functionals (PBE and B3LYP), and two new functionals (B97-D and B2PLYP) together with very large AO basis sets are used to compute the isomerization energies for substituted (R [Formula: see text] H, F, Cl) branched to linear alkanes and silanes. The results of accurate SCS-MP2 computations are taken as reference. These reactions are an important test of how nonlocal electron correlation effects on medium-range lengths scales in saturated molecules are treated by approximate quantum chemical methods. It is found that the unacceptably large errors observed previously for hydrocarbons persist also for the here considered more polar systems. Although the B97-D and B2PLYP functionals provide improved energetics, the problem is not fully solved, and thus these systems are suggested as mandatory benchmarks for future density functionals.

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.

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 $\ge$ 3 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.

Recent years have seen a large increase in research activities related with Lithium-ion battery technology. Current systems are critically dependent on the formation of passivating films at the solid/liquid interface, the so-called solid electrolyte interphase (SEI). We review here atomic-scale computational investigations into the formation of such layers, as well as SEI-related studies on solvation, intercalation, and electrolyte materials screening.

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.

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%.

In the state of the art electrochemical double layer capacitors (EDLCs), activated carbons (AC) are used as electrode active materials, while solutions of tetraethylammonium tetrafluroroborate (Et4NBF4) in propylene carbonate (PC) or acetonitrile (ACN) are used as electrolytes. These combinations of materials enable the realization of EDLCs with operative voltages of 2.7-2.8 V, extraordinary cycle life (>500.000 cycles), high power (up to 10 kW kg-1) and energy in the order of 5Whkg-1[1]. It has been shown that if the energy of EDLC could be increase up to 10Whkg-1 these devices could be introduced in many new applications, leading to a dramatic increase of their market [1]. For this reason, the development of high energy EDLCs is nowadays considered of crucial importance for the future of this technology. The most straightforward strategy to increase the EDLC´s energy is to increase their operative voltage. Since such desirable increase is not possible when the state-of-the-art electrolytes are used, the introduction of new electrolytic solution is presently consider of great importance [1]. To avoid time consuming “trial and error” experiments, it is desirable to “rationalize” this search for new electrolyte components. An important step in this direction is the systematic application of computational screening approaches. Via the fast prediction of the properties of a large number of compounds, for instance all reasonable candidates within a given compound class, such approaches should allow to identify of the most promising candidates for subsequent experiments [2]. In this paper we report about the use of computation screening for the identification of novel solvents for EDLCs. As an example application, the known chemical space of almost 70 million compounds is investigated in search of electrochemically more stable solvents. Cyano esters are identified as especially promising new compound class. As a matter of fact, the use of electrolytes containing cyano ester as solvent and Et4NBF4 as conductive salt allows for the realization of EDLCs with operative voltage as high as 3.5 V. These high voltage EDLCs display good performance in term of specific capacitance and capacitance retention. Furthermore, we showed that EDLCs containing this type of solvent are able to retain almost 80% of their initial capacitance after 500 h of float tests carried out at 3.2 V. This extraordinary capacitance retention, which is among the highest so far reported for high voltage EDLC, clearly indicate that cyano ester can be considered as a new and very interesting solvent in view of the realization of high voltage EDLC [3]. Taking these results into account, the use of computational screening appears as a very promising and novel strategy for a rational design of new electrolyte materials for EDLCs. It is important to remark that such approach can be applied not only to the search for new materials, but also to the optimization of mixtures and salt/solvent combinations. References [1] F. Béguin, V. Presser, A. Balducci, E. Frackowiak, Advanced Materials, 26 (2014) 2219-2251 [2] C. Schütter, T. Husch, M. Korth, A. Balducci, J. Phys. Chem. C 119 (2015) 13413. [3] C. Schütter, T. Husch, V.Viswanathan, S. Passerini, A.Balducci, M. Korth, submitted

State of the art electrolytes for lithium ion batteries (LIBs) consist of a lithium salt dissolved in a mixture of cyclic and linear carbonates, mainly using ethylene carbonate (EC), dimethyl carbonate (DMC) and/or diethyl carbonate (DEC). Notwithstanding many beneficial properties, e.g. high conductivity and low viscosity, the thermal operation window is limited especially in regards to low volatility and flammability. To overcome well-known drawbacks of carbonate based solvents, alternative solvents are desired to simultaneously expand the operating temperature range, improve the safety and maintain excellent electrochemical performance. As conductive salt, LiPF6 is still the lithium salt of choice. However, it suffers from drawbacks related to trace amounts of water as well as its decomposition at high temperatures. Lithium bistrifluoromethanesulfonimide (LiTFSI) represents a promising alternative salt for LIB technology to possibly overcome the aforementioned challenges. However, an additional challenge in LITFSI based electrolytes is set on the dissolution of the aluminum current collector at already moderate potential values (+) when using carbonate based solvents. The goal of our research was to develop new safer electrolyte formulation based on non-carbonate based single solvents with LiPF6 or LiTFSI as conducting salt. In this work, an ester functional group was introduced to the nitrile molecular structure to support salt dissociation and to enhance the compatibility towards lithium metal and graphite based anodes. The basic framework for the possible structures was either R1-COO-R2, whereas two different linkages of the nitrile moiety were possible. In the first one, nitrile functionality is positioned on the acid part of the ester, whereas in the second it is situated on the alcohol part. In order to select the best possible combination of ester and nitrile moieties, a computational screening by means of theoretical calculations of the main physical and electrochemical properties was preceded. Over 2000 possible structures were calculated in regards to important parameters namely viscosity and pkA value as well as the melting point. All possible molecules were divided into the two possible linkages. Methyl 3-cyanopropanoate (MCP) and, methyl 2-cyano-2-methylpropionate (MCMP) were identified as the two most promising candidates for the acid linkage. Two additional compounds, namely methyl cyanoacetate (MCA) and ethyl-2-cyano-2-methylpropionate (EMCP) were included for better evaluation of the results obtained by theoretical calculations. For the second possibility, three molecules were synthesized, namely 2-cyanoethyl acetate (CEA), 2-cyanoethyl 2,2,2-trifluoracetate (CFA) and 2-cyanopropan-2-yl acetate (CYA) as depicted in Figure 1. In the frame of this work, the newly proposed electrolyte solvents were analyzed in regards to their liquid window, viscosity and conductivity. In our study, a very good agreement between theoretical and experimental results was obtained. Additionally, all possible solvents were screened with respect to their compatibility to graphite based anodes. We found that it is necessary to use a film-forming additive. This study showed that possible acid linked candidate proved to be MCP and the best alcohol linked proved to be CEA, which were not the ideal candidates in regards to their physicochemical properties. After having identified the two most suitable candidates, experiments in full cell setups with 4 V cell chemistry were performed. As we used a single solvent approach, the obtained results were compared with 1 M LiPF6 in PC based electrolytes containing FEC as film forming additive and additionally to a state of the art electrolyte: 1 M LiPF6 in EC:DMC (1:1 by wt.). These experiments showed that at moderate cycling rates of 1 C the proposed electrolytes perform comparable to the carbonate based electrolytes. To further evaluate the thermal properties of the electrolytes, Heat-wait-search (HWS) tests were performed to determine the onset temperature value for a thermal runaway. Furthermore, the compatibility of MCP and CEA with the alternative conductive salt LiTFSI was investigated, showing that the cyanoester based solvents show negligible to no corrosion behavior on the aluminum current collector in comparison to the carbonate based solvents. In conclusion, we present a complete study obtained from selected theoretical calculations of a promising new class of solvents for the implementation of MCP and CEA in full cell set-up as possible alternative solvents for LiPF6 and LiTFSI. Comparable thermal and electrochemical behavior in comparison to a one solvent carbonate based system and better thermal behavior in comparison to a two solvent carbonate based system was recognized. Figure 1

Further development of high voltage lithium-ion batteries requires electrolyte formulations stable against oxidation or measures to generate a protective cathode/electrolyte interface (CEI) film. In the frame of this work, the actually counterintuitive concept of using metal ions as electrolyte additives to stabilize the CEI has proven to be successful. The addition of 1 wt% magnesium bis(trifluoromethanesulfonyl)imide (Mg(TFSI)2) as electrolyte additive to a conventional LiPF6/organic carbonate electrolyte suppresses the oxidative decomposition of the bulk electrolyte as displayed in improved capacity retention, increased Coulombic efficiencies, and reduced self-discharge of LiNi1/3Mn1/3Co1/3O2 (NMC111)/Li half cells charged to the elevated upper cutoff potential of 4.6 V versus Li/Li+ at 20 °C. Moreover, the addition of Mg(TFSI)2 shows no adverse effect on the cycling performance of graphite anodes, as observed by good long-term cycling results of NMC111/graphite full cells. Ex situ analysis via X-ray photoelectron spectroscopy, scanning electron microscopy, time-of-flight secondary ion mass spectrometry, and electron energy loss spectroscopy of the harvested NMC111 electrodes after cycling indicate that the addition of Mg2+ ions leads to the formation of a CEI layer as a result of an increased hydrolysis reaction of the PF6 – anion.

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.

Quantum Monte Carlo (QMC) calculations on the stacked (st) and Watson/Crick (wc) bound adenine/thymine (A/T) and cytosine/guanine (C/G) DNA base pair complexes were made possible with the first large scale distributed computing project in ab initio quantum chemistry, Quantum Monte Carlo at Home (QMC@HOME). The results for the interaction energies (wc-A/T = 15.7 kcal/mol, wc-C/G = 30.2 kcal/mol, st-A/T = 13.1 kcal/mol, st-C/G = 19.6 kcal/mol) are in very good agreement with the best known coupled-cluster based estimates. The accuracy of these values is further supported by calculations on the S22 benchmark set of noncovalently bound systems, for which we obtain a small mean absolute deviation of 0.68 kcal/mol. Our results support previous claims that the stacking energies are of comparable magnitude to the interactions of the commonly discussed hydrogen-bonded motif. Furthermore, we show that QMC can serve as an advantageous alternative to conventional wave function methods for large noncovalently bound systems. We also investigated in detail all technical parameters of the QMC simulations and recommend a careful optimization procedure of the Jastrow correlation factors in order to obtain numerically stable and reliable results.

The accurate prediction of the strength of protein–ligand interactions is a very difficult problem despite impressive advances in the field of biomolecular modeling. There are good reasons to believe that quantum mechanical methods can help with this task, but the application of such methods in the context of scoring is still in its infancy. Here we benchmark several wave function theory (WFT), density functional theory (DFT) and semiempirical quantum mechanical (SQM) approaches against high-level theoretical references for realistic test cases. Based on our findings for systematically generated model systems of real protein/ligand complexes from the PDB-bind database, we can recommend SCS-MP2 and B2-PLYP-D3 as reference methods, TPSS-D3+Dabc/def-TZVPP as the best DFT approach and PM6-DH+ as a fast and accurate alternative to full ab initio treatments.

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.

Enthalpy–entropy compensation phenomena are of high importance for processes with dominating non-covalent interactions, like protein–ligand binding. We show here that non-covalent interactions are compensated by entropic effects not on an equal footing, but dependent on their electronic nature. This insight helps us to understand the observed diversity of enthalpy–entropy compensation phenomena and opens up a new route for the prediction of the entropic effects of non-covalent binding.