Discovery of lead quinone cathode materials for Li-ion batteries.

Organic cathode materials are attractive candidates for the development of high-performance Li-ion batteries (LIBs). The chemical space of candidate molecules is too vast to be explored solely by experiments; however, it can be systematically explored by a high-throughput computational search that incorporates a spectrum of screening techniques. Here, we present a time- and resource-efficient computational scheme that incorporates machine learning and semi-empirical quantum mechanical methods to study the chemical space of approximately 200 000 quinone-based molecules for use as cathode materials in LIBs. By performing an automated search on a commercial vendor database, computing battery-relevant properties such as redox potential, gravimetric charge capacity, gravimetric energy density, and synthetic complexity score, and evaluating the structural integrity upon the lithiation process, a total of 349 molecules were identified as potentially high-performing cathode materials for LIBs. The chemical space of the screened candidates was visualized using dimensionality reduction methods with the aim of further downselecting the best candidates for experimental validation. One such directly purchasable candidate, 1,4,9,10-anthracenetetraone, was analyzed through cyclic voltammetry experiments. The measured redox potentials of the two lithiation steps, , of 3.3 and 2.4 V, were in good agreement with the predicted redox potentials, , of 3.2 and 2.3 V vs. Li/Li+, respectively. Lastly, to lay out the principles for rational design of quinone-based cathode materials beyond the current work, we constructed and discussed the quantitative structure property relationships of quinones based on the data generated from the calculations.

Copper Site Motion Promotes Catalytic NOx Reduction under Zeolite Confinement.

Ammonia-mediated selective catalytic reduction (NH3-SCR) is currently the key approach to abate nitrogen oxides (NOx) emitted from heavy-duty lean-burn vehicles. The state-of-art NH3-SCR catalysts, namely, copper ion-exchanged chabazite (Cu-CHA) zeolites, perform rather poorly at low temperatures (below 200 °C) and are thus incapable of eliminating effectively NOx emissions under cold-start conditions. Here, we demonstrate a significant promotion of low-temperature NOx reduction by reinforcing the dynamic motion of zeolite-confined Cu sites during NH3-SCR. Combining complex impedance-based in situ spectroscopy (IS) and extended density-functional tight-binding molecular dynamics simulation, we revealed an environment- and temperature-dependent nature of the dynamic Cu motion within the zeolite lattice. Further coupling in situ IS with infrared spectroscopy allows us to unravel the critical role of monovalent Cu in the overall Cu mobility at a molecular level. Based on these mechanistic understandings, we elicit a boost of NOx reduction below 200 °C by reinforcing the dynamic Cu motion in various Cu-zeolites (Cu-CHA, Cu-ZSM-5, Cu-Beta, etc.) via facile postsynthesis treatments, either in a reductive mixture at low temperatures (below 250 °C) or in a nonoxidative atmosphere at high temperatures (above 450 °C).

Revealing the Formation and Reactivity of Cage-Confined Cu Pairs in Catalytic NOx Reduction over Cu-SSZ-13 Zeolites by In Situ UV-Vis Spectroscopy and Time-Dependent DFT Calculation.

The low-temperature mechanism of chabazite-type small-pore Cu-SSZ-13 zeolite, a state-of-the-art catalyst for ammonia-assisted selective reduction (NH3-SCR) of toxic NOx pollutants from heavy-duty vehicles, remains a debate and needs to be clarified for further improvement of NH3-SCR performance. In this study, we established experimental protocols to follow the dynamic redox cycling (i.e., CuII ↔ CuI) of Cu sites in Cu-SSZ-13 during low-temperature NH3-SCR catalysis by in situ ultraviolet-visible spectroscopy and in situ infrared spectroscopy. Further integrating the in situ spectroscopic observations with time-dependent density functional theory calculations allows us to identify two cage-confined transient states, namely, the O2-bridged Cu dimers (i.e., µ-η2:η2-peroxodiamino dicopper) and the proximately paired, chemically nonbonded CuI(NH3)2 sites, and to confirm the CuI(NH3)2 pair as a precursor to the O2-bridged Cu dimer. Comparative transient experiments reveal a particularly high reactivity of the CuI(NH3)2 pairs for NO-to-N2 reduction at low temperatures. Our study demonstrates direct experimental evidence for the transient formation and high reactivity of proximately paired CuI sites under zeolite confinement and provides new insights into the monomeric-to-dimeric Cu transformation for completing the Cu redox cycle in low-temperature NH3-SCR catalysis over Cu-SSZ-13.

RedDB, a computational database of electroactive molecules for aqueous redox flow batteries.

An increasing number of electroactive compounds have recently been explored for their use in high-performance redox flow batteries for grid-scale energy storage. Given the vast and highly diverse chemical space of the candidate compounds, it is alluring to access their physicochemical properties in a speedy way. High-throughput virtual screening approaches, which use powerful combinatorial techniques for systematic enumerations of large virtual chemical libraries and respective property evaluations, are indispensable tools for an agile exploration of the designated chemical space. Herein, RedDB: a computational database that contains 31,618 molecules from two prominent classes of organic electroactive compounds, quinones and aza-aromatics, has been presented. RedDB incorporates miscellaneous physicochemical property information of the compounds that can potentially be employed as battery performance descriptors. RedDB's development steps, including: (i) chemical library generation, (ii) molecular property prediction based on quantum chemical calculations, (iii) aqueous solubility prediction using machine learning, and (iv) data processing and database creation, have been described.

A quantitative evaluation of computational methods to accelerate the study of alloxazine-derived electroactive compounds for energy storage.

Alloxazines are a promising class of organic electroactive compounds for application in aqueous redox flow batteries (ARFBs), whose redox properties need to be tuned further for higher performance. High-throughput computational screening (HTCS) enables rational and time-efficient study of energy storage compounds. We compared the performance of computational chemistry methods, including the force field based molecular mechanics, semi-empirical quantum mechanics, density functional tight binding, and density functional theory, on the basis of their accuracy and computational cost in predicting the redox potentials of alloxazines. Various energy-based descriptors, including the redox reaction energies and the frontier orbital energies of the reactant and product molecules, were considered. We found that the lowest unoccupied molecular orbital (LUMO) energy of the reactant molecules is the best performing chemical descriptor for alloxazines, which is in contrast to other classes of energy storage compounds, such as quinones that we reported earlier. Notably, we present a flexible in silico approach to accelerate both the singly and the HTCS studies, therewithal considering the level of accuracy versus measured electrochemical data, which is readily applicable for the discovery of alloxazine-derived organic compounds for energy storage in ARFBs.

Comparison of computational chemistry methods for the discovery of quinone-based electroactive compounds for energy storage.

High-throughput computational screening (HTCS) is a powerful approach for the rational and time-efficient design of electroactive compounds. The effectiveness of HTCS is dependent on accuracy and speed at which the performance descriptors can be estimated for possibly millions of candidate compounds. Here, a systematic evaluation of computational methods, including force field (FF), semi-empirical quantum mechanics (SEQM), density functional based tight binding (DFTB), and density functional theory (DFT), is performed on the basis of their accuracy in predicting the redox potentials of redox-active organic compounds. Geometry optimizations at low-level theories followed by single point energy (SPE) DFT calculations that include an implicit solvation model are found to offer equipollent accuracy as the high-level DFT methods, albeit at significantly lower computational costs. Effects of implicit solvation on molecular geometries and SPEs, and their overall effects on the prediction accuracy of redox potentials are analyzed in view of computational cost versus prediction accuracy, which outlines the best choice of methods corresponding to a desired level of accuracy. The modular computational approach is applicable for accelerating the virtual studies on functional quinones and the respective discovery of candidate compounds for energy storage.

AqSolDB, a curated reference set of aqueous solubility and 2D descriptors for a diverse set of compounds.

Water is a ubiquitous solvent in chemistry and life. It is therefore no surprise that the aqueous solubility of compounds has a key role in various domains, including but not limited to drug discovery, paint, coating, and battery materials design. Measurement and prediction of aqueous solubility is a complex and prevailing challenge in chemistry. For the latter, different data-driven prediction models have recently been developed to augment the physics-based modeling approaches. To construct accurate data-driven estimation models, it is essential that the underlying experimental calibration data used by these models is of high fidelity and quality. Existing solubility datasets show variance in the chemical space of compounds covered, measurement methods, experimental conditions, but also in the non-standard representations, size, and accessibility of data. To address this problem, we generated a new database of compounds, AqSolDB, by merging a total of nine different aqueous solubility datasets, curating the merged data, standardizing and validating the compound representation formats, marking with reliability labels, and providing 2D descriptors of compounds as a Supplementary Resource.

Mechanistic Understanding of Cu-CHA Catalyst as Sensor for Direct NH3-SCR Monitoring: The Role of Cu Mobility.

The concept to utilize a catalyst directly as a sensor is fundamentally and technically attractive for a number of catalytic applications, in particular, for the catalytic abatement of automotive emission. Here, we explore the potential of microporous copper-exchanged chabazite (Cu-CHA, including Cu-SSZ-13 and Cu-SAPO-34) zeolite catalysts, which are used commercially in the selective catalytic reduction of automotive nitrogen oxide emission by NH3 (NH3-SCR), as impedance sensor elements to monitor directly the NH3-SCR process. The NH3-SCR sensing behavior of commercial Cu-SSZ-13 and Cu-SAPO-34 catalysts at typical reaction temperatures (i.e., 200 and 350 °C) was evaluated according to the change of ionic conductivity and was mechanistically investigated by complex impedance-based in situ modulus spectroscopy. Short-range (local) movement of Cu ions within the zeolite structure was found to determine largely the NH3-SCR sensing behavior of both catalysts. Formation of NH3-solvated, highly mobile CuI species showed a predominant influence on the ionic conductivity of both catalysts and, consequently, hindered NH3-SCR sensing at 200 °C. Density functional theory calculations over a model Cu-SAPO-34 system revealed that CuII reduction to CuI by coadsorbed NH3 and NO weakened significantly the coordination of the Cu site to the CHA framework, enabling high mobility of CuI species that influences substantially the NH3-SCR sensing. The in situ spectroscopic and theoretical investigations not only unveil the mechanisms of Cu-CHA catalyst as sensor elements for direct NH3-SCR monitoring but also allow us to get insights into the speciation of active Cu sites in NH3-SCR under different reaction conditions with varied temperatures and gas compositions.

Electrochemical and Electronic Charge Transport Properties of Ni-Doped LiMn2O4 Spinel Obtained from Polyol-Mediated Synthesis.

LiNi0.5Mn1.5O4 (LNMO) spinel has been extensively investigated as one of the most promising high-voltage cathode candidates for lithium-ion batteries. The electrochemical performance of LNMO, especially its rate performance, seems to be governed by its crystallographic structure, which is strongly influenced by the preparation methods. Conventionally, LNMO materials are prepared via solid-state reactions, which typically lead to microscaled particles with only limited control over the particle size and morphology. In this work, we prepared Ni-doped LiMn2O4 (LMO) spinel via the polyol method. The cycling stability and rate capability of the synthesized material are found to be comparable to the ones reported in literature. Furthermore, its electronic charge transport properties were investigated by local electrical transport measurements on individual particles by means of a nanorobotics setup in a scanning electron microscope, as well as by performing DFT calculations. We found that the scarcity of Mn3+ in the LNMO leads to a significant decrease in electronic conductivity as compared to undoped LMO, which had no obvious effect on the rate capability of the two materials. Our results suggest that the rate capability of LNMO and LMO materials is not limited by the electronic conductivity of the fully lithiated materials.

Towards Synergistic Electrode-Electrolyte Design Principles for Nonaqueous Li-O[Formula: see text] batteries.

One route toward sustainable land and aerial transportation is based on electrified vehicles. To enable electrification in transportation, there is a need for high-energy-density batteries, and this has led to an enormous interest in lithium-oxygen batteries. Several critical challenges remain with respect to realizing a practical lithium-oxygen battery. In this article, we present a detailed overview of theoretical efforts to formulate design principles for identifying stable electrolytes and electrodes with the desired functionality and stability. We discuss design principles relating to electrolytes and the additional stability challenges that arise at the cathode-electrolyte interface. Based on a thermodynamic analysis, we discuss two important requirements for the cathode: the ability to nucleate the desired discharge product, Li[Formula: see text]O[Formula: see text], and the ability to selectively activate only this discharge product while suppressing lithium oxide, the undesired secondary discharge product. We propose preliminary guidelines for determining the chemical stability of the electrode and illustrate the challenge associated with electrode selection using the examples of carbon cathodes and transition metals. We believe that a synergistic design framework for identifying electrolyte-electrode formulations is needed to realize a practical Li-O[Formula: see text] battery.

Elucidation and Comparison of the Effect of LiTFSI and LiNO3 Salts on Discharge Chemistry in Nonaqueous Li-O2 Batteries.

The role of lithium salts in determining the discharge capacity of Li-O2 batteries has been highlighted in several recent studies; however, questions pertaining to their effect on the cathode surface and in the solution phase still remain unanswered. We conducted galvanostatic discharge experiments with different compositions of a binary mixture of 1 M of LiNO3 and LiTFSI in tetraglyme (TEGDME) as the electrolyte and analyzed the discharge products using techniques such as FT-IR, Raman spectroscopy, and SEM. It was observed that there is a nonlinear correlation between the electrolyte composition and the first discharge capacity, with the highest discharge capacity achieved with the electrolyte composition as 0.75 M LiNO3 and 0.25 M LiTFSI. The ID/IG values obtained from Raman spectroscopy, which represent the degree of order in the carbon cathode surface, were found to be correlated to the measured capacity. Our results indicate that at concentrations of LiNO3 higher than 0.75 M in the electrolyte, nitrogen doping of the carbon surface reaches a critical limit, beyond which it becomes unfavorable for the discharge process. On the other hand, decomposition of the electrolyte and formation of an amorphous layer on the cathode surface was found to intensify with increasing LiTFSI concentration. Our results show that the maximum discharge capacity of the cells is strongly dependent on the surface structure of the carbon cathode, which in turn is heavily influenced by the electrolyte composition. Classical molecular dynamics simulations of the same system indicated no such nonlinearity in the co-ordination of Li+ ions with respect to electrolyte composition, indicating that the ionic association strength of the anion may have only a limited effect.

Evidence of Porphyrin-Like Structures in Natural Melanin Pigments Using Electrochemical Fingerprinting.

Eumelanins are extended heterogeneous biopolymers composed of molecular subunits with ambiguous macromolecular topology. Here, an electrochemical fingerprinting technique is described, which suggests that natural eumelanin pigments contain indole-based tetramers that are arranged into porphyrin-like domains. Spectroscopy and density functional theory calculations suggest that sodium ions undergo occupancy-dependent stepwise insertion into the core of porphyrin-like tetramers in natural eumelanins at discrete potentials.

Trade-Offs in Capacity and Rechargeability in Nonaqueous Li-O2 Batteries: Solution-Driven Growth versus Nucleophilic Stability.

The development of high-capacity rechargeable Li-O2 batteries requires the identification of stable solvents that can promote a solution-based discharge mechanism, which has been shown to result in higher discharge capacities. Solution-driven discharge product growth requires dissolution of the adsorbed intermediate LiO2*, thus generating solvated Li+ and O2(-) ions. Such a mechanism is possible in solvents with high Gutmann donor or acceptor numbers. However, O2(-) is a strong nucleophile and is known to attack solvents via proton/hydrogen abstraction or substitution. This kind of a parasitic process is extremely detrimental to the battery's rechargeability. In this work, we develop a thermodynamic model to describe these two effects and demonstrate an anticorrelation between solvents' stability and their ability to enhance capacity via solution-mediated discharge product growth. We analyze the commonly used solvents in the same framework and describe why solvents that can promote higher discharge capacity are also prone to degradation. Solvating additives for practical Li-O2 batteries will have to be outliers to this observed anticorrelation.

Enhancing electrochemical intermediate solvation through electrolyte anion selection to increase nonaqueous Li-O2 battery capacity.

Among the "beyond Li-ion" battery chemistries, nonaqueous Li-O2 batteries have the highest theoretical specific energy and, as a result, have attracted significant research attention over the past decade. A critical scientific challenge facing nonaqueous Li-O2 batteries is the electronically insulating nature of the primary discharge product, lithium peroxide, which passivates the battery cathode as it is formed, leading to low ultimate cell capacities. Recently, strategies to enhance solubility to circumvent this issue have been reported, but rely upon electrolyte formulations that further decrease the overall electrochemical stability of the system, thereby deleteriously affecting battery rechargeability. In this study, we report that a significant enhancement (greater than fourfold) in Li-O2 cell capacity is possible by appropriately selecting the salt anion in the electrolyte solution. Using (7)Li NMR and modeling, we confirm that this improvement is a result of enhanced Li(+) stability in solution, which, in turn, induces solubility of the intermediate to Li2O2 formation. Using this strategy, the challenging task of identifying an electrolyte solvent that possesses the anticorrelated properties of high intermediate solubility and solvent stability is alleviated, potentially providing a pathway to develop an electrolyte that affords both high capacity and rechargeability. We believe the model and strategy presented here will be generally useful to enhance Coulombic efficiency in many electrochemical systems (e.g., Li-S batteries) where improving intermediate stability in solution could induce desired mechanisms of product formation.

Identifying Descriptors for Solvent Stability in Nonaqueous Li-O2 Batteries.

One crucial challenge in developing rechargeable Li-O2 batteries is to identify a stable solvent that is resistant to decomposition in the electrochemical environment of Li2O2. We attempt to identify descriptors that could be used to test for solvent stability. We build on the recent quantitative experimental results on oxygen consumption and release during discharge and charge respectively. We limit our focus to understanding trends in oxidative stability of solvents and based on a systematic treatment of the electrochemical environment of Li2O2, we propose that, to a first approximation, the highest occupied molecular orbital (HOMO) level could be a good descriptor. We demonstrate that this descriptor correlates well with the experimentally measured degree of rechargeability. We utilize this descriptor to screen a large number of solvents and identify several solvents that could enhance the rechargeability of nonaqueous Li-O2 batteries. We provide a comprehensive compilation of available computational and experimental data of several key solvent parameters that we believe will be the genesis for an 'electrolyte genome'.

Solvent Degradation in Nonaqueous Li-O2 Batteries: Oxidative Stability versus H-Abstraction.

Developing rechargeable Li-O2 batteries hinges on identifying stable solvents resistant to decomposition. Here, we focus on solvent stability against adsorption-induced H-abstraction during discharge. Using a detailed thermodynamic analysis, we show that a solvent's propensity to resist H-abstraction is determined by its acid dissociation constant, pKa, in its own environment. Upon surveying hundreds of solvents for their pKa values in different media, we find linear correlations between the pKa values across various classes of solvents in any two given media. Utilizing these correlations, we choose DMSO as the common standard to compare the relative stability trends. We construct a stability plot based on the solvent's HOMO level and its pKa in DMSO, which reveals that most solvents obey a correlation where solvents with lower HOMO levels tend to have lower pKa values in DMSO. However, this is at odds with the stability requirement that demands deep HOMO levels and high pKa values. Thus, stable solvents need to be outliers to this observed correlation.