Electrolyte Reactivity on the MgV2O4 Cathode Surface.

Predictive understanding of the molecular interaction of electrolyte ions and solvent molecules and their chemical reactivity on electrodes has been a major challenge but is essential for addressing instabilities and surface passivation that occur at the electrode-electrolyte interface of multivalent magnesium batteries. In this work, the isolated intrinsic reactivities of prominent chemical species present in magnesium bis(trifluoromethanesulfonimide) (Mg(TFSI)2) in diglyme (G2) electrolytes, including ionic (TFSI-, [Mg(TFSI)]+, [Mg(TFSI):G2]+, and [Mg(TFSI):2G2]+) as well as neutral molecules (G2) on a well-defined magnesium vanadate cathode (MgV2O4) surface, have been studied using a combination of first-principles calculations and multimodal spectroscopy analysis. Our calculations show that nonsolvated [Mg(TFSI)]+ is the strongest adsorbing species on the MgV2O4 surface compared with all other ions while partially solvated [Mg(TFSI):G2]+ is the most reactive species. The cleavage of C-S bonds in TFSI- to form CF3- is predicted to be the most desired pathway for all ionic species, which is followed by the cleavage of C-O bonds of G2 to yield CH3+ or OCH3- species. The strong stabilization and electron transfer between ionic electrolyte species and MgV2O4 is found to significantly favor these decomposition reactions on the surface compared with intrinsic gas-phase dissociation. Experimentally, we used state-of-the-art ion soft landing to selectively deposit mass-selected TFSI-, [Mg(TFSI):G2]+, and [Mg(TFSI):2G2]+ on a MgV2O4 thin film to form a well-defined electrolyte-MgV2O4 interface. Analysis of the soft-landed interface using X-ray photoelectron, X-ray absorption near-edge structure, electron energy-loss spectroscopies, as well as transmission electron microscopy confirmed the presence of decomposition species (e.g., MgFx, carbonates) and the higher amount of MgFx with [Mg(TFSI):G2]+ formed in the interfacial region, which corroborates the theoretical observation. Overall, these results indicate that Mg2+ desolvation results in electrolyte decomposition facilitated by surface adsorption, charge transfer, and the formation of passivating fluorides on the MgV2O4 cathode surface. This work provides the first evidence of the primary mechanisms leading to electrolyte decomposition at high-voltage oxide surfaces in multivalent batteries and suggests that the design of new, anodically stable electrolytes must target systems that facilitate cation desolvation.

Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning.

In previous work (Dandu et al., J. Phys. Chem. A, 2022, 126, 4528-4536), we were successful in predicting accurate atomization energies of organic molecules using machine learning (ML) models, obtaining an accuracy as low as 0.1 kcal/mol compared to the G4MP2 method. In this work, we extend the use of these ML models to adiabatic ionization potentials on data sets of energies generated using quantum chemical calculations. Atomic specific corrections that were found to improve atomization energies from quantum chemical calculations have also been used in this study to improve ionization potentials. The quantum chemical calculations were performed on 3405 molecules containing eight or fewer non-hydrogen atoms derived from the QM9 data set, using the B3LYP functional with the 6-31G(2df,p) basis set for optimization. Low-fidelity IPs for these structures were obtained using two density functional methods: B3LYP/6-31+G(2df,p) and ωB97XD/6-311+G(3df,2p). Highly accurate G4MP2 calculations were performed on these optimized structures to obtain high-fidelity IPs to use in ML models based on the low-fidelity IPs. Our best performing ML methods gave IPs of organic molecules within a mean absolute deviation of 0.035 eV from the G4MP2 IPs for the whole data set. This work demonstrates that ML predictions assisted by quantum chemical calculations can be used to successfully predict IPs of organic molecules for use in high throughput screening.

A room temperature rechargeable Li2O-based lithium-air battery enabled by a solid electrolyte.

A lithium-air battery based on lithium oxide (Li2O) formation can theoretically deliver an energy density that is comparable to that of gasoline. Lithium oxide formation involves a four-electron reaction that is more difficult to achieve than the one- and two-electron reaction processes that result in lithium superoxide (LiO2) and lithium peroxide (Li2O2), respectively. By using a composite polymer electrolyte based on Li10GeP2S12 nanoparticles embedded in a modified polyethylene oxide polymer matrix, we found that Li2O is the main product in a room temperature solid-state lithium-air battery. The battery is rechargeable for 1000 cycles with a low polarization gap and can operate at high rates. The four-electron reaction is enabled by a mixed ion-electron-conducting discharge product and its interface with air.

Computational Predictions of the Stability of Fluorinated Calcium Aluminate and Borate Salts.

Energy storage concepts based on multivalent ions, such as calcium, have great potential to become next-generation batteries due to their low cost and comparable cell voltage and energy density to Li-ion batteries. However, the development of Ca batteries is still hindered by the lack of suitable materials that grant a long cycle life. Specific to electrolyte materials, developing a calcium salt that is chemically stable under ambient conditions and enables reversible electrodeposition of Ca is critical. In this work, we use first-principles calculations to study the intrinsic and reductive stability of twelve Ca salts with fluorinated aluminate and borate anions and analyze the decomposition products formed on the metal anode surface that are critical to early-stage solid electrolyte interphase formation. We found anions with significant steric hindrance and a high degree of fluorination are intrinsically less stable and deemed unviable designs for Ca salt. Aluminate salts are generally less reactive with the Ca anode than their borate counterparts, and a high degree of fluorination leads to weaker reductive stability. Calcium fluoride is the most prominent decomposition product on the anode surface, and carbide-like motifs were also found from the decomposition of the designed salts.

A KMnO4-Generated Colloidal Electrolyte for Redox Mediation and Anode Protection in a Li-Air Battery.

The rechargeable lithium-oxygen (Li-O2) battery has the highest theoretical specific energy density of any rechargeable batteries and could transform energy storage systems if a practical device could be attained. However, among numerous challenges, which are all interconnected, are polarization due to sluggish kinetics, low cycle life, small capacity, and slow rates. In this study, we report on use of KMnO4 to generate a colloidal electrolyte made up of MnO2 nanoparticles. The resulting electrolyte provides a redox mediator for reducing the charge potential and lithium anode protection to increase cycle life. This electrolyte in combination with a stable binary transition metal dichalcogenide alloy, Nb0.5Ta0.5S2, as the cathode enables the operation of a Li-O2 battery at a current density of 1 mA·cm-2 and specific capacity ranging from 1000 to 10 000 mA·h·g-1 (corresponding to 0.1-1 mA·h·cm-2) in a dry air environment with a cycle life of up to 150. This colloidal electrolyte provides a robust approach for advancing Li-air batteries.

Improving the Accuracy of Composite Methods: A G4MP2 Method with G4-like Accuracy and Implications for Machine Learning.

G4MP2 theory has proven to be a reliable and accurate quantum chemical composite method for the calculation of molecular energies using an approximation based on second-order perturbation theory to lower computational costs compared to G4 theory. However, it has been found to have significantly increased errors when applied to larger organic molecules with 10 or more nonhydrogen atoms. We report here on an investigation of the cause of the failure of G4MP2 theory for such larger molecules. One source of error is found to be the "higher-level correction (HLC)", which is meant to correct for deficiencies in correlation contributions to the calculated energies. This is because the HLC assumes that the contribution is independent of the element and the type of bonding involved, both of which become more important with larger molecules. We address this problem by adding an atom-specific correction, dependent on atom type but not bond type, to the higher-level correction. We find that a G4MP2 method that incorporates this modification of the higher-level correction, referred to as G4MP2A, becomes as accurate as G4 theory (for computing enthalpies of formation) for a test set of molecules with less than 10 nonhydrogen atoms as well as a set with 10-14 such atoms, the set of molecules considered here, with a much lower computational cost. The G4MP2A method is also found to significantly improve ionization potentials and electron affinities. Finally, we implemented the G4MP2A energies in a machine learning method to predict molecular energies.

Graph-Based Approaches for Predicting Solvation Energy in Multiple Solvents: Open Datasets and Machine Learning Models.

The solvation properties of molecules, often estimated using quantum chemical simulations, are important in the synthesis of energy storage materials, drugs, and industrial chemicals. Here, we develop machine learning models of solvation energies to replace expensive quantum chemistry calculations with inexpensive-to-compute message-passing neural network models that require only the molecular graph as inputs. Our models are trained on a new database of solvation energies for 130,258 molecules taken from the QM9 dataset computed in five solvents (acetone, ethanol, acetonitrile, dimethyl sulfoxide, and water) via an implicit solvent model. Our best model achieves a mean absolute error of 0.5 kcal/mol for molecules with nine or fewer non-hydrogen atoms and 1 kcal/mol for molecules with between 10 and 14 non-hydrogen atoms. We make the entire dataset of 651,290 computed entries openly available and provide simple web and programmatic interfaces to enable others to run our solvation energy model on new molecules. This model calculates the solvation energies for molecules using only the SMILES string and also provides an estimate of whether each molecule is within the domain of applicability of our model. We envision that the dataset and models will provide the functionality needed for the rapid screening of large chemical spaces to discover improved molecules for many applications.

Theoretical evidence of water serving as a promoter for lithium superoxide disproportionation in Li-O2 batteries.

Experimental evidence has demonstrated that the presence of water in non-aqueous electrolytes significantly affects Li-O2 electrochemistry. Understanding the reaction mechanism for Li2O2 formation in the presence of water impurities is important to understand Li-O2 battery performance. A recent experiment has found that very small amounts of water (as low as 40 ppm) can significantly affect the product formation in Li-O2 batteries as opposed to essentially no water (1 ppm). Although experimental as well as theoretical work has proposed mechanisms of Li2O2 formation in the presence of much larger amounts of water, none of the mechanisms provide an explanation for the observations for very small amounts of water. In this work, density functional theory (DFT) was utilized to obtain a mechanistic understanding of the Li-O2 discharge chemistry in a dimethoxyethane (DME) electrolyte containing an isolated water and no water. The reaction pathways for Li2O2 formation from LiO2 on a model system were carefully evaluated with different level of theories, i.e. PBE (PW), B3LYP/6-31G(2df,p), B3LYP/6-311++G(2df,p) and G4MP2. The results indicate that the LiO2 disproportionation reaction to Li2O2 can be promoted by the water in DME electrolyte, which explains why there is a significant difference compared to when no water is present in the experimentally observed discharge product distributions. Ab initio molecular dynamics calculations were also used to investigate the disproportionation of LiO2 dimer in explicit DME. This work adds to the fundamental understanding of the discharge chemistry of a Li-O2 battery.

Origin of Unusual Acidity and Li+ Diffusivity in a Series of Water-in-Salt Electrolytes.

Superconcentrated aqueous electrolytes ("water-in-salt" electrolytes, or WiSEs) enable various aqueous battery chemistries beyond the voltage limits imposed by the Pourbaix diagram of water. However, their detailed structural and transport properties remain unexplored and could be better understood through added studies. Here, we report on our observations of strong acidity (pH 2.4) induced by lithium bis(trifluoromethane sulfonyl)imide (LiTFSI) at superconcentration (at 20 mol/kg). Multiple nuclear magnetic resonance (NMR) and pulsed-field gradient (PFG) diffusion NMR experiments, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations reveal that such acidity originates from the formation of nanometric ion-rich structures. The experimental and simulation results indicate the separation of water-rich and ion-rich domains at salt concentrations ≥5 m and the acidity arising therefrom is due to deprotonation of water molecules in the ion-rich domains. As such, the ion-rich domain is composed of hydrophobic -CF3 (of TFSI-) and hydrophilic hydroxyl (OH-) groups. At 20 m concentration, the tortuosity and radius of water diffusion channels are estimated to be ∼10 and ∼1 nm, respectively, which are close to values obtained from hydrated Nafion membranes that also have hydrophobic polytetrafluoroethylene (PTFE) backbones and hydrophilic channels consisting of SO3- ion cluster networks providing for the transport of ions and water. Thus, we have discovered the structural similarity between WiSE and hydrated Nafion membranes on the nanometer scale.

Quantum-Chemically Informed Machine Learning: Prediction of Energies of Organic Molecules with 10 to 14 Non-hydrogen Atoms.

High-fidelity quantum-chemical calculations can provide accurate predictions of molecular energies, but their high computational costs limit their utility, especially for larger molecules. We have shown in previous work that machine learning models trained on high-level quantum-chemical calculations (G4MP2) for organic molecules with one to nine non-hydrogen atoms can provide accurate predictions for other molecules of comparable size at much lower costs. Here we demonstrate that such models can also be used to effectively predict energies of molecules larger than those in the training set. To implement this strategy, we first established a set of 191 molecules with 10-14 non-hydrogen atoms having reliable experimental enthalpies of formation. We then assessed the accuracy of computed G4MP2 enthalpies of formation for these 191 molecules. The error in the G4MP2 results was somewhat larger than that for smaller molecules, and the reason for this increase is discussed. Two density functional methods, B3LYP and ωB97X-D, were also used on this set of molecules, with ωB97X-D found to perform better than B3LYP at predicting energies. The G4MP2 energies for the 191 molecules were then predicted using these two functionals with two machine learning methods, the FCHL-Δ and SchNet-Δ models, with the learning done on calculated energies of the one to nine non-hydrogen atom molecules. The better-performing model, FCHL-Δ, gave atomization energies of the 191 organic molecules with 10-14 non-hydrogen atoms within 0.4 kcal/mol of their G4MP2 energies. Thus, this work demonstrates that quantum-chemically informed machine learning can be used to successfully predict the energies of large organic molecules whose size is beyond that in the training set.

How do we know what we don't know? Exploring Deaf people's experiences of supporting their Deaf family member living with dementia.

Deaf sign language users living with dementia and their carers, some of whom are Deaf, routinely face everyday barriers in accessing information, support (both formal and informal) and services. The familial care situation is further complicated given that most Deaf people will choose a life partner who is Deaf and most Deaf couples will have hearing children. This study focussed specifically on the everyday experiences of Deaf carers and the impact of caring for a loved one with dementia. Drawing on data from a wider consultation about dementia care, three Deaf carers were directly interviewed in British Sign Language by a Deaf researcher about their everyday experiences of care, support, and services. Thematic analysis focussed on: access is more than the provision of interpreters; effective care for the carers; and unknowing risk taking. Findings demonstrate the multifaceted effects of barriers to knowledge and information when the care partner is also Deaf, the urgent need for effective support for Deaf carers and unrecognised safeguarding concerns that are a result of lack of access to forms of basic knowledge about living with someone with dementia and potential coping strategies. Nonetheless, the participants demonstrated novel solutions and resilience in the face of these multiple challenges. Implications are drawn for future targeted services to supported Deaf carers of people affected by dementia.

In Situ Formed Ir3Li Nanoparticles as Active Cathode Material in Li-Oxygen Batteries.

Lithium-oxygen (Li-O2) batteries are a promising class of rechargeable Li batteries with a potentially very high achievable energy density. One of the major challenges for Li-O2 batteries is the high charge overpotential, which results in a low energy efficiency. In this work size-selected subnanometer Ir clusters are used to investigate cathode materials that can help control lithium superoxide formation during discharge, which has good electronic conductivity needed for low charge potentials. It is found that Ir particles can lead to lithium superoxide formation as the discharge product with Ir particle sizes of ∼1.5 nm giving the lowest charge potentials. During discharge these 1.5 nm Ir nanoparticles surprisingly evolve to larger ones while incorporating Li to form core-shell structures with Ir3Li shells, which probably act as templates for growth of lithium superoxide during discharge. Various characterization techniques including DEMS, Raman, titration, and HRTEM are used to characterize the LiO2 discharge product and the evolution of the Ir nanoparticles. Density functional calculations are used to provide insight into the mechanism for formation of the core-shell Ir3Li particles. The in situ formed Ir3Li core-shell nanoparticles discovered here provide a new direction for active cathode materials that can reduce charge overpotentials in Li-O2 batteries.

Accurate quantum chemical energies for 133 000 organic molecules.

The energies of the 133 000 molecules in the GDB-9 database have been calculated at the G4MP2 level of theory and then were used to calculate their enthalpies of formation. This database contains organic molecules having nine or less atoms of carbon, nitrogen, oxygen, and fluorine, as well as hydrogen atoms. The accuracy of the G4MP2 energies was investigated on a subset of 459 of the molecules having experimental enthalpies of formation with small uncertainties. On this subset the G4MP2 enthalpies of formation have an accuracy of 0.79 kcal mol-1, which is similar to its accuracy previously reported for the smaller G3/05 test set. An error analysis of the theoretical enthalpies of formation of the 459 molecules is presented in terms of the size and type of the molecules. Three different density functionals (B3LYP, ωB97X-D, M06-2X) were also assessed on 459 molecules of accurate enthalpy data for comparison with the G4MP2 results. The G4MP2 energies for the 133 K molecules provide a database that can be used to calculate accurate reaction energies as well as to assess new or existing experimental enthalpies of formation. Several examples are given of types of reactions that can be predicted using the G4MP2 database of energies. The G4MP2 energies of the GDB-9 molecules will also be useful in future investigations of applications of machine learning to quantum chemical data.

A Long-Cycle-Life Lithium-CO2 Battery with Carbon Neutrality.

Lithium-CO2 batteries are attractive energy-storage systems for fulfilling the demand of future large-scale applications such as electric vehicles due to their high specific energy density. However, a major challenge with Li-CO2 batteries is to attain reversible formation and decomposition of the Li2 CO3 and carbon discharge products. A fully reversible Li-CO2 battery is developed with overall carbon neutrality using MoS2 nanoflakes as a cathode catalyst combined with an ionic liquid/dimethyl sulfoxide electrolyte. This combination of materials produces a multicomponent composite (Li2 CO3 /C) product. The battery shows a superior long cycle life of 500 for a fixed 500 mAh g-1 capacity per cycle, far exceeding the best cycling stability reported in Li-CO2 batteries. The long cycle life demonstrates that chemical transformations, making and breaking covalent CO bonds can be used in energy-storage systems. Theoretical calculations are used to deduce a mechanism for the reversible discharge/charge processes and explain how the carbon interface with Li2 CO3 provides the electronic conduction needed for the oxidation of Li2 CO3 and carbon to generate the CO2 on charge. This achievement paves the way for the use of CO2 in advanced energy-storage systems.

Deactivation of redox mediators in lithium-oxygen batteries by singlet oxygen.

Non-aqueous lithium-oxygen batteries cycle by forming lithium peroxide during discharge and oxidizing it during recharge. The significant problem of oxidizing the solid insulating lithium peroxide can greatly be facilitated by incorporating redox mediators that shuttle electron-holes between the porous substrate and lithium peroxide. Redox mediator stability is thus key for energy efficiency, reversibility, and cycle life. However, the gradual deactivation of redox mediators during repeated cycling has not conclusively been explained. Here, we show that organic redox mediators are predominantly decomposed by singlet oxygen that forms during cycling. Their reaction with superoxide, previously assumed to mainly trigger their degradation, peroxide, and dioxygen, is orders of magnitude slower in comparison. The reduced form of the mediator is markedly more reactive towards singlet oxygen than the oxidized form, from which we derive reaction mechanisms supported by density functional theory calculations. Redox mediators must thus be designed for stability against singlet oxygen.

Manipulation of Origin of Life Molecules: Recognizing Single-Molecule Conformations in ß-Carotene and Chlorophyll-a/ß-Carotene Clusters.

Carotenoids and chlorophyll are essential parts of plant leaves and are involved in photosynthesis, a vital biological process responsible for the origin of life on Earth. Here, we investigate how ß-carotene and chlorophyll-a form mixed molecular phases on a Au(111) surface using low-temperature scanning tunneling microscopy and molecular manipulation at the single-molecule level supported by density functional theory calculations. By isolating individual molecules from nanoscale molecular clusters with a scanning tunneling microscope tip, we are able to identify five ß-carotene conformations including a structure exhibiting a three-dimensional conformation. Furthermore, molecular resolution images enable direct visualization of ß-carotene/chlorophyll-a clsuters, with intimate structural details highlighting how they pair: ß-carotene preferentially positions next to chlorophyll-a and induces switching of chlorophyll-a from straight to several bent tail conformations in the molecular clusters.

Role of Manganese Deposition on Graphite in the Capacity Fading of Lithium Ion Batteries.

Lithium ion batteries utilizing manganese-based cathodes have received considerable interest in recent years for their lower cost and more favorable environmental friendliness relative to their cobalt counterparts. However, Li ion batteries using these cathodes combined with graphite anodes suffer from severe capacity fading at high operating temperatures. In this paper, we report on how the dissolution of manganese impacts the capacity fading within the Li ion batteries. Our investigation reveals that the manganese dissolves from the cathode, transports to the graphite electrode, and deposits onto the outer surface of the innermost solid-electrolyte interphase layer, which is known to be a mixture of inorganic salts (e.g., Li2CO3, LiF, and Li2O). In this location, the manganese facilitates the reduction of the electrolyte and the subsequent formation of lithium-containing products on the graphite, which removes lithium ions from the normal operation of the cell and thereby induces the severe capacity fade.

An atomistically informed mesoscale model for growth and coarsening during discharge in lithium-oxygen batteries.

An atomistically informed mesoscale model is developed for the deposition of a discharge product in a Li-O2 battery. This mescocale model includes particle growth and coarsening as well as a simplified nucleation model. The model involves LiO2 formation through reaction of O2(-) and Li(+) in the electrolyte, which deposits on the cathode surface when the LiO2 concentration reaches supersaturation in the electrolyte. A reaction-diffusion (rate-equation) model is used to describe the processes occurring in the electrolyte and a phase-field model is used to capture microstructural evolution. This model predicts that coarsening, in which large particles grow and small ones disappear, has a substantial effect on the size distribution of the LiO2 particles during the discharge process. The size evolution during discharge is the result of the interplay between this coarsening process and particle growth. The growth through continued deposition of LiO2 has the effect of causing large particles to grow ever faster while delaying the dissolution of small particles. The predicted size evolution is consistent with experimental results for a previously reported cathode material based on activated carbon during discharge and when it is at rest, although kinetic factors need to be included. The approach described in this paper synergistically combines models on different length scales with experimental observations and should have applications in studying other related discharge processes, such as Li2O2 deposition, in Li-O2 batteries and nucleation and growth in Li-S batteries.

Effect of the size-selective silver clusters on lithium peroxide morphology in lithium-oxygen batteries.

Lithium-oxygen batteries have the potential needed for long-range electric vehicles, but the charge and discharge chemistries are complex and not well understood. The active sites on cathode surfaces and their role in electrochemical reactions in aprotic lithium-oxygen cells are difficult to ascertain because the exact nature of the sites is unknown. Here we report the deposition of subnanometre silver clusters of exact size and number of atoms on passivated carbon to study the discharge process in lithium-oxygen cells. The results reveal dramatically different morphologies of the electrochemically grown lithium peroxide dependent on the size of the clusters. This dependence is found to be due to the influence of the cluster size on the formation mechanism, which also affects the charge process. The results of this study suggest that precise control of subnanometre surface structure on cathodes can be used as a means to improve the performance of lithium-oxygen cells.

Structure and Stability of Lithium Superoxide Clusters and Relevance to Li-O2 Batteries.

The discharge mechanism of a Li-O2 battery involves lithium superoxide (LiO2) radicals. In this Letter, we have performed high-level quantum chemical calculations (G4MP2) to investigate the structure and stability of LiO2 clusters. The clusters have planar ring-shaped structures, high spins, and are thermodynamically more stable than LiO2 dimer. The computed energy barrier for disproportionation of the larger clusters is also significantly higher than the corresponding barrier in the LiO2 dimer (1.0 eV vs 0.5 eV). This means that disproportionation rate should be much slower if the reaction involves LiO2 clusters other than the dimer. As a result, the clusters may survive long enough to be incorporated into the growing discharge product. These results are discussed in terms of recent experimental studies of the electronic structure and morphology of the discharge products in Li-air batteries.