Anode-free solid-state batteries contain no active material at the negative electrode in the as-manufactured state, yielding high energy densities for use in long-range electric vehicles. The mechanisms governing charge–discharge cycling of anode-free batteries are largely controlled by electro-chemo-mechanical phenomena at solid–solid interfaces, and there are important mechanistic differences when compared with conventional lithium-excess batteries. This Perspective provides an overview of the factors governing lithium nucleation, growth, stripping and cycling in anode-free solid-state batteries, including mechanical deformation of lithium, the chemical and mechanical properties of the current collector, microstructural effects, and stripping dynamics. Pathways for engineering interfaces to maximize performance and extend battery lifetime are discussed. We end with critical research questions to pursue, including understanding behaviour at low stack pressure, tailoring interphase growth, and engineering current collectors and interlayers. Anode-free batteries contain no active material at the negative electrode when manufactured, and this can enable them to have high energy density. This Perspective presents a critical overview of the mechanisms governing the behaviour of anode-free solid-state batteries and provides guidance to improve this type of battery.

Magnesium-ion batteries hold the potential to outperform the energy density of lithium-ion batteries, given the divalent charge carried by each Mg2+ cation, but remain in an early stage of development. Here, 25Mg solid-state nuclear magnetic resonance (ssNMR) is used to gain insight into the local structure and Mg-ion dynamics of candidate Mg-ion solid electrolytes, the antiperovskites Mg3SbN and Mg3AsN. Using the highest available magnetic field (35.2 T) for high-resolution solid-state NMR, the largest 25Mg quadrupole coupling constants (CQ) yet measured of up to 22 MHz are reported and corroborated by first-principles calculations. Predicted CQ values are shown to correlate with the antiperovskite's tolerance factor; thus, 25Mg NMR linewidths can report on lattice distortions and phase stability of these antiperovskites. Variable-temperature 25Mg NMR spectra demonstrate changes at elevated temperatures, ascribed to Mg-ion motional effects. 25Mg T1 relaxometry measurements at ultrahigh field reveal a lower activation energy for the more distorted Mg3AsN phase, matching computational predictions of a lower energy barrier for Mg2+ ion migration and suggesting that additional scrutiny of antiperovskites as Mg-ion conductors is warranted. Given the inherent challenges of 25Mg NMR, this work demonstrates the benefits of combining ultrahigh field NMR spectroscopy, advanced pulse sequences, modern signal processing, and first-principles calculations to facilitate NMR of quadrupolar nuclei as a tool to probe the local structure and ion dynamics in beyond-Li battery materials.

A machine learning (ML) model is developed for predicting useable methane (CH4) capacities in metal-organic frameworks (MOFs). The model applies to a wide variety of MOFs, including those with and without open metal sites, and predicts capacities for multiple pressure swing conditions. Despite its wider applicability, the model requires only 5 measurable structural features as input, yet achieves accuracies that surpass less-general models. Application of the model to a database of more than a million hypothetical MOFs identified several hundred whose capacities surpass that of the benchmark MOF, UMCM-152. Guided by the computational predictions, one of the promising candidates, UMCM-153, was synthesized and demonstrated to achieve superior volumetric capacity for CH4. Feature importance analyses reveal that pore volume and gravimetric surface area are the most important features for predicting CH4 capacity in MOFs. Finally, a reverse ML model is demonstrated. This model predicts the set of elementary MOF structural properties needed to achieve a desired CH4 capacity for a prescribed operating condition.

A significant challenge hindering the development of batteries based on the redox of multivalent ions is the sluggish mobility of such ions in most solids. Computational methods for efficiently predicting conductivity can accelerate the discovery of faster ion conductors. Direct first-principles calculations of conductivity are expensive and difficult to automate, which has prompted a search for other properties related to conductivity that are easier to calculate or measure. Previous studies have identified features related to the electronic charge density and phonon spectrum that are correlated with energy barriers for ion migration in monovalent conductors. Results from our first-principles simulations demonstrate that these features are not well correlated with energy barriers for multivalent ion migration. I will discuss potential reasons for this lack of correlation and propose modifications that are found to improve correlations. These findings quantify the promise of using such features to efficiently screen for better multivalent ion conductors. Figure 1

3D-framework Prussian blue analogues (PBAs) are appealing as a cost-effective, sustainable cathodes for Na-ion batteries. However, the aqueous-based synthesis of PBAs inherently introduces three different forms of water molecules (surface, interstitial and crystal) into the structure. Removal of water molecules causes phase transformation from monoclinic (M) to rhombohedral (R). This work presents the effects of water molecules on the structure before the phase transformation temperature, employing two promising PBA cathodes, Na2Fe[Fe(CN)6]1.69H2O and Na2Mn[Fe(CN)6]1.76H2O. Specifically, the water molecules impact the molecular interactions at the local structure and the electrochemical properties. This work has performed calculations on low-vacancy Na2M[Fe(CN)6] PBAs (where M = Mn, Fe, Co, Ni and Cu) to understand the dehydration energy. Employing in situ high-temperature X-ray diffraction and Raman spectroscopy, this work observes that water removal induces negative thermal expansion and stronger interactions between C equivalent to N and Na ions, resulting in biphasic reactions with sluggish kinetics. Additionally, water molecules play a role in maintaining the open 3D tunnels and facilitating a solid-solution like insertion of Na ions. Calculated phonon-Raman spectra provide insights into cyanide group deformations, revealing the interactions between water molecules, alkali-ions, and transition-metal ions. This study enhances the understanding of the relationship among electronic, vibrational, and electrochemical properties. The interaction of water molecules and their influence on the electrochemistry of Prussian blue analogues are presented. The hydration behavior of these materials is rapid, emphasizing their sensitivity to water molecules and the necessity for controlled electrode processing. The interstitial water molecules assist a solid-solution type insertion of Na ions. image

Evaluation of metal-organic frameworks (MOFs) for adsorbed natural gas (ANG) technology employs pure methane as a surrogate for natural gas (NG). This approximation is problematic, as it ignores the impact of other heavier hydrocarbons present in NG, such as ethane and propane, which generally have more favorable adsorption interactions with MOFs compared to methane. Herein, using quantitative Raman spectroscopic analysis and Monte Carlo calculations, we demonstrate the adsorption selectivity of high-performing MOFs, such as MOF-5, MOF-177, and SNU-70, for a methane and ethane mixture (95:5) that mimics the composition of NG. The impact of selectivity on the storage and deliverable capacities of these adsorbents during successive cycles of adsorption and desorption, simulating the filling and emptying of an ANG tank, is also demonstrated. The study reveals a gradual reduction in the storage performance of MOFs, particularly with smaller pore volumes, due to ethane accumulation over long-term cycling, until a steady state is reached with substantially degraded storage performance.

Batteries based on the redox of multivalent cations (Mg2+, Ca2+, Zn2+, Al3+, etc.) offer potential advantages over today’s lithium-ion batteries, but their development is hindered by the sluggish migration of such ions in solid electrodes and electrolytes. Computational screening can accelerate the discovery of more conductive materials, provided that ionic conductivity can be estimated with sufficient accuracy and efficiency. The present study examines whether vibrational properties can be used to predict energetic barriers for cation migration in 24 prototypical multivalent solid electrolytes. Phonon band centers (i.e. mean frequencies), which have been previously used to predict Li-ion conductivity, are calculated using density functional theory. Band centers alone are found not to correlate with migration barriers (R^2 = 0.02), perhaps due to poor alignment of low-frequency phonon eigenmodes with ion migration pathways in some materials. A new metric that incorporates both frequencies and alignments—the mean alignment-weighted frequency—is more strongly correlated with migration barriers (R^2 = 0.25). Materials in this study with the lowest migration barriers consistently exhibit the lowest mean alignment-weighted frequencies, suggesting the utility of this metric for filtering out materials with high barriers in screening efforts. Comparisons to previous studies suggest that phonon band centers may be correlated with migration barriers only in compositionally similar materials, and that adding alignment information may enable more reliable predictions among more diverse sets of materials. These results quantify the promise of using phonon frequencies and alignments, perhaps in combination with other properties, to efficiently screen for materials with high multivalent ionic conductivity.

A rechargeable battery that employs a Li metal anode requires that Li be plated in a uniform fashion during charging. In "anode-free" configurations, this plating will occur on the surface of the Cu current collector (CC) during the initial cycle and in any subsequent cycle where the capacity of the cell is fully accessed. Experimental measurements have shown that the plating of Li on Cu can be inhomogeneous, which can lower the efficiency of plating and foster the formation of Li dendrites. The present study employs a combination of first-principles calculations and sessile drop experiments to characterize the thermodynamics and adhesive (i.e., wetting) properties of interfaces involving Li and other phases present on or near the CC. Interfaces between Li and Cu, Cu2O, and Li2O are considered. The calculations predict that both Cu and Cu2O surfaces are lithiophilic. However, sessile drop measurements reveal that Li wetting occurs readily only on pristine Cu. This apparent discrepancy is explained by the occurrence of a spontaneous conversion reaction, 2 Li + Cu2O → Li2O + 2 Cu, that generates Li2O as one of its products. Calculations and sessile drop measurements show that Li does not wet (newly formed) Li2O. Hence, Li that is deposited on a Cu CC where surface oxide species are present will encounter a compositionally heterogeneous substrate comprising lithiophillic (Cu) and lithiophobic (Li2O) regions. These initial heterogeneities have the potential to influence the longer-term behavior of the anode under cycling. In sum, the present study provides insights into the early stage processes associated with Li plating in anode-free batteries and describes mechanisms that contribute to inefficiencies in their operation.

Maintaining interfacial contact between the Li metal anode and the solid electrolyte is a key challenge in developing Li metal-based solid-state batteries (LMSSB). At moderate discharge rates, relatively slower diffusion within the anode results in roughening and void formation in Li near this interface. The resulting reduction in interfacial contact focuses the Li-ion current during plating to a reduced number of contact points, generating high local current densities that nucleate dendrites. One approach to minimize void formation is to apply high stack pressure, which enhances plastic flow in the anode. Nevertheless, the use of pressure has drawbacks, as it facilitates fracture within the solid electrolyte. Here, an alternative strategy for minimizing void formation is described. Using a multi-scale model, it is shown that targets for capacity and current density in LMSSBs can be achieved by reducing the grain size of Li to exploit fast grain boundary (GB) diffusion. Diffusion rates along a diverse sampling of 55 tilt and twist GBs in Li were predicted using molecular dynamics, and found to be 3 to 6 orders of magnitude faster than in the bulk. Using these atomic-scale data as input, a meso-scale model of Li depletion in the anode during discharge was developed. The model predicts that smaller, columnar grains are desirable, with grain sizes of approximately 1 μm or less needed to meet performance targets. As micron-sized grains are two orders of magnitude smaller than those in common use, strategies for controlling grain size are discussed. In total, the model highlights the importance of the anode’s microstructure on the performance of LMSSBs.

Technologies for thermal energy storage (TES) are limited by the performance of the heat storage material. Therefore, it is desirable to develop materials with superior heat storage properties. The present study employs first-principles calculations to predict the properties of 7012 hypothetical hydrates based on chalcogenide and complex anion salts. Accounting for thermodynamic stability and energy densities, promising hydrates were identified for temperatures below 200 degrees C, including Li2S center dot 9H(2)O, Ca(OH)(2)center dot 8H(2)O, and Li2CO3 center dot 10H(2)O. System-level projections indicate that several of the proposed materials surpass the energy densities of known materials when incorporated into a solar-thermal storage system. Interpretable machine learning models were trained on the hydrate data set and used to identify features that control the enthalpy of dehydration. This analysis reveals similarities and differences in the thermodynamic behavior of hydrates based on chalcogenides, complex anions, and the previously studied halides. Hydrates based on chalcogenide anions exhibit a wide distribution of dehydration enthalpies; the low average enthalpies of these hydrates reflect the fact that relatively few are stable. In contrast, hydrates based on complex anions and halides exhibit enthalpies that are, on average, larger and more narrowly distributed. The enthalpies of the chalcogenide hydrates can be predicted by using only two machine-learned features, both of which implicate the electronegativity of the cation as a controlling property. This correlation agrees with a trend reported previously for halide-salt hydrates. In contrast, the behavior of the complex-anion hydrates requires twice as many features for machine-learning predictions, and some of these features are complex. Nevertheless, a combination of the molar volume and boiling point data is identified as a useful descriptor. In total, the hydrate compositions and design insights identified in this study are anticipated to catalyze the development of more efficient TES systems.

Antiperovskite (AP) structure compounds (X3AB, where X is an alkali cation and A and B are anions) have the potential for highly correlated motion between the cation and a cluster anion on the A or B site. This so-called “paddle-wheel” mechanism may be the basis for enhanced cation mobility in solid electrolytes. Here we show, through combined experiments and modeling, the first instance of a double paddle-wheel mechanism, leading to fast sodium ion conduction in the antiperovskite Na3-xO1-x(NH2)x(BH4). As the concentration of amide (NH2-) cluster anions is increased, large positive deviations in ionic conductivity above that predicted from a vacancy diffusion model are observed. Using EIS, PXRD, synchrotron XRD, neutron diffraction, AIMD, and NMR, we characterize the cluster anion rotational dynamics, and find that cation mobility is influenced by the rotation of both NH2- and BH4- species, resulting in sodium ion conductivity a factor of 102 higher at x = 1 than expected for the vacancy mechanism alone. Generalization of this phenomenon to other compounds could accelerate fast ion conductor exploration and design.

Interdiffusion of transition metals across the cathode-electrolyte interface is identified as a key challenge for the practical realization of solid-state batteries. This is related to the formation of highly resistive interphases impeding the charge transport across the materials thus limiting the battery performance. Herein, we investigate the hypothesis that formation of interphases is associated with the incorporation of Co into the LLZO lattice representing the starting point of a cascade of degradation processes. It is shown that Co incorporates into the garnet structure preferably four-fold coordinated as Co2+ or Co3+ depending on oxygen fugacity. The solubility limit of Co is determined to be around 0.16 pfu, whereby concentrations beyond this limit causes a cubic-to-tetragonal phase transition. Moreover, the temperature-dependent Co diffusion coefficient is determined, e.g., D700 °C = 9.46 × 10-14 cm2/s and an activation energy Ea = 1.65 eV, suggesting that detrimental cross diffusion will take place at any relevant process condition. Additionally, the optimal protective Al2O3 coating thickness for relevant temperatures is studied, which allows to create a process diagram to mitigate any degradation with a minimum compromise on electrochemical performance. This study provides a tool to optimize processing conditions toward developing high energy density solid-state batteries.

Thin intermetallic Li2Te–LiTe3 bilayer (0.75 mm) derived from 2D tellurene stabilizes solid electrolyte interphase (SEI) of lithium metal and argyrodite (LPSCl, Li6PS5Cl) solid-state electrolyte (SSE). Tellurene is loaded onto standard battery separator and reacted with lithium through single-pass mechanical rolling, or transferred directly to SSE surface by pressing. State-of-the-art electrochemical performance is achieved, e.g. symmetric cell stable for 300 cycles (1800 hours) at 1 mA cm-2 and 3 mAh cm-2 (25% DOD, 60 mm foil). Cryo-FIB sectioning and Raman mapping demonstrate that Li2Te–LiTe3 bilayer impedes SSE decomposition. The unmodified Li–LPSCl interphase is electrochemically unstable with geometrically heterogeneous reduction decomposition reaction front that extends deep into the SSE. Decomposition drives voiding in Li metal due to its high flux to the reaction front, as well as voiding in the SSE due to the associated volume changes. Analysis of cycled SSEs found no evidence for pristine (unreacted) lithium metal filaments/dendrites, implying failure driven by decomposition phases with sufficient electrical conductivity that span electrolyte thickness. Density Functional Theory (DFT) calculations clarify thermodynamic stability, interfacial adhesion, and electronic transport properties of interphases, while mesoscale modeling examines interrelations between reaction front heterogeneity (SEI heterogeneity), current distribution and localized chemo-mechanical stresses.

The inclusion of salts within the pores of metal- organic frameworks (MOFs) has been shown to increase the ionic conductivities of the salt ions relative to that of the bulk salt, raising the possibility that salt/MOF composites could be used as solid electrolytes. The present study explores the mechanism by which the inclusion of ionic liquids (ILs) occurs in MOFs and the mass loadings that can be achieved. Simulated annealing simulations and cyclic differential scanning calorimetry (DSC) experiments are used to investigate the loading of tetraethylammonium bis-(trifluoromethylsulfonyl)-imide ([NEt4][TFSI]) salt in three different UiO-6x MOFs: UiO-66, UiO-67, and a defective form of UiO-66 containing missing linkers. Good agreement is achieved between the predicted loadings and those measured experimentally. An analysis of the spatial distribution of salt ions within the MOF pores as a function of loading shows that repulsive anion-anion and cation-cation electrostatic interactions contribute to the upper limit of loading. The surface area and void fraction of the MOFs approach zero at the maximum loading, suggesting that the ions completely fill the MOF pores. The absence of free volume at the maximum loading is proposed as an explanation for the decrease in conductivity observed in prior experiments; hence, conductivity will be maximized for loadings that do not fill the MOF pores. Finally, the surface area and pore volume of the empty MOFs are shown to be good predictors of the maximum salt loading.

In 2016, an Editorial in ACS Nano, entitled “The Rising and Receding Fortunes of Electrochemists”, reflected the growing scientific consensus that existing initiatives in fundamental research were undermatched to the fact that electrochemistry was becoming ubiquitous in applications in energy, thus handicapping progress toward social impact. That same year, Next Generation Electrochemistry (NGenE) hosted its first edition at the University of Illinois at Chicago (UIC). NGenE is an annual summer workshop focused on describing emerging challenges at the frontiers of research in electrochemistry and the application of innovative strategies to address them. The original premise behind NGenE was also that, despite its reach and importance, fundamental electrochemistry had gone through a rather slow period of activity in the early 21st century compared to many companion fields. Back in 2016, one of the causes was ascribed to a deficit in electrochemistry training at the graduate level, leading to calls for increased emphasis in research in this area. Since 2016, NGenE has tackled these deficiencies by broadening the knowledge and perspective of senior graduate students and postdoctoral researchers. A series of world-renowned experts in various walks of electrochemistry examine fundamental phenomena at an advanced level, identifying critical gaps in our understanding and innovative strategies to address them. The program assumes baseline knowledge and prior experience in electrochemistry. NGenE does not ask, “What is electrochemistry?” but instead, “What will electrochemistry become?”. As such, it addresses the very same issues raised in the aforementioned Editorial. Fast-forwarding five years, support and activities in fundamental electrochemical research have undergone very significant growth. Furthermore, new applications of electrochemistry that were not on our radar in 2016 have emerged, especially among organic chemists. It is an exciting time to be an electrochemist, and new generations of leaders in research are increasingly pursuing this path. Simultaneously, NGenE has evolved from a program with a focus on rather specific topics, such as batteries, to expose the major diversity of fields interested in electrochemistry and finding common elements between their challenges. In 2020, the world ground to a halt with the onset of the COVID-19 pandemic, and NGenE had to adapt to the reality that meetings in person were not possible. The program migrated from a format of interactive lectures led by individual researchers to panel discussions involving multiple researchers talking to each other and with the attendees, who were provided the virtual floor to ask questions. The outcome was a series of highly dynamic discussions that are now free to watch on demand by anyone in the world. NGenE 2021 was divided into a series of panels, each dedicated to a specific topic at the frontiers of electrochemical research. In this status report, we summarize the key messages emerging from the discussions. While some panels covered aspects not limited to energy technology, the commonality of lessons and challenges highlights the many opportunities ahead for cross-pollination to establish electrochemistry as central to our current transition away from the fossil-fuel paradigm. By sharing them here, we strive to motivate the community to pursue directions that move us beyond the current frontiers. This summary is divided in themes that map out of the specific panel topics. Can Electrochemistry Replace Thermochemistry? In thermochemistry, temperature and pressure are major driving forces for chemical transformations. Existing high-temperature thermochemical processes rely on burning fossil fuels to achieve high temperatures in the furnace, reactor, or kiln. By burning fossil fuels to achieve the desired chemical transformation, CO2 is emitted, which adds to its toll as a major greenhouse gas. Steel and cement manufacturing, steammethane reforming, and the Haber−Bosch process are some of the examples of thermochemical processes at high temperatures that are challenging to decarbonize. These industries rely on mature technologies that have evolved over decades and have not changed significantly in the past decade. With the sustained declines in the cost of installing and using renewable sources of energy, electricity continues its transition to becoming a sustainable energy carrier free of emissions of greenhouse gases. All the major sources of renewable and carbon-neutral energy (solar, wind, nuclear) generate electricity, ensuring that a renewably powered society will be electrified. Shifting from thermochemistry to electrochemistry in industrial production could accelerate this transition by relying on electricity free of emissions. Electrifying the generation of heat is one way that could enable an electrified thermochemical industry. However, estimates suggest that if all thermal needs were electrified, it would be necessary to double the electricity running through the distribution system. This transition will be challenging without a tremendous increase in electrical transmission and

Li2OHCl is an exemplar of the antiperovskite family of ionic conductors, for which high ionic conductivities have been reported, but in which the atomic-level mechanism of ion migration is unclear. The stable phase is both crystallographically defective and disordered, having ∼1/3 of the Li sites vacant, while the presence of the OH- anion introduces the possibility of rotational disorder that may be coupled to cation migration. Here, complementary experimental and computational methods are applied to understand the relationship between the crystal chemistry and ionic conductivity in Li2OHCl, which undergoes an orthorhombic to cubic phase transition near 311 K (≈38 °C) and coincides with the more than a factor of 10 change in ionic conductivity (from 1.2 × 10-5mS/cm at 37 °C to 1.4 × 10-3 mS/cm at 39 °C). X-ray and neutron experiments conducted over the temperature range 20-200 °C, including diffraction, quasi-elastic neutron scattering (QENS), the maximum entropy method (MEM) analysis, and ab initio molecular dynamics (AIMD) simulations, together show conclusively that the high lithium ion conductivity of cubic Li2OHCl is correlated to "paddlewheel" rotation of the dynamic OH- anion. The present results suggest that in antiperovskites and derivative structures a high cation vacancy concentration combined with the presence of disordered molecular anions can lead to high cation mobility.

Thermal energy storage (TES) has the potential to improve the efficiency of many applications, but has not been widely deployed. The viability of a TES system depends upon the performance of its underlying storage material; improving the energy density of TES materials is an important step in accelerating the adoption of TES systems. Salt hydrates are a promising class of TES materials due to their relatively high energy densities and their reversibility. Despite their promise, relatively few salt hydrates have been characterized, presenting the possibility that new hydrate compositions with superior properties may exist. Here, the energy densities, turning temperatures, and thermodynamic stabilities of 5292 hypothetical salt hydrates are predicted using high-throughput density functional theory calculations. The hydrates of several metal-fluorides, including CaF2, VF2, and CoF3, are identified as new, stable TES materials with class-leading energy densities and operating temperatures suitable for use in domestic heating and intermediate-temperature applications. The promising performance of these materials is demonstrated at the system level by parameterizing an operating model of a solar thermal TES system with data from the new hydrates. Finally, machine learning models for salt hydrate thermodynamics are developed and used to identify design guidelines for maximizing energy density. In total, the new materials and design rules reported here are expected to foster the adoption of TES systems.

Machine learning is used to identify and assess the relative importance of features that control ion mobility in anti-perovskite solid electrolytes. Lattice properties such as hopping distance and channel width have the largest impact.