Detailed analysis of the various factors underlying the relevant properties and processes during energy conversion not only helps us to better understand the phenomenological implications of the fundamental concepts but also to uncover the important physical and chemical trends in energy systems that they produce. Electronic and atomic structure, microstructure, chemical and mechanical stability, electronic and ionic conductivity, as well as reactivity are examples of important parameters controlling the performance of energy materials. In principle, all these parameters can be characterized by applying experimental and/or theoretical techniques. Thus, designing high-performing energy storage and conversion systems requires combined theoretical/experimental efforts to screen materials in the search for optimal components.
First-principles density functional theory (DFT) calculation as well as ab initio thermodynamics, kinetics, and dynamics, and continuum-scale modelling have been applied to investigate electrode, electrolyte, and their interfaces in energy storages and conversion systems. For example, mechanism of lithiation/delithiation and potential profile for Li-based cathode materials have been simulated by calculating phase diagrams [1, 2] using a combination of DFT and Monte Carlo simulations. The simulated staging mechanism was in fair agreement with experimental observation . Moreover, electronic and atomic structure of surfaces as well as morphology of nanoparticles of cathode materials for Li-ion [4-5], Li-air , Li-S  batteries were characterized by DFT and ab initio atomistic thermodynamics approaches. The theoretical calculations were either combined with experimental observations or they were later confirmed by measurements. Stress distribution in primary  and secondary particles  of cathode materials was also simulated. The results of ref. 9, for example, explained the reason behind the higher stability of well-ordered core-shell cathode particles. Influence of atomic structure of grain boundaries in microstructures on Li-ion conduction in solid electrolyte materials for all-solid-state batteries (ASSBs) were also recently performed [10,11], which can be in future combined with experimental studied to understand and improve the performance of ASSBs. Electronic and atomic structure of complex solid-electrolyte/electrode interfaces have also been calculated [12,13]. On the other hand, continuum-scale modelling of solid/solid interfaces and space charge have been developed [14-18]. However, most of the computational parameters in these models have been either provided by experimental data or were considered as free parameters. Besides ideal interfaces, decomposition and secondary phase formation between solid electrolytes and electrodes were predicted by calculating Li and O grand potential phase diagrams [19,20]. Predicted interfacial phase formation were well correlated with experimental interfacial observations and battery performance.
Treatment of chemical reactions at the active interfaces in energy conversion devices, in particular solid-liquid interfaces in fuel cells, remain a great challenge for theory. Ab initio treatment of chemical reactions at solid-liquid interfaces under bias voltage was pioneered by Nørskov et al. . The long-range effects of charge redistribution between electrodes, adsorbates, and electrolyte play an important role, and must be taken into account when modelling electrochemical reactions [17,22,23]. The main remaining problem is to account for statistical effects at finite temperatures, in particular configurational entropy and interplay of chemical reactions. The possibility of treating equilibrium (potential of zero charge and differential capacitance) and dynamic (chemical reactions) properties of the electrode/electrolyte interface in a unified theoretical framework remains unclear . A pre-requisite to address these problems from first principles is to accelerate the energy evaluation per structure without losing the accuracy. In the context of fuel cells, a combination of first-principles calculations with reactive force fields has been proposed for this purpose . An interesting emerging prospect is to combine ab initio calculations with machine learning to find more transferrable interatomic potentials [26-28]. Data mining and machine learning can be also used to find descriptive parameters (descriptors) that establish correlations between easily computable or measurable properties of materials (e.g., properties of involved atoms and interfaces) and their (electro)chemical and catalytic properties [29,30]. Therefore, we expect that bringing together experts with data mining/machine learning and energy conversion expertise will induce many interesting discussions and collaborations.
Characterization of primary particles and microstructures as well as interfaces and grain boundaries is a major challenge for both experimentalists and theoreticians. Multiscale modelling of these complex systems is still in its infancy stage and needs to be further developed. In particular, ab initio and/or atomistic-based multiscale modelling can help us to gain fundamental understanding of relation between (physical, chemical, and mechanical) properties and performance of materials. It is also an enormous challenge for experimentalist to characterize energy materials in atomic scale, in particular at realistic operational conditions.
The proposed workshop aims to bring together theoreticians and experimentalists who are working on development of energy materials and systems. Recent advances in electronic-structure theory, continuum modelling, multiscale modelling, data analytics, as well as atomic-scale observation techniques will be presented and discussed. Applications of the theoretical and experimental methods for Li- and Na-ion batteries, all-solid-state batteries, and solid oxide fuel cells will be presented.
• Data Mining and Machine Learning, and Multiscale Modeling
• Combined Computational/Experimental Strategies to Energy Material Design
• All-Solid-State Batteries and Fuel Cells: Novel Electrolyte Materials, Interfaces and Interphases
• Novel Cathode and Anode Materials for Li-, Na-, K-, and Mg-based Batteries