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Page 14 of 32 Yan et al. Energy Mater 2023;3:300002 https://dx.doi.org/10.20517/energymater.2022.60

[77]
Song et al. used in situ NR and NT to study Li distribution dynamics . As shown in Figure 5K, Li
consumption increased with time during the charge process. Further studies confirmed that high current
densities result in a high density of Li deposits, while low current densities generate a low density of Li
deposits and thick Li deposition, thereby forming significant “dead Li”. Titration gas chromatography (GC)
techniques can be used to quantify the fraction of dead Li . Recently, Hsieh et al. estimated the amount of
[98]
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dead Li by combining GC with in situ Li NMR analytical techniques . Based on in situ holographic
[99]
interferometry, in which a variation in the refractive index caused by a concentration variation of chemical
species leads to a discrepancy in the optical path length between the reference and objective beams,
Ota et al. proposed the ion concentration-dependent basal growth mechanism . The results showed that
[100]
+
the concentration gradient of Li ions around the tip and arm of Li dendrites was steeper than that at the
electrode/electrolyte interface, indicating that the local current density converged here [101-103] .

THEORETICAL INVESTIGATIONS
Advanced characterization often tends to concentrate on describing the phenomenon of the electrode
process. The understanding of the underlying mechanism also requires theoretical analysis, such as
simulations and calculations, which provides reliable assistance for experimental studies [104,105] . Phase field
simulations are practical tools to study the Li deposition rate in the 3D conductive host, which provides
[106]
guidance for the future design of the pore structures of 3D hosts . In addition, the anode/electrolyte
interface is an equally critical region that has been highlighted, especially in the field of solid-state batteries.
Yang et al. reported an atomic model of Li deposition/dissolution at the anode/solid electrolyte interface
based on large-scale molecular dynamics (MD) simulations, revealing that the sluggish kinetics of Li-ion
diffusion at the anode/solid electrolyte interface was responsible for the formation of interfacial
nanopores . These nanopores cause an increase in interfacial contact resistance, leading to degradation of
[107]
+
the electrochemical performance of batteries. In addition, due to the fast diffusion of Li ions, coherent
interfaces were less likely to generate nanopores, which highlights the importance of interfacial engineering
and new directions for the modification of LMBs. Furthermore, through classical MD simulations,
Karimi et al. investigated the properties of 1-butyl-1-methylpyrrolidinium tricyanomethanide (Pyr TCM),
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1-butyl-1-methylpyrrolidinium dicyanamide (Pyr DCA) and their binary solutions with the respective Li
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-
[108]
-
salts . Compared with TCM , the DCA showed less stability because DCA was closer to both cations (i.e.,
-
Pyr and Li ), which was more exposed to the consequent radical reactions. Therefore, the formed SEI on
+
+
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the anode surface with the LiDCA:Pyr DCA electrolyte system could probably be thicker.
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Moreover, as a step toward understanding the surface reactions, thermodynamic energy factors determining
the heterogeneity in the adsorption and desorption energy of ions are demonstrated by density functional
theory calculations, specifically adsorption and migration energies. First, lithium tends to form dendrites
different from some multivalent-ion systems, such as Mg, due to their intrinsic thermodynamic differences.
According to Matsui’s calculations, the bonding between Li atoms is much weaker than that between Mg,
meaning that moving a Li atom from the bulk to surface needs less energy and this low free-energy
difference means a greater tendency to form the low-dimension structure of whiskers and dendrites in the
[109]
Li system . Combined with the first-principles calculations, high-throughput screening and machine
learning methods are playing increasingly effective roles in the exploration of practical Li metal anodes.
High-throughput quantum-chemical calculations starting with a huge molecule database can effectively
select potential candidates based on abundant and accurate property evaluation. Compared with
conventional trial-and-error methods, this well-established method can speed up the search and selection of
optimal materials, greatly saving the expense and time costs.