Inorganic Gel-Derived Metallic Frameworks Enabling High

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Inorganic Gel-Derived Metallic Frameworks Enabling High-Performance Silicon Anodes Anping Zhang, Zhiwei Fang, Yawen Tang, Yiming Zhou, Ping Wu, and Guihua Yu Nano Lett., Just Accepted Manuscript • DOI: 10.1021/acs.nanolett.9b02429 • Publication Date (Web): 19 Aug 2019 Downloaded from pubs.acs.org on August 20, 2019

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Nano Letters

Inorganic Gel-Derived Metallic Frameworks Enabling High-Performance Silicon Anodes Anping Zhang,†,§ Zhiwei Fang,‡,§ Yawen Tang,† Yiming Zhou,† Ping Wu,*,† and Guihua Yu*,‡ †Jiangsu

Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of

Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210023, China ‡Materials

Science and Engineering Program and Department of Mechanical Engineering, The

University of Texas at Austin, Austin, Texas 78712, United States KEYWORDS: silicon anodes, metallic frameworks, inorganic gel, silicon rearrangement, Li-ion batteries

ACS Paragon Plus Environment

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ABSTRACT

Metallic matrix materials have emerged as an ideal platform to hybridize with next-generation electrode materials such as silicon for practical applications in Li-ion batteries. However, these metallic species commonly exist in the form of isolated particles, failing to provide enough free space for silicon volume changes as well as continuous charge transport pathways. Herein, 3D metallic frameworks with interconnected pore channels and conductive skeletons, have been synthesized from inorganic gel precursors as buffering/conducting matrices to boost lithium storage performance of silicon anodes. As a proof-of-concept demonstration, commercial Si particles are in situ immobilized within Sn–Ni alloy framework via a facile gel-reduction route, and the rearrangement of Si particles during cycling increases the dispersity of Si in Sn–Ni framework as well as their synergic effects toward lithium storage. The Si@Sn–Ni all-metallic framework manifests high structural integrity, 3D Li+/e- mixed conduction pathway, and synergic effects of interfacial bonding and concurrent reaction dynamics between active Si and Sn, enabling long-term cycle life (1205 mA h g-1 after 100 cycles at 0.5 A g-1) and superior rate capability (653 mA h g-1 at 10 A g-1).


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Among next-generation anodes for lithium storage, silicon is the most promising highcapacity anode due to its large theoretical capacity at room temperature (3579 mA h g-1 for Li15Si4), proper operating potentials (~0.4 V vs. Li/Li+), and natural abundance.1-4 However, the huge volume change during lithiation and delithiation (~300%) leads to severe electrode pulverization and unstable solid electrolyte interphase (SEI) formation, causing decreased Coulombic efficiencies and fast capacity fading.1-3 Meanwhile, the ultralow intrinsic electrical conductivity and Li+ diffusion coefficient (10-14–10-13 cm2 s-1) seriously limit the full utilization of theoretical capacity, leading to unsatisfied rate performance.1,2 The incorporation of heteromatrices into silicon is regarded as a powerful strategy to tailor the lithium storage performance, and carbon has proved to be an effective buffering and conducting matrix for silicon anodes owing to its superior mechanical flexibility and electronic conductivity.5-9 Similarly to carbon, metallic matrix can promote electron/ion transport and help maintain electrode integrity of silicon anodes. Besides these common merits, metallic components possess their own properties and peculiar electrochemical mechanisms to boost Si-based lithium storage.10-26 Generally, silicon–metal (Si–M) anodes manifest higher tap densities and volumetric energy densities than Si and Si–C ones.13 Moreover, the concurrent lithium-storage dynamics between active metals (M'=Ge, Sn, Sb, etc) and silicon improve reaction kinetics and alleviate electrochemically induced mechanical degradation effectively.17 Also, electrochemically inactive metals (M''=Ti, Ni, Fe, etc), acting as diffusion barriers, inhibit the full lithiation of amorphous LixSi to crystalline Li15Si4, thus avoiding uneven volume variations and enhancing electrode stability.24-26 Therefore, silicon-based all-metal materials, especially Si–M'–M'' ones, represent an important category of promising and practical Si-based anodes with desirable performance.


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Up to now, a series of electrochemically active and inactive metals have been integrated with silicon to realize improved overall lithium storage performance benefited from the hybridization merits of metallic matrices.10-26 However, in these Si–M anodes, metallic species often exist in the form of zero-dimensional (0D) particles isolated from each other, failing to provide enough free space for silicon volume changes as well as continuous charge transport pathways.10-16 In this regard, structural engineering of metallic matrices, especially adopting 3D interconnected metallic frameworks, is highly desirable to address the intrinsic pulverization and conducting challenges of silicon anodes. Recently, 3D carbonaceous frameworks, including amorphous carbon,27,28 graphene,29 and conducting polymers (CP),30 enable encapsulated silicon particles to exhibit prolonged cyclic life and enhanced rate capability toward lithium storage, owing to their structural integrity and stability as well as 3D electron/ion mixed conducting networks. Despite the progress in 3D Si@C and Si@CP framework anodes, it remains a huge challenge to synthesize such types of Si@metal anodes with controllable composition/structure-features of metallic frameworks and uniform dispersion of embedded Si for significantly enhanced lithiumstorage performance. Herein, we propose a facile and scalable gel-reduction methodology for uniformly immobilizing Si particles within 3D metallic frameworks. As a representative example, the ligand-substitution reaction between SnCl4 and K2Ni(CN)4 generates a cyano-bridged coordination polymer gel (Sn–Ni cyanogel), and commercial Si particles are in situ immobilized within cyanogel skeleton, as illustrated in Figure 1a. The Si@Sn–Ni hybrid cyanogel is directly reduced to an all-metal framework consisting of Sn–Ni alloy matrix and uniform-immobilized Si particles, chemically binded via Si−O−Sn bonds. Upon cycling, the embedded Si particles continuously break into smaller pieces, and as shown in Figure 1b, such rearrangement increases


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the dispersity of Si in the metallic framework as well as their hybridization merits and synergic effects including interfacial bonding and concurrent reaction dynamics between active Si and Sn. The highly structural integrity, 3D Li+/e- mixed conducting pathway, and enhanced synergic effects between Si and Sn–Ni enable the Si@Sn–Ni all-metal framework to exhibit long-term cycle life (1205 mA h g-1 after 100 cycles at 0.5 A g-1) and superior rate capability (653 mA h g-1 at 10 A g-1).

Figure 1. (a) Synthetic diagram of the Si@Sn–Ni all-metal framework. (b) Schematic illustration of the rearrangement upon cycling and lithiation/de-lithiation processes for the Si@Sn–Ni allmetal framework. As a special category of inorganic gels, cyanogels are generally formed via ligandsubstitution reactions between main-group or noble metal chlorides/chlorometalates (Sn,31-33 In,34 Sb,35 Pt,36 Pd,36,37 etc) and transition-metal cyanometalates (Fe, Co, Ni, etc) solutions. The uniform distribution of functional metal species on gel skeletons makes cyanogels become an emerging material platform to study metal-based frameworks for advanced electrochemical


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energy storage and conversion.31-37 Here, as shown in Figure S1, Sn–Ni alloy product is directly obtained via a facile cyanogel-reduction route. The alloy product inherits the structural features of Sn–Ni cyanogel, and the unique 3D framework can be clearly observed from its transmission electron microscopy (TEM) image (Figure S2b). The crystalline phases can be assigned to Ni3Sn4 (JCPDS no. 65-4310) and metastable Sn–Ni alloy (MS Sn–Ni) from X-ray powder diffraction (XRD) pattern (Figure S2c). MS Sn–Ni, formed by melting of nickel into tin crystals, might have a positive effect on improved structural stability and cycling life toward lithium storage.38 The intimate interconnection between Sn and Ni species on cyanogel scaffold (Sn– N≡C–Ni) facilitates the combination between zero-valent metallic nuclei during reduction, and moreover, the solid nature of gels restrains Brownian motion of Sn and Ni nuclei, benefitting the formation of homogeneous Sn–Ni alloy (Figure S2e).35-37

Figure 2. (a) Photograph of the Si@Sn–Ni hybrid cyanogel. (b) TEM image and SAED pattern (inset), (c) XRD pattern, (d) magnified TEM image and SEM image (inset), (e) TEM-EDS elemental mappings, and (f) Sn 3d3/2 XPS spectrum of the Si@Sn−Ni all-metal framework.


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Moreover, cyanogel possesses the mutual structure advantages of nanostructured gels,39-44 and functional nanomaterials can be immobilized in gel and gel-derivative frameworks for furtherenhanced performances and broader applications.30,45,46 As inspired, in this gel-reduction route, commercial Si particles, with a concentration of 5 mg mL-1, are in situ immobilized in Sn–Ni cyanogel, yielding a uniform Si@Sn–Ni hybrid cyanogel (Figure 2a). The hydrogen bonding between hydroxyl groups on Si surface with a primitive oxide layer and cyano group in gel skeleton increases the dispersity of Si particles in gel network while favoring subsequent interfacial bonding between embedded Si and gel-derived metallic framework.31,47 After reduction, Si particles are uniformly embedded within cyanogel-derived Sn–Ni alloy framework, yielding the final Si@Sn−Ni all-metal framework (Figure 2b). The selected-area electron diffraction (SAED) pattern of the Si@Sn−Ni product shows characteristic diffraction rings from Si, Ni3Sn4, and MS Sn–Ni (Inset in Figure 2b), and these crystalline phases are also confirmed by its XRD pattern (Figure 2c). Moreover, the scanning electron microscope (SEM) image clearly reveals the nanodendrite-assembled framework structure of Sn–Ni alloy, and spherical Si particles can be observed from the edge part of the Sn–Ni framework, as indicated by yellow arrows (Inset in Figure 2d). Also, the TEM image shows the co-existence of Sn–Ni nano-dendrites, embedded and half-exposed Si particles (Figure 2d), which is further confirmed by the high-resolution TEM (HRTEM) image and micro-area energy-dispersive X-ray spectrometer (EDS) spectra (Figure S3). Additionally, the elemental mappings in both low magnification (Figure S4) and high magnification (Figure 2e) verify the effective and uniform embedding of Si particles in Sn–Ni alloy matrix over the entire hybrid framework. The nanoporous features of the Si@Sn−Ni framework have been demonstrated by nitrogen adsorption/desorption tests (Figure S5). As illustrated, the hybrid framework manifests a high


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Brunauer–Emmett–Teller (BET) surface area of 35.0 m2 g-1, a large Barrett–Joyner–Halenda (BJH) pore volume of 0.22 cm3 g-1, and hierarchical meso-/macro-pores with an average size of 18.0 nm. To gain further insight into the chemical interactions between Si and Sn–Ni, X-ray photoelectron spectroscopy (XPS) analysis of the hybrid framework has been examined in comparison with Si particles and Sn–Ni alloy framework. Figure 2f displays the Sn 3d3/2 XPS spectrum of the Si@Sn–Ni product compared with single Sn–Ni counterpart. After Si incorporation, the peak shifts from 495.0 eV (curve a) to higher binding energy (495.3 eV, curve b). The positive shift indicates stronger Sn–O bond polarization in the hybrid framework, causing by the formation of Si−O−Sn bonding.48 The presence of interfacial bonding is also confirmed by Si 2p XPS spectrum of the hybrid framework, which shows an additional Si−O−Sn peak at 102.6 eV with high intensity compared with Si particle sample (Figure S6).49 The strong interfacial bonding of Si−O−Sn prevents the electrochemical aggregation while accelerating ion shuttling upon repeated lithium insertion/extraction, facilitating long-term cyclic life and fast reaction kinetics.50 As a proof-of-concept illustration of the compositional and structural features, the lithium storage behavior and performance of the Si@Sn−Ni all-metal framework has been examined in comparison with Si and Sn−Ni control samples. Figure 3a and Figure S7 display the initial three cyclic voltammetry (CV) curves of the Si@Sn–Ni framework and control samples (0-1.2 V, 0.2 mV s-1). As can be seen, the profiles of these curves in control samples are consistent with the lithium-storage behaviors of Si and Sn–M'' alloy anodes, contributed by the reversible alloying and dealloying reactions of active Si and Sn components, respectively (Figure S7).1-4,31,32 As expected, the Si@Sn–Ni hybrid framework demonstrates combinative and synergic


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electrochemical behaviors from Si and Sn–Ni samples, which can be clearly revealed by the anodic scanning (Figure 3a). Specifically, the peak at 0.33 V is related to the lithium extraction process from LixSi alloys, whereas the peaks at 0.64, 0.74, and 0.80 V correspond to the gradual Li-extraction processes from LixSn alloys. The stepwise Li-storage processes of active Si and Sn components at different potentials can accommodate the volume changes for each other and improve the structural stability of the hybrid anode.10-12 Apart from these separate electrochemical processes, the strong peak at 0.55 V is contributed by the co-delithiation reactions of LixSi and LixSn alloys. The concurrent lithium-storage reaction dynamics between active Si and Sn can effectively mitigate the electrochemically induced mechanical degradation, thus maintaining long-term structural integrity upon lithium insertion/extraction.17

Figure 3. Lithium storage performance of the Si@Sn−Ni all-metal framework in comparison with Si particles and Sn−Ni alloy framework: (a) CV curves, (b) cycling stability (0.5 A g-1), (c) rate capability (from 0.5 to 10 A g-1), (d) comparison of rate performance with literatures, (e) impedance spectra, and (f) relationship between Z' and -1/2.


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The cyclic and rate performances of the Si@Sn−Ni framework and control samples have been further examined at current densities of 0.1 A g-1 for the first cycle and 0.5 to 10 A g-1 for subsequent cycles. Consistent with CV results, the initial discharge/charge curves of these three samples also reveal the co-lithiation/co-delithiation processes of active Si and Sn components in the Si@Sn−Ni hybrid framework (Figure S8). Figure 3b displays the cycling performance of these three samples at 0.5 A g-1. As can be seen, the Si@Sn−Ni hybrid framework manifests significantly improved capacity retention than Si particles and much higher capacities than Sn−Ni framework. The average capacity fading for hybrid framework is only 0.15% per cycle from 2 to 100 cycles, much lower than the values of Si particles (0.99%) and Sn−Ni framework (0.28%). After 100 cycles, the Si@Sn−Ni hybrid anode is thus able to deliver a high discharge capacity of 1205 mA h g-1, much higher than those of Si (56 mA h g-1) and Sn−Ni (470 mA h g-1) control samples. The cyclic performance of the Si@Sn−Ni all-metal framework is comparable to those of state-of-the-art Si–M anodes, as listed in Table S1. These results confirm the effectiveness of Sn−Ni framework in buffering volume variations and prolonging cyclic life of embedded silicon anodes, and the interfacial Si−O−Sn bonding as well as concurrent lithium storage dynamics between Si and Sn–Ni further improves the structural integrity and stability of the hybrid anodes. Besides the prolonged life span, the gel-derived metallic frameworks, together with their synergic effects with embedded silicon, also play a vital role in enhancing the charge-transport capability and rate performance of the hybrid anodes. As illustrated in Figure 3c, the Si@Sn−Ni hybrid framework exhibits stable capacities at various current densities from 0.5 to 10 A g-1, and high average capacities of 886 and 653 mA h g-1 can be delivered even at ultrahigh current densities of 5 and 10 A g-1, respectively. Additionally, the average capacity retention at 10 A g-1


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vs. 0.5 A g-1 is 47.5% for Si@Sn−Ni framework, much higher than those of Si particles (1.5%) and Sn−Ni framework (35%). The superior rate performance of the Si@Sn−Ni hybrid framework is among the best of silicon-based all-metal anodes including Si–M' and Si–M'' ones (Figure 3d). In Si@Sn−Ni hybrid frameworks, the uniform embedding of Si particles in alloy frameworks is a prerequisite for achieving desirable electrochemical performance. For verification, Si particles and Sn−Ni framework were milled, and the lithium-storage performance of the milled Si/Sn−Ni mixture was examined in comparison with Si@Sn−Ni framework (Figure S9). As observed, the Si/Sn−Ni mixture exhibits much worse cyclic stability (427 mA h g-1 after 100 cycles at 0.5 A g-1) and rate capability (317 mA h g-1 at 10 A g-1), further demonstrating the structural advantages of hybrid frameworks toward lithium storage. Moreover, for Si–M'–M'' allmetal anodes, the contents of each metallic component play critical roles in the lithium-storage performance owing to their distinct functions. The cyanogel-reduction route can readily control the silicon, tin, and nickel contents in Si@Sn−Ni frameworks by simply adjusting reagent concentrations and ratios.31-35 Here, silicon content in the hybrid anodes has been regulated to further optimize their electrochemical performance. Figure S10 reveals the EDS spectra of the Si@Sn−Ni frameworks prepared with different Si concentrations (2.5, 5, and 10 mg mL-1), and the Si/Sn atomic ratio is determined to be 1.1:1 (2.5 mg mL-1), 2.2:1 (5 mg mL-1), and 3.9:1 (10 mg mL-1), respectively. As seen in Figure S11, the Si@Sn−Ni frameworks manifest Si contentdependent cyclic and rate performances. High silicon content is beneficial for achieving large capacities in initial stages, whereas low silicon content favors improved cyclic stability and rate retention. Therefore, silicon content should be carefully determined for optimized overall electrochemical performance, and the Si@Sn−Ni framework, prepared with a Si concentration of


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5 mg mL-1, can be a good example in realizing high reversible capacity, long-term cyclic life, and high rate capability. The high structural integrity and 3D Li+/e- mixed conducting pathways as well as synergic effects between Si particles and Sn–Ni framework are the key factors for the optimal Si@Sn–Ni all-metal anode to achieve superior overall lithium-storage performance. Specifically, the Sn–Ni alloy framework, with large surface area and abundant nanopores, accommodates volume change and improves cyclic stability of silicon particles to a large extent.27-30 Meanwhile, the 3D alloy framework promotes electron transfer along its backbone while facilitating lithium ion transport through interconnected nanopores, and such mixed Li+/e- conducting channels ensures enhanced high-rate performance.39-47 Besides these structural advantages, the synergic effects between Si and Sn–Ni further improve the strain-accommodation and charge-transport capabilities. The interfacial Si−O−Sn bonding, as well as the concurrent lithium-storage reaction dynamics in active Si and Sn, prevents the electrochemically induced electrode degradation while accelerating Li-ion shuttling upon cycling.17,50 These desirable structural and compositional features of the Si@Sn−Ni hybrid frameworks could be further verified by electrochemical kinetics analysis. Figure 3e depicts the Nyquist plots of Si@Sn–Ni all-metal anode in comparison with Si and Sn–Ni electrodes at open circuit potential after five cycles. Using an optimized equivalent circuit model, the fitting results of SEI resistance (RSEI) and charge transfer resistance (RCT) for these samples are summarized in the inset of Figure 3e. As clearly seen, the RCT value for Si@Sn–Ni sample is only 13 Ω, much lower than those of Si and Sn–Ni samples (257 and 45 Ω, respectively), demonstrating the significantly improved charge transport capability of the hybrid anode. Besides the differences in Li-ion insertion kinetics, the comparative diffusion coefficient of lithium ions (DLi+) of these


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three samples has been examined through the relationship between the real part of impedance (Z') and square root of frequency (-1/2) in low frequency region (Figure 3f). The slop of fitted line represents the Warburg coefficient (w), and DLi+ is proportional to (1/w)2. Thus, the DLi+ of Si@Sn–Ni sample is calculated to be 89 and 4 times than those of Si and Sn–Ni samples, respectively, suggesting the markedly enhanced Li-ion diffusion kinetics in the hybrid framework. The prominent synergic effects between Si and Sn–Ni can be responsible for the efficient charge transfer and improved Li-ion diffusion in the Si@Sn−Ni hybrid framework.

Figure 4. (a) Schematic illustration for the rearrangement of Si particles in Sn−Ni framework upon cycling. (b) TEM images, (c) elemental mappings, (d) HRTEM image, and (e) Raman spectra of the Si@Sn−Ni all-metal framework in a fully de-lithiated state (1.2 V vs. Li+/Li) after 100 cycles.


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Apart from the lithium-storage kinetics analysis, the anodic characterization after cycling has been carried out to further reveal the favorable electrochemical behavior of the Si@Sn−Ni hybrid framework. During cycling, the embedded Si particles continuously break into smaller fragments, and the generated Si pieces are still encapsulated by alloy matrix and tend to attach to the alloy surface owing to the unique framework structure with interconnected nanopores. Such rearrangement process, as illustrated in Figure 4a, increases the dispersity of Si in Sn−Ni framework as well as their synergic effects including interfacial bonding and concurrent reaction dynamics, thereby enabling enhanced lithium storage performance. Figure 4b-e reveal the structural and compositional features of the Si@Sn−Ni anode in a de-lithiated state after 100 cycles. As clearly shown, the 3D framework structure is well preserved after repeated lithium insertion/extraction, and the de-lithiated alloy framework is also assembled by interconnected nanodendrites (Figure 4b). Compared with the uncycled sample, the distribution of silicon component is more homogenous in the de-lithiated framework (Figure 4c), indicating the rearrangement of Si particles within Sn−Ni matrix. Additionally, the crystalline phases can be assigned to tetragonal Sn (JCPDS no. 04-0673) and cubic Ni (JCPDS no. 65-0380) from the SAED pattern (Inset in Figure 4b), and the HRTEM image also reveals characteristic lattice fringes of (200) plane from Sn and (111) plane from Ni (Figure 4d), consistent with the Listorage behavior of Sn–M'' active–inactive alloy anodes. Moreover, the amorphous nanoparticle, located within the mesopore and attached to the crystalline nanodendrite, can be identified as a silicon fragment by its micro-area EDS spectrum with an ultrahigh Si/Sn atomic ratio of 9.8:1 (Figure 4d). The crystalline/amorphous phase transition of silicon during cycling is further confirmed by Raman spectra, which show a negative shift from 514 cm-1 in uncycled state to 466 cm-1 in de-lithiated framework (Figure 4e).15


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To summarize, we develop a facile and scalable cyanogel-reduction methodology for uniformly immobilizing Si particles within 3D Sn–Ni alloy frameworks. The high structural integrity, 3D Li+/e- mixed conducting pathways, as well as synergic effects between Si particles and Sn–Ni framework, are the key factors for the Si@Sn–Ni all-metal framework to achieve remarkable structural stability and charge-transport capability toward lithium storage. Moreover, the rearrangement of Si particles during cycling increases the dispersity of Si in Sn–Ni framework as well as their synergic effects including interfacial bonding and concurrent reaction dynamics. Thanks to these intriguing features, the Si@Sn–Ni all-metal framework manifests long-term cycle life and superior rate capability. Furthermore, the present cyanogel-reduction strategy provides a promising method for achieving other metal-based hybrid frameworks with both structural and compositional tunability for diverse electrochemical energy-related applications.

ASSOCIATED CONTENT Supporting Information. Experimental details, synthetic diagram, photographs, TEM and HRTEM

images,

XRD

pattern,

EDS

spectra,

EDS

elemental

mappings,

nitrogen

adsorption/desorption isotherms, XPS spectrum, CV curves, initial discharge and charge curves, cycling stability, rate capability, and comparison of lithium storage performance can be found in Supporting Information. AUTHOR INFORMATION Corresponding Authors *E-mail: [email protected]


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*E-mail: [email protected] Author Contributions §A.Z.

and Z.F. contributed equally to this work.

ACKNOWLEDGMENT G. Y. acknowledges the funding support from US Department of Energy, Office of Science, Basic Energy Sciences, under Award DE-SC0019019, Sloan Research Fellowship and Camille Dreyfus Teacher-Scholar Award. P.W. appreciates the financial supports from National Natural Science Foundation of China (No. 51401110). REFERENCES (1) Li, P.; Zhao, G.; Zheng, X.; Xu, X.; Yao, C.; Sun, W.; Dou, S. X. Energy Storage Mater. 2018, 15, 422–446. (2) Luo, W.; Chen, X.; Xia, Y.; Chen, M.; Wang, L.; Wang, Q.; Li, W.; Yang, J. Adv. Energy Mater. 2017, 7 (24), 1701083. (3) Liu, B.; Soares, P.; Checkles, C.; Zhao, Y.; Yu, G. Nano Lett. 2013, 13, 3414-3419. (4) Li, J. Y.; Xu, Q.; Li, G.; Yin, Y. X.; Wan, L. J.; Guo, Y. G. Mater. Chem. Front. 2017, 1 (9), 1691–1708. (5) Zhang, X.; Kong, D.; Li, X.; Zhi, L. Adv. Funct. Mater. 2019, 29 (2), 1806061. (6) Li, Y.; Yan, K.; Lee, H. W.; Lu, Z.; Liu, N.; Cui, Y. Nat. Energy 2016, 1, 15029. (7) Xu, Q.; Li, J. Y.; Sun, J. K.; Yin, Y. X.; Wan, L. J.; Guo, Y. G. Adv. Energy Mater. 2017, 7 (3), 1601481. (8) Lee, S. J.; Kim, H. J.; Hwang, T. H.; Choi, S.; Park, S. H.; Deniz, E.; Jung, D. S.; Choi, J. W. Nano Lett. 2017, 17 (3), 1870–1876.


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Inorganic Gel-Derived Metallic Frameworks Enabling High

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