Hybrid Dynamic Covalent Network-Based Protecting Layer for Stable Li-Metal Batteries.

Metallic lithium (Li) is considered as the "Holy Grail" anode material for next-generation energy storage systems due to its extremely high theoretical capacity and low electrochemical potential. Before the commercialization of the Li electrode, dendritic Li growth and the unstable solid electrolyte interphase layer should be conquered. Herein, a hybrid covalent adaptable polymer network (HCAPN) is prepared via the random copolymerization of poly(ethylene glycol) methyl ether methacrylate and -acetoacetoxyethyl methacrylate, followed by chemical cross-linking with polyethylenimine (PEI) and amine-modified silicon dioxide (SiO2). Such a hybrid network, where PEI and amine-modified SiO2 formed a vinylogous urethane-based dynamic covalent bond with the copolymer, respectively, shows improved mechanical properties, solvent resistance, and excellent healability/recyclability. As the protecting layer on the Li electrode, the assembled HCAPN@Li||HCAPN@Li symmetric cell shows a long cycle life of 800 h with low overpotential at a current density of 1 mA cm-2, and superior electrochemical performance can be achieved in the HCAPN@Li||LiFePO4 full cell (capacity retention of 77% over 400 cycles at 1.5 C) and HCAPN@Li||NCM811 cell (capacity retention of 79% after 300 cycles). Surface morphology analysis is also performed for physical insight into their role as protecting layer. This work provides a new perspective for constructing a hybrid dynamic covalent network-based polymer protecting layer for inhibiting Li dendrite growth.

Hybrid Dynamic Covalent Network as a Protective Layer and Solid-State Electrolyte for Stable Lithium-Metal Batteries.

Lithium (Li) metal is a highly promising anode material for next-generation high-energy-density batteries, while Li dendrite growth and the unstable solid electrolyte interphase layer inhibit its commercialization. Herein, a chemically grafted hybrid dynamic network (CHDN) is rationally designed and synthesized by the 4,4'-thiobisbenzenamine cross-linked poly(poly(ethylene glycol) methyl ether methacrylate-r-glycidyl methacrylate) and (3-glycidyloxypropyl) trimethoxysilane-functionalized SiO2 nanoparticles, which is utilized as a protective layer and hybrid solid-state electrolyte (HSE) for stable Li-metal batteries. The presence of a dynamic exchangeable disulfide affords self-heability and recyclability, and the chemical attachment between SiO2 nanoparticles and the polymer matrix enables the homogeneous distribution of inorganic fillers and mechanical robustness. With integrated flexibility, fast segmental dynamics, and autonomous adaptability, the as-prepared CHDN-based protective layer enables superior electrochemical performance in half cells and full cells (capacity retention of 83.7% over 400 cycles for the CHDN@Li/LiFePO4 cell at 1 C). Furthermore, benefiting from intimate electrode/electrolyte interfacial contact, CHDN-based solid-state cells deliver excellent electrochemical performance (capacity retention of 89.5% over 500 cycles for the Li/HSE/LiFePO4 cell at 0.5 C). In addition, the Li/HSE/LiFePO4 pouch cell exhibits superior safety, even exposing various physical damage conditions. This work thereby provides a fresh insight into a rational design principle for dynamic network-based protective layers and solid-state electrolytes for battery applications.

A Novel Design Concept of Cemented Paste Backfill (CPB) Materials: Biobjective Optimization Approach by Applying an Evolved Random Forest Model.

For cemented paste backfill (CPB), uniaxial compressive strength (UCS) is the key to ensuring the safety of stope construction, and its cost is an important part of the mining cost. However, there are a lack of design methods based on UCS and cost optimization. To address such issues, this study proposes a biobjective optimization approach by applying a novel evolved random forest (RF) model. First, the evolved RF model, based on the beetle search algorithm (BAS), was constructed to predict the UCS of CPB. The consistency between the predicted value and the actual value is high, which proves that the hybrid machine learning model has a good effect on the prediction of the UCS of CPB. Then, considering the linear relationship between the costs and the components of CPB, a mathematical model of the cost is constructed. Finally, based on the weighted sum method, the biobjective optimization process of the UCS and cost of CPB is conducted; the Pareto front optimal solutions of UCS and the cost of CPB can be obtained by the sort of solution set. When the UCS or the cost of CPB is constant, the Pareto front optimal solutions can always have a lower cost or a higher UCS compared with the actual dataset, which proves that the biobjective optimization approach has a good effect.

Single-Ion Conducting Polymeric Protective Interlayer for Stable Solid Lithium-Metal Batteries.

With many reported attempts on fabricating single-ion conducting polymer electrolytes, they still suffer from low ionic conductivity, narrow voltage window, and high cost. Herein, we report an unprecedented approach on improving the cationic transport number (tLi+) of the polymer electrolyte, i.e., single-ion conducting polymeric protective interlayer (SIPPI), which is designed between the conventional polymer electrolyte (PVEC) and Li-metal electrode. Satisfied ionic conductivity (1 mS cm-1, 30 °C), high tLi+ (0.79), and wide-area voltage stability are realized by coupling the SIPPI with the PVEC electrolyte. Benefiting from this unique design, the Li symmetrical cell with the SIPPI shows stable cycling over 6000 h at 3 mA cm-2, and the full cell with the SIPPI exhibits stable cycling performance with a capacity retention of 86% over 1000 cycles at 1 C and 25 °C. This incorporated SIPPI on the Li anode presents an alternative strategy for enabling high-energy density, long cycling lifetime, and safe and cost-effective solid-state batteries.