Molecular-docking electrolytes enable high-voltage lithium battery chemistries.

Ideal rechargeable lithium battery electrolytes should promote the Faradaic reaction near the electrode surface while mitigating undesired side reactions. Yet, conventional electrolytes usually show sluggish kinetics and severe degradation due to their high desolvation energy and poor compatibility. Here we propose an electrolyte design strategy that overcomes the limitations associated with Li salt dissociation in non-coordinating solvents to enable fast, stable Li chemistries. The non-coordinating solvents are activated through favourable hydrogen bond interactions, specifically Fδ--Hδ+ or Hδ+-Oδ-, when blended with fluorinated benzenes or halide alkane compounds. These intermolecular interactions enable a dynamic Li+-solvent coordination process, thereby promoting the fast Li+ reaction kinetics and suppressing electrode side reactions. Utilizing this molecular-docking electrolyte design strategy, we have developed 25 electrolytes that demonstrate high Li plating/stripping Coulombic efficiencies and promising capacity retentions in both full cells and pouch cells. This work supports the use of the molecular-docking solvation mechanism for designing electrolytes with fast Li+ kinetics for high-voltage Li batteries.

Simultaneous Stabilization of Lithium Anode and Cathode using Hyperconjugative Electrolytes for High-voltage Lithium Metal Batteries.

Although great progress has been made in new electrolytes for lithium metal batteries (LMBs), the intrinsic relationship between electrolyte composition and cell performance remains unclear due to the lack of valid quantization method. Here, we proposed the concept of negative center of electrostatic potential (NCESP) and Mayer bond order (MBO) to describe solvent capability, which highly relate to solvation structure and oxidation potential, respectively. Based on established principles, the selected electrolyte with 1.7 M LiFSI in methoxytrimethylsilane (MOTMS)/ (trifluoromethyl)trimethylsilane (TFMTMS) shows unique hyperconjugation nature to stabilize both Li anode and high-voltage cathode. The 4.6 V 30 µm Li||4.5 mAh cm-2 lithium cobalt oxide (LCO) (low N/P ratio of 1.3) cell with our electrolyte shows stable cycling with 91 % capacity retention over 200 cycles. The bottom-up design concept of electrolyte opens up a general strategy for advancing high-voltage LMBs.

Toward Stable Co-Saliency Detection and Object Co-Segmentation.

In this paper, we present a novel model for simultaneous stable co-saliency detection (CoSOD) and object co-segmentation (CoSEG). To detect co-saliency (segmentation) accurately, the core problem is to well model inter-image relations between an image group. Some methods design sophisticated modules, such as recurrent neural network (RNN), to address this problem. However, order-sensitive problem is the major drawback of RNN, which heavily affects the stability of proposed CoSOD (CoSEG) model. In this paper, inspired by RNN-based model, we first propose a multi-path stable recurrent unit (MSRU), containing dummy orders mechanisms (DOM) and recurrent unit (RU). Our proposed MSRU not only helps CoSOD (CoSEG) model captures robust inter-image relations, but also reduces order-sensitivity, resulting in a more stable inference and training process. Moreover, we design a cross-order contrastive loss (COCL) that can further address order-sensitive problem by pulling close the feature embedding generated from different input orders. We validate our model on five widely used CoSOD datasets (CoCA, CoSOD3k, Cosal2015, iCoseg and MSRC), and three widely used datasets (Internet, iCoseg and PASCAL-VOC) for object co-segmentation, the performance demonstrates the superiority of the proposed approach as compared to the state-of-the-art (SOTA) methods.