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Lithium metal batteries (LMBs), especially “anode-free“ LMBs, promise much higher energy density than current lithium-ion batteries but suffer from poor capacity retention. While novel electrolytes have been designed to extend cycle life in anode free LMBs, most of them contain a high fraction of fluorinated solvents or diluents that may cause environmental concerns. Herein, we report the design and synthesis of a group of nonfluorinated ether solvents (termed xME solvents). By substituting the methyl terminal group of 1,2-dimethoxy ethane (DME) with different alkyl groups, the solvation power of xME solvents was tuned to be weaker, leading to more ion pairing in electrolyte solvation structure. In anode free type Cu/LiFePO₄(Cu/LFP) cells, xME electrolytes in general show better capacity retention than DME-based electrolyte. Some xME electrolytes also show better oxidative stability than DME against aluminum and LiNi_0.8Mn_0.1Co_0.1O₂(NMC811) electrodes. While the general improvement in LMB cycle life and oxidative stability can be attributed to more ion pairing, the local variation within xME electrolytes indicates other factors are also important. Our work proposes a molecular design strategy to fine-tune ion solvation structure of nonfluorinated ether electrolytes for LMBs.

 

Models for open quantum systems, which play important roles in electron transport problems and quantum computing, must take into account the interaction of the quantum system with the surrounding environment. Although such models can be derived in some special cases, in most practical situations, the exact models are unknown and have to be calibrated. This paper presents a learning method to infer parameters in Markovian open quantum systems from measurement data. One important ingredient in the method is a direct simulation technique of the quantum master equation, which is designed to preserve the completely-positive property with guaranteed accuracy. The method is particularly helpful in the situation where the time intervals between measurements are large. The approach is validated with error estimates and numerical experiments.

 

As the size of real-world graphs continues to grow at an exponential rate, performing the Graph Convolutional Network (GCN) inference efficiently is becoming increasingly challenging. Prior works that employ a unified computing engine with a predefined computation order lack the necessary flexibility and scalability to handle diverse input graph datasets. In this paper, we introduce OPT-GCN, a chiplet-based accelerator design that performs GCN inference efficiently while providing flexibility and scalability through an architecture-algorithm co-design. On the architecture side, the proposed design integrates a unified computing engine in each chiplet and an active interposer, both of which are adaptable to efficiently perform the GCN inference and facilitate data communication. On the algorithm side, we propose dynamic scheduling and mapping algorithms to optimize memory access and on-chip computations for diverse GCN applications. Experimental results show that the proposed design provides a memory access reduction by a factor of 11.3×, 3.4×, 1.4× energy savings of 15.2×, 3.7×, 1.6× on average compared to HyGCN, AWB-GCN, and GCNAX, respectively. 

Fragmentation and evolution for the molecular shells of the compact H ii regions are less explored compared to their evolved counterparts. We map nine compact H ii regions with a typical diameter of 0.4 pc that are surrounded by molecular shells traced by CCH. Several to a dozen dense gas fragments probed by H$^{13}$CO$^+$ are embedded in these molecular shells. These gas fragments, strongly affected by the H ii region, have a higher surface density, mass, and turbulence than those outside the shells but within the same pc-scale natal clump. These features suggest that the shells swept up by the early H ii regions can enhance the formation of massive dense structures that may host the birth of higher mass stars. We examine the formation of fragments and find that fragmentation of the swept-up shell is unlikely to occur in these early H ii regions, by comparing the expected time scale of shell fragmentation with the age of H ii region. We propose that the appearance of gas fragments in these shells is probably the result of sweeping up pre-existing fragments into the molecular shell that has not yet fragmented. Taken together, this work provides a basis for understanding the interplay of star-forming sites with an intricate environment containing ionization feedback such as those observed in starburst regions.