Ju Li (ORCID:0000-0002-7841-8058)

Aqueous Zn‐ion batteries (AZIBs) are promising for grid‐scale energy storage. However, conventional AZIBs face challenges including hydrogen evolution reaction (HER), leading to high local pH, and by‐product formation on the anode. Hereby the hydrogen bonds in the aqueous electrolyte are reconstructed by using a deep eutectic co‐solvent (DES) made of acetamide (H‐bond donor) and caprolactam (H‐bond acceptor), which effectively suppresses the reactivity of water and broadens the electrochemical voltage stability window. The coordination between Zn2+ and acetamide‐caprolactam in DES‐based electrolytes produces a unique solvation structure that promotes the preferential growth of Zn crystals along the (002) plane. This will inhibit the formation of Zn dendrites and ensure the uniform deposition of Zn‐ions on the anode surface. In addition, it is found that this DES‐based electrolyte can form a …

A persistent challenge plaguing lithium-ion batteries (LIBs) is the consumption of active lithium with the formation of SEI. This leads to an irreversible lithium loss in the initial cycle and a gradual further exhaustion of active lithium in subsequent cycles. While prelithiation has been proven effective in compensating for this loss by introducing additional active lithium into batteries, prior studies have predominantly concentrated on offsetting the initial lithium loss, often overlooking the continuous lithium consumption that occurs throughout cycling. To address this challenge, we employed a sustained in situ lithium replenishment strategy that involves the systematic release of additional lithium inventory through precise capacity control during long-term cycling. Our method utilizes a lithium replenishment separator (LRS) coated with dilithium squarate-carbon nanotube (Li2C4O4–CNT) as the lithium compensation reagent …

We investigated the microstructure and mechanical properties of ZrB2 fortified Inconel 718 (In718+ZrB2) superalloy metal matrix composite (MMC), which was produced via Laser Powder Bed Fusion (LPBF). 2 vol% ZrB2 nano powders (below 100 nm in diameter) were decorated on the surfaces of Inconel 718 alloy powders by high-speed blender. Microstructural analysis of the as-printed specimens showed that the ZrB2 decomposed during LPBF, which promoted the formation of homogeneously distributed (Zr, Ni)-based intermetallic and (Nb, Mo, Cr)-based boride nanoparticles in the matrix. The 3D printed In718+ZrB2 has remarkably lower porosity and smaller grain size compared to 3D printed In718 fabricated under the same LPBF conditions. The mechanical performance of the as-printed and heat-treated In718+ZrB2 showed significantly higher room temperature (RT) hardness, RT yield strength (σYS), and …

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this work, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities …

Atomic diffusion in solids is an important process in various phenomena. However, atomistic simulations of diffusion processes are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interests. In this work, we developed a long-timescale method using reinforcement learning that extends simulation capability to match the duration of experimental interest. As a testbed, we simulate hydrogen diffusion in pure metals and a medium entropy alloy, CrCoNi. The algorithm can derive hydrogen diffusivity reasonably consistent with previous experiments. The algorithm can also recover counter-intuitive HV cooperative motion. We also demonstrate that our method can accelerate the sampling of low-energy configurations compared to the Metropolis-Hastings algorithm using hydrogen migration to copper (111) surface sites as an example.

Recent studies have reported the experimental discovery that nanoscale specimens of even a natural material, such as diamond, can be deformed elastically to as much as 10% tensile elastic strain at room temperature without the onset of permanent damage or fracture. Computational work combining ab initio calculations and machine learning (ML) algorithms has further demonstrated that the bandgap of diamond can be altered significantly purely by reversible elastic straining. These findings open up unprecedented possibilities for designing materials and devices with extreme physical properties and performance characteristics for a variety of technological applications. However, a general scientific framework to guide the design of engineering materials through such elastic strain engineering (ESE) has not yet been developed. By combining first-principles calculations with ML, we present here a general …

Neuromechanical simulations enable the study of how interactions between organisms and their physical surroundings give rise to behavior. NeuroMechFly is an open-source neuromechanical model of adult Drosophila, with data-driven morphological biorealism that enables a synergistic cross-talk between computational and experimental neuroscience.

Hydrogen embrittlement jeopardizes the use of high-strength steels in critical load-bearing applications. However, uncertainty regarding how hydrogen affects dislocation motion, owing to the lack of quantitative experimental evidence, hinders our understanding of hydrogen embrittlement. Here, by studying the well-controlled, cyclic, bow-out motions of individual screw dislocations in α-iron, we find that the critical stress for initiating dislocation motion in a 2 Pa electron-beam-excited H2 atmosphere is 27–43% lower than that in a vacuum environment, proving that hydrogen enhances screw dislocation motion. Moreover, we find that aside from vacuum degassing, cyclic loading and unloading facilitates the de-trapping of hydrogen, allowing the dislocation to regain its hydrogen-free behaviour. These findings at the individual dislocation level can inform hydrogen embrittlement modelling and guide the design of …