Chen Liu

Bio: Chen Liu is an academic researcher from Shenzhen University. The author has contributed to research in topics: Energy consumption & Hardware acceleration. The author has an hindex of 15, co-authored 145 publications receiving 957 citations. Previous affiliations of Chen Liu include Guangxi Normal University & Chinese Academy of Sciences.

Epitaxially grown monolayer VSe 2 : an air-stable magnetic two-dimensional material with low work function at edges

Abstract: Recent experimental breakthroughs open up new opportunities for magnetism in few-atomic-layer two-dimensional (2D) materials, which makes fabrication of new magnetic 2D materials a fascinating issue. Here, we report the growth of monolayer VSe2 by molecular beam epitaxy (MBE) method. Electronic properties measurements by scanning tunneling spectroscopy (STS) method revealed that the as-grown monolayer VSe2 has magnetic characteristic peaks in its electronic density of states and a lower work-function at its edges. Moreover, air exposure experiments show air-stability of the monolayer VSe2. This high-quality monolayer VSe2, a very air-inert 2D material with magnetism and low edge work function, is promising for applications in developing next-generation low power-consumption, high efficiency spintronic devices and new electrocatalysts.

Big Data Analytics for Electric Vehicle Integration in Green Smart Cities

Abstract: The huge amount of data generated by devices, vehicles, buildings, the power grid, and many other connected things, coupled with increased rates of data transmission, constitute the big data challenge. Among many areas associated with the Internet of Things, smart grid and electric vehilces have their share of this challenge by being both producers and consumers (ie., prosumers) of big data. Electric vehicls can significantly help smart cities to become greener by reducing emissions of the transportation sector and play an important role in green smart cities. In this article, we first survey the data analytics techniques used for handling the big data of smart grid and electric vehicles. The data generated by electric vehicles come from sources that vary from sensors to trip logs. Once this vast amount of data are analyzed using big data techniques, they can be used to develop policies for siting charging stations, developing smart charging algorithms, solving energy efficiency issues, evaluating the capacity of power distribution systems to handle extra charging loads, and finally, determining the market value for the services provided by electric vehicles (i.e., vehicle-to-grid opportunities). This article provides a comprehensive overview of the data analytics landscape on the electric vehicle integration to green smart cities. It serves as a roadmap to the future data analytics needs and solutions for electric vehicle integration to smart cities.

In-situ intermolecular interaction in composite polymer electrolyte for ultralong life quasi-solid-state lithium metal batteries.

Abstract: Solid-state lithium metal batteries built with composite polymer electrolytes using cubic garnets as active fillers are particularly attractive owing to their high energy density, easy manufacturing and inherent safety. However, the uncontrollable formation of intractable contaminant on garnet surface usually aggravates poor interfacial contact with polymer matrix and deteriorates Li + pathways. Here we report a rational designed intermolecular interaction in composite electrolytes that utilizing contaminants as reaction initiator to generate Li + conducting ether oligomers, which further emerge as molecular cross-linkers between inorganic fillers and polymer matrix, creating dense and homogeneous interfacial Li + immigration channels in the composite electrolytes. The delicate design results in a remarkable ionic conductivity of 1.43×10 -3 S cm -1 and an unprecedented 1000 cycles with 90% capacity retention at room temperature is achieved for the assembled solid-state batteries.

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

Bactericidal and Cytotoxic Properties of Silver Nanoparticles.

Abstract: Silver nanoparticles (AgNPs) can be synthesized from a variety of techniques including physical, chemical and biological routes. They have been widely used as nanomaterials for manufacturing cosmetic and healthcare products, antimicrobial textiles, wound dressings, antitumor drug carriers, etc. due to their excellent antimicrobial properties. Accordingly, AgNPs have gained access into our daily life, and the inevitable human exposure to these nanoparticles has raised concerns about their potential hazards to the environment, health, and safety in recent years. From in vitro cell cultivation tests, AgNPs have been reported to be toxic to several human cell lines including human bronchial epithelial cells, human umbilical vein endothelial cells, red blood cells, human peripheral blood mononuclear cells, immortal human keratinocytes, liver cells, etc. AgNPs induce a dose-, size- and time-dependent cytotoxicity, particularly for those with sizes ≤10 nm. Furthermore, AgNPs can cross the brain blood barrier of mice through the circulation system on the basis of in vivo animal tests. AgNPs tend to accumulate in mice organs such as liver, spleen, kidney and brain following intravenous, intraperitoneal, and intratracheal routes of administration. In this respect, AgNPs are considered a double-edged sword that can eliminate microorganisms but induce cytotoxicity in mammalian cells. This article provides a state-of-the-art review on the synthesis of AgNPs, and their applications in antimicrobial textile fabrics, food packaging films, and wound dressings. Particular attention is paid to the bactericidal activity and cytotoxic effect in mammalian cells.

Progress and Perspective of Ceramic/Polymer Composite Solid Electrolytes for Lithium Batteries

Abstract: Solid composite electrolytes (SCEs) that combine the advantages of solid polymer electrolytes (SPEs) and inorganic ceramic electrolytes (ICEs) present acceptable ionic conductivity, high mechanical strength, and favorable interfacial contact with electrodes, which greatly improve the electrochemical performance of all-solid-state batteries compared to single SPEs and ICEs. However, there are many challenges to overcome before the practical application of SCEs, including the low ionic conductivity less than 10-3 S cm-1 at ambient temperature, poor interfacial stability, and high interfacial resistance, which greatly restrict the room temperature performance. Herein, the advances of SCEs applied in all-solid-state lithium batteries are presented, including the Li ion migration mechanism of SCEs, the strategies to enhance the ionic conductivity of SCEs by various morphologies of ICEs, and construction methods of the low resistance and stable interfaces of SCEs with both cathode and anode. Finally, some typical applications of SCEs in lithium batteries are summarized and future development directions are prospected. This work presents how it is quite significant to further enhance the ionic conductivity of SCEs by developing the novel SPEs with the special morphology of ICEs for advanced all-solid-state lithium batteries.

Edge Computing for Autonomous Driving: Opportunities and Challenges

Abstract: Safety is the most important requirement for autonomous vehicles; hence, the ultimate challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver enough computing power, redundancy, and security so as to guarantee the safety of autonomous vehicles. Specifically, autonomous driving systems are extremely complex; they tightly integrate many technologies, including sensing, localization, perception, decision making, as well as the smooth interactions with cloud platforms for high-definition (HD) map generation and data storage. These complexities impose numerous challenges for the design of autonomous driving edge computing systems. First, edge computing systems for autonomous driving need to process an enormous amount of data in real time, and often the incoming data from different sensors are highly heterogeneous. Since autonomous driving edge computing systems are mobile, they often have very strict energy consumption restrictions. Thus, it is imperative to deliver sufficient computing power with reasonable energy consumption, to guarantee the safety of autonomous vehicles, even at high speed. Second, in addition to the edge system design, vehicle-to-everything (V2X) provides redundancy for autonomous driving workloads and alleviates stringent performance and energy constraints on the edge side. With V2X, more research is required to define how vehicles cooperate with each other and the infrastructure. Last, safety cannot be guaranteed when security is compromised. Thus, protecting autonomous driving edge computing systems against attacks at different layers of the sensing and computing stack is of paramount concern. In this paper, we review state-of-the-art approaches in these areas as well as explore potential solutions to address these challenges.

Atomic-scale control of graphene magnetism by using hydrogen atoms

Abstract: Hydrogen atom makes graphene magnetic Graphene has many extraordinary mechanical and electronic properties, but it's not magnetic. To make it so, the simplest strategy is to modify its electronic structure to create unpaired electrons. Researchers can do that by, for example, removing individual carbon atoms or adsorbing hydrogen onto graphene. This has to be done in a very controlled way because of a peculiarity of the graphene's crystal lattice, which consists of two sublattices. Gonzales-Herrero et al. deposited a single hydrogen atom on top of graphene and used scanning tunneling microscopy to detect magnetism on the sublattice lacking the deposited atom (see the Perspective by Hollen and Gupta). Science, this issue p. 437; see also p. 415 Scanning tunneling microscopy shows that a hydrogen atom deposited on graphene makes the complementary sublattice magnetic. [Also see Perspective by Hollen and Gupta] Isolated hydrogen atoms absorbed on graphene are predicted to induce magnetic moments. Here we demonstrate that the adsorption of a single hydrogen atom on graphene induces a magnetic moment characterized by a ~20–millielectron volt spin-split state at the Fermi energy. Our scanning tunneling microscopy (STM) experiments, complemented by first-principles calculations, show that such a spin-polarized state is essentially localized on the carbon sublattice opposite to the one where the hydrogen atom is chemisorbed. This atomically modulated spin texture, which extends several nanometers away from the hydrogen atom, drives the direct coupling between the magnetic moments at unusually long distances. By using the STM tip to manipulate hydrogen atoms with atomic precision, it is possible to tailor the magnetism of selected graphene regions.