Functional carbon nanomembrane: microfabrication and functionalization

Carbon nanomembranes (CNMs) are fabricated via cross-linking the aromatic self-assembled monolayers (SAMs) with low-energy electron irradiation. As the first reported organic 2D material, CNMs possess numerous special properties such as ultimate thinness, high mechanical stability, high tunnelling resistance, homogeneous porosity, adjustable chemical functionality and high transmittance to light. This thesis demonstrates the electrochemical delamination (ECD) assisted transfer and the chemical functionalization of CNMs and their applications in different fields including selective ion sieving, fabricating optical metasurfaces, immobilizing biospecimens for cryogenic electron microscopy (cyroEM) imaging and building photo-switchable graphene field-effect transistor (GFET). The properties of the fabricated CNMs and CNMs based materials (or devices) were characterized employing complementary methods such as transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, atomic force microscopy (AFM) as well as surface plasmon resonance (SPR) measurements etc

Optimization-based Framework for Stability and Robustness of Bipedal Walking Robots

As robots become more sophisticated and move out of the laboratory, they need to be able to reliably traverse difficult and rugged environments. Legged robots -- as inspired by nature -- are most suitable for navigating through terrain too rough or irregular for wheels. However, control design and stability analysis is inherently difficult since their dynamics are highly nonlinear, hybrid (mixing continuous dynamics with discrete impact events), and the target motion is a limit cycle (or more complex trajectory), rather than an equilibrium. For such walkers, stability and robustness analysis of even stable walking on flat ground is difficult. This thesis proposes new theoretical methods to analyse the stability and robustness of periodic walking motions. The methods are implemented as a series of pointwise linear matrix inequalities (LMI), enabling the use of convex optimization tools such as sum-of-squares programming in verifying the stability and robustness of the walker. To ensure computational tractability of the resulting optimization program, construction of a novel reduced coordinate system is proposed and implemented. To validate theoretic and algorithmic developments in this thesis, a custom-built “Compass gait” walking robot is used to demonstrate the efficacy of the proposed methods. The hardware setup, system identification and walking controller are discussed. Using the proposed analysis tools, the stability property of the hardware walker was successfully verified, which corroborated with the computational results

Diverse Feature Blend Based on Filter-Bank Common Spatial Pattern and Brain Functional Connectivity for Multiple Motor Imagery Detection

Motor imagery (MI) based brain-computer interface (BCI) is a research hotspot and has attracted lots of attention. Within this research topic, multiple MI classification is a challenge due to the difficulties caused by time-varying spatial features across different individuals. To deal with this challenge, we tried to fuse brain functional connectivity (BFC) and one-versus-the-rest filter-bank common spatial pattern (OVR-FBCSP) to improve the robustness of classification. The BFC features were extracted by phase locking value (PLV), representing the brain inter-regional interactions relevant to the MI, whilst the OVR-FBCSP is used to extract the spatial-frequency features related to the MI. These diverse features were then fed into a multi-kernel relevance vector machine (MK-RVM). The dataset with three motor imagery tasks (left hand MI, right hand MI, and feet MI) was used to assess the proposed method. Experimental results not only showed that the cascade structure of diverse feature fusion and MK-RVM achieved satisfactory classification performance (average accuracy: 83.81%, average kappa: 0.76), but also demonstrated that BFC plays a supplementary role in the MI classification. Moreover, the proposed method has a potential to be integrated into multiple MI online detection owing to the advantage of strong time-efficiency of RVM

Inhibition of lithium dendrite formation in lithium metal batteries via regulated cation transport through ultrathin sub‐nanometer porous carbon nanomembranes

Suppressing Li dendrite growth has gained research interest due to the high theoretical capacity of Li metal anodes. Traditional Celgard membranes which are currently used in Li metal batteries fall short in achieving uniform Li flux at the electrode/electrolyte interface due to their inherent irregular pore sizes. Here, the use of an ultrathin (≈1.2 nm) carbon nanomembrane (CNM) which contains sub-nanometer sized pores as an interlayer to regulate the mass transport of Li-ions is demonstrated. Symmetrical cell analysis reveals that the cell with CNM interlayer cycles over 2x longer than the control experiment without the formation of Li dendrites. Further investigation on the Li plating morphology on Cu foil reveals highly dense deposits of Li metal using a standard carbonate electrolyte. A smoothed-particle hydrodynamics simulation of the mass transport at the anode–electrolyte interface elucidates the effect of the CNM in promoting the formation of highly dense Li deposits and inhibiting the formation of dendrites. A lithium metal battery fabricated using the LiFePO4 cathode exhibits a stable, flat voltage profile with low polarization for over 300 cycles indicating the effect of regulated mass transport.Published versio

Concept for a Future Super Proton-Proton Collider

Following the discovery of the Higgs boson at LHC, new large colliders are being studied by the international high-energy community to explore Higgs physics in detail and new physics beyond the Standard Model. In China, a two-stage circular collider project CEPC-SPPC is proposed, with the first stage CEPC (Circular Electron Positron Collier, a so-called Higgs factory) focused on Higgs physics, and the second stage SPPC (Super Proton-Proton Collider) focused on new physics beyond the Standard Model. This paper discusses this second stage.Comment: 34 pages, 8 figures, 5 table

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe