University of Electronic Science and Technology of China

About: University of Electronic Science and Technology of China is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Computer science & Antenna (radio). The organization has 50594 authors who have published 58502 publications receiving 711188 citations. The organization is also known as: UESTC.

Recent progress in the electrochemical ammonia synthesis under ambient conditions

Abstract: Ammonia not only serves as a building block for nitrogen-rich fertilizer, but offers a carbon-free energy carrier. At present, industrial ammonia synthesis is dominated by the Hablocker-Bosch process under high temperature and pressure, resulting in high energy consumption and serious environmental issues. Considerable recent at tention has focused on designing electrocatalysts for the N2 reduction reaction (NRR). However, the ammonia synthesis through electrocatalytic N2 reduction is still far from practical applications. In this review, recent theoretical and experiment investigations on various catalysts for the ammonia synthesis under mild conditions are highlighted. Firstly, the mechanisms for the electrochemical NRR are reviewed briefly. Then, based on these mechanisms, various catalysts, such as noble metal catalysts, non-noble metal catalysts, metal-free catalysts and even single atoms catalysts, for ammonia production are reviewed, with a particular focus on the improvement of the catalytic activity and selectivity toward ammonia production through optimizing the electrolyte, pH and the structure of the catalyst, etc. Lastly, the challenges and outlook for the ammonia synthesis are shown. This review systematically retrospects recent advances in the electrocatalytic NRR to show the readers a thorough understanding in this field. Most importantly, this review sheds some light toward the future development of electrocatalytic NRR.

Toward a Better Understanding of Model Validation Metrics

Abstract: Model validation metrics have been developed to provide a quantitative measure that characterizes the agreement between predictions and observations. In engineering design, the metrics become useful for model selection when alternative models are being considered. Additionally, the predictive capability of a computational model needs to be assessed before it is used in engineering analysis and design. Due to the various sources of uncertainties in both computer simulations and physical experiments, model validation must be conducted based on stochastic characteristics. Currently there is no unified validation metric that is widely accepted. In this paper, we present a classification of validation metrics based on their key characteristics along with a discussion of the desired features. Focusing on stochastic validation with the consideration of uncertainty in both predictions and physical experiments, four main types of metrics, namely classical hypothesis testing, Bayes factor, frequentist’s metric, and area metric, are examined to provide a better understanding of the pros and cons of each. Using mathematical examples, a set of numerical studies are designed to answer various research questions and study how sensitive these metrics are with respect to the experimental data size, the uncertainty from measurement error, and the uncertainty in unknown model parameters. The insight gained from this work provides useful guidelines for choosing the appropriate validation metric in engineering applications. [DOI: 10.1115/1.4004223]

Robust Cooperative Beamforming and Artificial Noise Design for Physical-Layer Secrecy in AF Multi-Antenna Multi-Relay Networks

Abstract: This paper is concerned with an optimization problem in a two-hop relay wiretap channel, wherein multiple multi-antenna relays collaboratively amplify and forward (AF) information from a single-antenna source to a single-antenna destination, and at the same time emit artificial noise (AN) to improve physical-layer information security in the presence of multiple multi-antenna eavesdroppers (or Eves). More specifically, the problem is to simultaneously optimize the AF matrices and AN covariances for secrecy rate maximization, with robustness against imperfect channel state information of Eves via a worst-case robust formulation. Such a problem is nonconvex, and we propose a polynomial-time optimization solution based on a two-level optimization approach and semidefinite relaxation (SDR). In particular, while SDR is generally an approximation technique, we prove that SDR is optimal in the specific context here. This desirable result is obtained by careful reformulation and Karush-Kuhn-Tucker optimality analysis, where, rather interestingly, AN is found to be instrumental in providing guarantee of SDR optimality. Simulation results are provided, and the results show that the proposed joint AF-AN solution can attain considerably higher achievable secrecy rates than some existing suboptimal designs.