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Large amounts of iron– and steelmaking slag and greenhouse gas are annually produced by the steel industry worldwide. Using Ca/Mg in the slag to capture and store the CO2 via mineral carbonation is a promising approach to the reduction of waste emissions. Since iron– and steelmaking slags are a mixture of numerous types of minerals, understanding the dissolution behavior of various phases in solution system is of critical importance for Ca/Mg recovery. In this work, seven Ca/Mg–bearing phases and four typical solutions were prepared and studied. Theoretical results indicated that the order of mineral solubility in aqueous solution is as follows: (CaO and Ca2SiO4) > (Ca3MgSi2O8, Ca2MgSi2O7, and MgO) > Ca2Al2SiO7 > MgCr2O4. A batch of leaching tests was conducted at room temperature, and the recovery yield of Ca/Mg was investigated. It was found that minerals show different dissolution behavior in various systems, and the metallic oxide phases exhibited a relatively higher solubility than silicate phases. The solubility of minerals in various systems was illustrated by radar plots. Moreover, leaching tests for silicate briquettes were performed to investigate the transformation mechanism. On the basis of the results, it was proposed that a silicic acid layer generated on the surface of briquettes in the leaching process, and could transform into porous silica phase via dehydration process. The formed Si–rich layer obstructed the dissolution of inner mineral leading to a low recovery efficiency of Ca/Mg.

The future technologies should center around the human beings. How to let human interact with various state-of-the-art technologies in a straightforward and intuitive way is a grand challenge. Currently human uses hands to interact with the world, however, there are so many scenarios that human is not able to use his hands to control multiple devices/equipment at the same time, for instance, while the hands are busy at carrying stuffs, driving or riding a bicycle. Oftentimes, people do not want to use voice command either. But humans are really good at multi-model interactions using body languages, eye and facial gestures to communicate with each other. It provides a good hint to use eye movements and facial expressions as a compensation to other existing interaction interfaces. In this research project, we aim to build a wearable device that is extremely compact, non-obtrusive, which can be worn comfortably for long hours to identify eye movements and facial expressions. We develop our product - EXGbuds to evaluate this idea of controlling the games in an engaging way.

This paper proposed a method using eye saccade and facial expression physiological signals to interpret human intentions as a mean to operate wearable robots. Our approach used only two electrodes placed on top of the left and right ears to identify high fidelity physiological signals. With the developed machine learning algorithms, we can achieve over 97% accuracy of the classified various human eye-facial gestures, which allows us to build up intuitive Human-Machine Interaction (HMI) strategies to let disable people operate exoskeletons or wheelchairs easily and naturally. This method also enables the design of earbud-like wearable device, which can be worn comfortably for long hours to provide ubiquitous controllability to operate external smart devices. The ultimate goal of this research is to seamlessly merge human and machine all together by just using a simple wearable device.

The fine tracking system is important to improve the performance of orbital angular momentum (OAM) space optical communication system. In order to improve the accuracy and stability of the centroid algorithm, this article proposes a modified algorithm to detect the center position of OAM light beam. The modified algorithm firstly takes a binary-conversion with the threshold based on the intensity profile of OAM beam, and then calculates the center position of the light spot using centroid algorithm. The threshold for binary-conversion of Laguerre-Gaussian (LG) beam is obtained by theoretical analysis and numerical calculation. The accuracy, stability and complexity of the modified algorithm are studied by numerical simulation. The results show that the new algorithm, compared with the centroid algorithm, has 2 orders of magnitude higher in computing accuracy and 3∼4 orders of magnitude higher in stability. However, the computing time has increased by about 1.5 times compared with the centroid algorithm.