Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm

Post-earthquake rescue missions are full of challenges due to the unstable structure of ruins and successive aftershocks.Most of the current rescue robots lack the ability to interact with environments,leading to low rescue efficiency.The multimodal electronic skin(e-skin)proposed not only reproduces the pressure,temperature,and humidity sensing capabilities of natural skin but also develops sensing functions beyond it—perceiving object proximity and NO2 gas.Its multilayer stacked structure based on Ecoflex and organohydrogel endows the e-skin with mechanical properties similar to natural skin.Rescue robots integrated with multimodal e-skin and artificial intelligence(AI)algorithms show strong environmental perception capabilities and can accurately distinguish objects and identify human limbs through grasping,laying the foundation for automated post-earthquake rescue.Besides,the combination of e-skin and NO2 wireless alarm circuits allows robots to sense toxic gases in the environment in real time,thereby adopting appropriate measures to protect trapped people from the toxic environment.Multimodal e-skin powered by AI algorithms and hardware circuits exhibits powerful environmental perception and information processing capabilities,which,as an interface for interaction with the physical world,dramatically expands intelligent robots’application scenarios.

An Improved Hybrid Genetic Algorithm for Chemical Plant Layout Optimization with Novel Non-overlapping and Toxic Gas Dispersion Constraints

New approaches for facility distribution in chemical plants are proposed including an improved non-overlapping constraint based on projection relationships of facilities and a novel toxic gas dispersion constraint. In consideration of the large number of variables in the plant layout model, our new method can significantly reduce the number of variables with their own projection relationships. Also, as toxic gas dispersion is a usual incident in a chemical plant, a simple approach to describe the gas leakage is proposed, which can clearly represent the constraints of potential emission source and sitting facilities. For solving the plant layout model, an improved genetic algorithm (GA) based on infeasible solution fix technique is proposed, which improves the globe search ability of GA. The case study and experiment show that a better layout plan can be obtained with our method, and the safety factors such as gas dispersion and minimum distances can be well handled in the solution.

Enhancement of Toxic Gas Detecting Ability of Film Type Colorimetric Sensor

In this study, we tried to develop the in situ coating methods of hydrophilic polymer solution containing water soluble dye on nonwoven sheet for the colorimetric film sensor. And color change of coated dye according to contact various gas samples (as strong acid and base, chloroform, ammonia and HF) of this dye-coated nonwoven film was examined for the application of chemically toxic materials detecting tools in the actual site of working place without aid of any kinds of detecting devices. By the addition of electron transfer agent (quinone derivatives), quick color change behaviors were observed within 10 seconds under the contact of various toxic gases in general condition(room temperature, 50% humidity).

Toxic Gas Put 161 Workers of Jilin Chemical Fiber Plant in Hospital

A news briefing held on May 13 by local government in Jilin city of Jilin province released that 161 workers got sick symptoms as a result of their contact with an unidentified gas emitting from Jilin Chemical Fiber Group Corp.

Distribution and treatment of harmful gas from heavy oil production in the Liaohe Oilfield, Northeast China

The distribution and treatment of harmful gas （H2S） in the Liaohe Oilfield, Northeast China, were investigated in this study. It was found that abundant toxic gas （H2S） is generated in thermal recovery of heavy oil. The H2S gas is mainly formed during thermochemical sulfate reduction （TSR） occurring in oil reservoirs or the thermal decomposition of sulfocompounds （TDS） in crude oil. H2S generation is controlled by thermal recovery time, temperature and the injected chemical compounds. The quantity of SO4^2- in the injected compounds is the most influencing factor for the rate of TSR reaction. Therefore, for prevention of H2S formation, periodic and effective monitoring should be undertaken and adequate H2S absorbent should also be provided during thermal recovery of heavy oil. The result suggests that great efforts should be made to reduce the SO4^2- source in heavy oil recovery, so as to restrain H2S generation in reservoirs. In situ burning or desulfurizer adsorption are suggested to reduce H2S levels. Prediction and prevention of H2S are important in heavy oil production. This will minimize environmental and human health risks, as well as equipment corrosion.

A Review of Metal–Organic Framework-Based Compounds for Environmental Applications

Metal–organic framework-based compounds have recently gained great attention because of their unique porous structure,ordered porosity,and high specific surface area.Benefiting from these superior properties,metal–organic framework-based compounds have been proven to be one of the most potential candidates for environmental governance and remediation.In this review,the different types of metal–organic framework-based compounds are first summarized.Further,the various environmental applications of metal–organic framework-based compounds including organic pollutant removal,toxic and hazardous gas capture,heavy metal ion detection,gas separation,water harvesting,air purification,and carbon dioxide reduction reactions are discussed in detail.In the end,the opportunities and challenges for the future development of metal–organic framework-based compounds for environmental applications are highlighted.