Coexisting Cooperative Cognitive Micro‐/Nanorobots

A Robot Platform for Highly Efficient Pollutant Purification

In this study, we propose a highly efficient robot platform for pollutant adsorption. This robot system consists of a flapping-wing micro aircraft (FWMA) for long-distance transportation and delivery and cost-effective multifunctional Janus microrobots for pollutant purification. The flapping-wing micro air vehicle can hover for 11.3 km with a flapping frequency of approximately 15 Hz, fly forward up to 31.6 km/h, and drop microrobots to a targeted destination. The Janus microrobot, which is composed of a silica microsphere, nickel layer, and hydrophobic layer, is used to absorb the oil and process organic pollutants. These Janus microrobots can be propelled fast up to 9.6 body lengths per second, and on-demand speed regulation and remote navigation are manageable. These Janus microrobots can continuously carry oil droplets in aqueous environments under the control of a uniform rotating magnetic field. Because of the fluid dynamics induced by the Janus microrobots, a highly efficient removal of Rhodamine B is accomplished. This smart robot system may open a door for pollutant purification.

Artificial Intelligent Multi-Modal Point-of-Care System for Predicting Response of Transarterial Chemoembolization in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) ranks the second most lethal tumor globally and is the fourth leading cause of cancer-related death worldwide. Unfortunately, HCC is commonly at intermediate tumor stage or advanced tumor stage, in which only some palliative treatment can be used to offer a limited overall survival. Due to the high heterogeneity of the genetic, molecular, and histological levels, HCC makes the prediction of preoperative transarterial chemoembolization (TACE) efficacy and the development of personalized regimens challenging. In this study, a new multi-modal point-of-care system is employed to predict the response of TACE in HCC by a concept of integrating multi-modal large-scale data of clinical index and computed tomography (CT) images. This multi-modal point-of-care predicting system opens new possibilities for predicting the response of TACE treatment and can help clinicians select the optimal patients with HCC who can benefit from the interventional therapy.

Recent development of autonomously driven micro/nanobots for efficient treatment of polluted water

Autonomously propelled micro/nanobots are one of the most advanced and integrated structures which have been fascinated researchers owing to its exceptional property that enables them to be carried out user-defined tasks more precisely even on an atomic scale. The unique architecture and engineering aspects of these manmade tiny devices make them viable options for widespread biomedical applications. Moreover, recent development in this line of interest demonstrated that micro/nanobots would be very promising for the water treatment as these can efficiently absorb or degrade the toxic chemicals from the polluted water based on their tunable surface chemistry. These auto propelled micro/nanobots catalytically degrade toxic pollutants into non-hazardous compounds more rapidly and effectively. Thus, for the last few decades, nanobots mediated water treatment gaining huge popularity due to its ease of operation and scope of guided motion that could be monitored by various external fields and stimuli. Also, these are economical, energy-saving, and suitable for large scale water treatment, particularly required for industrial effluents. However, the efficacy of these bots hugely relies on its design, characteristic of materials, properties of the medium, types of fuel, and surface functional groups. Minute variation for one of these things may lead to a change in its performance and hinders its dynamics of propulsion. It is deemed that nanobots might be a smart choice for using these as the new generation devices for treating industrial effluents before discharging it in the water bodies, which is a major concern for human health and the environment.

Non-oscillatory micromotors “learn” to oscillate on-the-fly from oscillating Ag micromotors

Oscillating Ag-containing micromotors release silver ions that diffuse and deposit on the surface of Au–Rh microrods, which then learn to oscillate individually or collectively as a wave.