Yi Cui, Postdoctoral Faculty Sponsor
Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100m, that are small enough that they do not settle out of solution. Colloidal robots are particles capable of functions such as sensing, computation, communication, locomotion and energy management that are all controlled by the particle itself. Their design and synthesis is an emerging area of interdisciplinary research drawing from materials science, colloid science, self-assembly, robophysics and control theory. Many colloidal robot systems approach synthetic versions of biological cells in autonomy and may find ultimate utility in bringing these specialized functions to previously inaccessible locations. This Perspective examines the emerging literature and highlights certain design principles and strategies towards the realization of colloidal robots.
View details for DOI 10.1038/s41563-023-01589-y
View details for PubMedID 37620646
- Colloidal State Machines as Smart Tracers for Chemical Reactor Analysis ADVANCED INTELLIGENT SYSTEMS 2023
- Synergistic multi-source ambient RF and thermal energy harvester for green IoT applications ENERGY REPORTS 2023; 9: 1875-1885
Investigations of Vacancy-Assisted Selective Detection of NO2 Molecules in Vertically Aligned SnS2.
2023; 8 (3): 1357-1367
Two important methods for enhancing gas sensing performance are vacancy/defect and interlayer engineering. Tin sulfide (SnS2) has recently attracted much attention for sensing of the NO2 gas due to its active surface sites and tunable electronic structure. Herein, SnS2 has been synthesized by the chemical vapor deposition (CVD) method followed by nitrogen plasma treatment with different exposure times for fast detection of NO2 molecules. Plasma treatment created a substantial number of surface vacancies on SnS2 flakes, which were controlled by the exposure period to modify the surface of flakes. After 12 min of nitrogen plasma treatment, SnS2 nanoflakes show considerable improvement in NO2 sensing characteristics, including a high sensing response of 264% toward 100 ppm NO2 at 120°C. The enhancement in the relative response of the sensor is due to the electronic interaction between NO2 molecules and the S vacancies on the surface of SnS2. Density functional theory (DFT) computations indicate that the S-vacancy defects on the surface dominate the effective NO2 detection and the NO2 adsorption mechanism transition from physisorption to chemisorption. Adsorption kinetics of the NO2 gas over SnS2 nanoflake-based chemiresistor sensors were studied using the Lee and Strano model [ Langmuir 2005, 21(11), 5192-5196]. The irreversible rate of the reaction for various NO2 concentrations exposed to the gas sensor is extracted using this model, which also appropriately describes the response curves. The forward rate constant of the irreversible gas sensor increased with the increase of the N2 plasma treatment time and reached the maximum in the 12 min plasma-treated sample. Through defect engineering, this research may open up new vistas for the design and synthesis of 2D materials with enhanced sensing properties.
View details for DOI 10.1021/acssensors.3c00133
View details for PubMedID 36921259
Emergent microrobotic oscillators via asymmetry-induced order
2022; 13 (1): 5734
Spontaneous oscillations on the order of several hertz are the drivers of many crucial processes in nature. From bacterial swimming to mammal gaits, converting static energy inputs into slowly oscillating power is key to the autonomy of organisms across scales. However, the fabrication of slow micrometre-scale oscillators remains a major roadblock towards fully-autonomous microrobots. Here, we study a low-frequency oscillator that emerges from a collective of active microparticles at the air-liquid interface of a hydrogen peroxide drop. Their interactions transduce ambient chemical energy into periodic mechanical motion and on-board electrical currents. Surprisingly, these oscillations persist at larger ensemble sizes only when a particle with modified reactivity is added to intentionally break permutation symmetry. We explain such emergent order through the discovery of a thermodynamic mechanism for asymmetry-induced order. The on-board power harvested from the stabilised oscillations enables the use of electronic components, which we demonstrate by cyclically and synchronously driving a microrobotic arm. This work highlights a new strategy for achieving low-frequency oscillations at the microscale, paving the way for future microrobotic autonomy.
View details for DOI 10.1038/s41467-022-33396-5
View details for Web of Science ID 000868657300013
View details for PubMedID 36229440
View details for PubMedCentralID PMC9561614
- Memristor Circuits for Colloidal Robotics: Temporal Access to Memory, Sensing, and Actuation ADVANCED INTELLIGENT SYSTEMS 2021
Solvent-induced electrochemistry at an electrically asymmetric carbon Janus particle.
2021; 12 (1): 3415
Chemical doping through heteroatom substitution is often used to control the Fermi level of semiconductor materials. Doping also occurs when surface adsorbed molecules modify the Fermi level of low dimensional materials such as carbon nanotubes. A gradient in dopant concentration, and hence the chemical potential, across such a material generates usable electrical current. This opens up the possibility of creating asymmetric catalytic particles capable of generating voltage from a surrounding solvent that imposes such a gradient, enabling electrochemical transformations. In this work, we report that symmetry-broken carbon particles comprised of high surface area single-walled carbon nanotube networks can effectively convert exothermic solvent adsorption into usable electrical potential, turning over electrochemical redox processes in situ with no external power supply. The results from ferrocene oxidation and the selective electro-oxidation of alcohols underscore the potential of solvent powered electrocatalytic particles to extend electrochemical transformation to various environments.
View details for DOI 10.1038/s41467-021-23038-7
View details for PubMedID 34099639