Colloidal robotics.

Robots have components that work together to accomplish a task. Colloids are particles, usually less than 100 µm, 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.

Antibody-Free Rapid Detection of SARS-CoV-2 Proteins Using Corona Phase Molecular Recognition to Accelerate Development Time.

To develop better analytical approaches for future global pandemics, it is widely recognized that sensing materials are necessary that enable molecular recognition and sensor assay development on a much faster scale than currently possible. Previously developed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) point-of-care devices are based on the specific molecular recognition using subunit protein antibodies and protein receptors that selectively capture the viral proteins. However, these necessarily involve complex and lengthy development and processing times and are notoriously prone to a loss of biological activity upon sensor immobilization and device interfacing, potentially limiting their use in applications at scale. Here, we report a synthetic strategy for nanoparticle corona interfaces that enables the molecular recognition of SARS-CoV-2 proteins without any antibody and receptor design. Our nanosensor constructs consist of poly(ethylene glycol) (PEG)─phospholipid heteropolymers adsorbed onto near-infrared (nIR) fluorescent single-walled carbon nanotubes (SWCNTs) that recognize the nucleocapsid (N) and spike (S) protein of SARS-CoV-2 using unique three-dimensional (3D) nanosensor interfaces. This results in rapid and label-free nIR fluorescence detection. This antibody-free nanosensor shows up to 50% sensor responses within 5 min of viral protein injections with limit of detection (LOD) values of 48 fM and 350 pM for N and S proteins, respectively. Finally, we demonstrate instrumentation based on a fiber-optic platform that interfaces the advantages of antibody-free molecular recognition and biofluid compatibility in human saliva conditions.

Fluorinated Aromatic Diluent for High-Performance Lithium Metal Batteries.

In lithium metal batteries, electrolytes containing a high concentration of salts have demonstrated promising cyclability, but their practicality with respect to the cost of materials is yet to be proved. Here we report a fluorinated aromatic compound, namely 1,2-difluorobenzene, for use as a diluent solvent in the electrolyte to realize the "high-concentration effect". The low energy level of the lowest unoccupied molecular orbital (LUMO), weak binding affinity for lithium ions, and high fluorine-donating power of 1,2-difluorobenzene jointly give rise to the high-concentration effect at a bulk salt concentration near 2 m, while modifying the composition of the solid-electrolyte-interphase (SEI) layer to be rich in lithium fluoride (LiF). The employment of triple salts to prevent corrosion of the aluminum current collector further improves cycling performance. This study offers a design principle for achieving a local high-concentration effect with reasonably low bulk concentrations of salts.

Environmental damping and vibrational coupling of confined fluids within isolated carbon nanotubes.

Because of their large surface areas, nanotubes and nanowires demonstrate exquisite mechanical coupling to their surroundings, promising advanced sensors and nanomechanical devices. However, this environmental sensitivity has resulted in several ambiguous observations of vibrational coupling across various experiments. Herein, we demonstrate a temperature-dependent Radial Breathing Mode (RBM) frequency in free-standing, electron-diffraction-assigned Double-Walled Carbon Nanotubes (DWNTs) that shows an unexpected and thermally reversible frequency downshift of 10 to 15%, for systems isolated in vacuum. An analysis based on a harmonic oscillator model assigns the distinctive frequency cusp, produced over 93 scans of 3 distinct DWNTs, along with the hyperbolic trajectory, to a reversible increase in damping from graphitic ribbons on the exterior surface. Strain-dependent coupling from self-tensioned, suspended DWNTs maintains the ratio of spring-to-damping frequencies, producing a stable saturation of RBM in the low-tension limit. In contrast, when the interior of DWNTs is subjected to a water-filling process, the RBM thermal trajectory is altered to that of a Langmuir isobar and elliptical trajectories, allowing measurement of the enthalpy of confined fluid phase change. These mechanisms and quantitative theory provide new insights into the environmental coupling of nanomechanical systems and the implications for devices and nanofluidic conduits.

Rational Design and Efficacy of Glucose-Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models.

Glucose-responsive insulins (GRIs) use plasma glucose levels in a diabetic patient to activate a specifically designed insulin analogue to a more potent state in real time. Alternatively, some GRI concepts use glucose-mediated release or injection of insulin into the bloodstream. GRIs hold promise to exhibit much improved pharmacological control of the plasma glucose concentration, particularly for the problem of therapeutically induced hypoglycemia. Several innovative GRI schemes are introduced into the literature, but there remains a dearth of quantitative analysis to aid the development and optimization of these constructs into effective therapeutics. This work evaluates several classes of GRIs that are proposed using a pharmacokinetic model as previously described, PAMERAH, simulating the glucoregulatory system of humans and rodents. GRI concepts are grouped into three mechanistic classes: 1) intrinsic GRIs, 2) glucose-responsive particles, and 3) glucose-responsive devices. Each class is analyzed for optimal designs that maintain glucose levels within the euglycemic range. These derived GRI parameter spaces are then compared between rodents and humans, providing the differences in clinical translation success for each candidate. This work demonstrates a computational framework to evaluate the potential clinical translatability of existing glucose-responsive systems, providing a useful approach for future GRI development.

In Silico Investigation of the Clinical Translatability of Competitive Clearance Glucose-Responsive Insulins.

The glucose-responsive insulin (GRI) MK-2640 from Merck was a pioneer in its class to enter the clinical stage, having demonstrated promising responsiveness in in vitro and preclinical studies via a novel competitive clearance mechanism (CCM). The smaller pharmacokinetic response in humans motivates the development of new predictive, computational tools that can improve the design of therapeutics such as GRIs. Herein, we develop and use a new computational model, IM3PACT, based on the intersection of human and animal model glucoregulatory systems, to investigate the clinical translatability of CCM GRIs based on existing preclinical and clinical data of MK-2640 and regular human insulin (RHI). Simulated multi-glycemic clamps not only validated the earlier hypothesis of insufficient glucose-responsive clearance capacity in humans but also uncovered an equally important mismatch between the in vivo competitiveness profile and the physiological glycemic range, which was not observed in animals. Removing the inter-species gap increases the glucose-dependent GRI clearance from 13.0% to beyond 20% for humans and up to 33.3% when both factors were corrected. The intrinsic clearance rate, potency, and distribution volume did not apparently compromise the translation. The analysis also confirms a responsive pharmacokinetics local to the liver. By scanning a large design space for CCM GRIs, we found that the mannose receptor physiology in humans remains limiting even for the most optimally designed candidate. Overall, we show that this computational approach is able to extract quantitative and mechanistic information of value from a posteriori analysis of preclinical and clinical data to assist future therapeutic discovery and development.

Emergent microrobotic oscillators via asymmetry-induced order.

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.