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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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DOE OSTI2024

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Nanomotor-enhanced transport of passive Brownian particles in porous media

Artificial micro/nanomotors are expected to perform tasks in interface-rich and species-rich environments for biomedical and environmental applications. In these highly confined and interconnected pore spaces, active species may influence the motion of coexisting passive participants in unexpected ways. Using three-dimensional super-resolution single-nanoparticle tracking, we observed enhanced motion of passive nanoparticles due to the presence of dilute well-separated nanomotors in an interconnected pore space. This enhancement acted at distances that are large compared to the sizes of the particles and cavities, in contrast with the insignificant effect on the passive particles with the same dilute concentration of nanomotors in an unconfined liquid. Experiments and simulations suggested an amplification of hydrodynamic coupling between self-propelled and passive nanoparticles in the interconnected confined environment, which enhanced the effective energy for passive particles to escape cavities through small holes. This finding represents an emergent behavior of confined nanomotors and suggests new strategies for the development of antifouling membranes and drug delivery systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Potential-Dependent Adhesion Forces between dsDNA and Electroactive Surfaces

A promising approach to regulating the interactions between polyelectrolytes and materials is the use of electroactive surfaces that can change their charge state. However, common electroactive groups are too unstable to be practical for this purpose. Here we have performed a single molecule force spectroscopy study of the interactions between dsDNA and an 1,1'-biferrocenylene (BFD = bis(fulvalene)diiron)-terminated self-assembled monolayer surface that allows us to reversibly change the charge state. We found that the interaction force between DNA and the surface is correlated to the oxidation state of the BFD groups, which is conveniently controlled by the electrochemical potentials. We discovered that the electroactive SAM produces much stronger interaction forces than its nonelectroactive counterpart. A model based on the Grahame equation was able to quantitatively reproduce the experimentally observed relation between the applied potentials and adhesion forces. Our electroactive surface provides a model system for quantitative studies of the interactions between polyelectrolyte and charged surfaces in liquid. Furthermore, these insights may enable new opportunities for actively manipulating the binding, orientations, and conformations of polyelectrolytes for biosensing, nanomotors, and other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Automating Bayesian inference and design to quantify acoustic particle levitation

Self-propulsion of micro- and nanoparticles powered by ultrasound provides an attractive strategy for the remote manipulation of colloidal matter using biocompatible energy inputs. Quantitative understanding of particle motion and its dependence on size, shape, and composition requires accurate characterization of the acoustic field, which depends sensitively on the experimental setup. Here, we show how automated experiments based on Bayesian inference and design can accurately and efficiently characterize the acoustic field within resonant chambers used to propel acoustic nanomotors. Repeated cycles of observation, inference, and design (OID) are guided by a physical model that describes the rate at which levitating particles approach the nodal plane. Using video microscopy, we observe the relaxation of tracer particles to this plane following the application of the acoustic field. We use sequential Monte Carlo methods to infer model parameters such as the amplitude and frequency of the resonant chamber while accounting for particle-level measurement noise and population-level heterogeneity in the field. Guided by simulated outcomes, we select the optimal design for the next experiment as to maximize the information gain in the relevant parameters. We show how this iterative process serves to discriminate between competing hypotheses and efficiently converges to accurate parameter estimates using only few automated experiments. We discuss the need for model criticism to ensure the validity of the guiding model throughout automated cycles of observation, inference, and design. Furthermore, this work demonstrates how Bayesian methods can learn the parameters of nonlinear, hierarchical models used to describe video microscopy data of active colloids.

42 ENGINEERING↗

DOE OSTI2022

Designing, synthesizing, and modeling active fluids

We review recent advances in the design, synthesis, and modeling of active fluids. Active fluids have been at the center of many technological innovations and theoretical advances over the past two decades. Research on this new class of fluids has been inspired by the fascinating and remarkably efficient strategies that biological systems employ, leading to the development of biomimetic nano- and micro-machines and swimmers. The review encompasses active fluids on both the nano- and micro-scale. We start with examples of biological active systems before we discuss how experimentalists leverage novel propulsion mechanisms to power nano- and micro-machines. Furthermore, we then examine how the study of these far-from-equilibrium systems has prompted the development of new simulation methods and theoretical models in nonequilibrium physics to account for their mechanical, thermodynamic, and emergent properties. Recent advances in the field have paved the way for the design, synthesis, and modeling of autonomous systems at the nano- and micro-scale and opened the door to the development of soft matter robotics.

36 MATERIALS SCIENCE↗