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The development of devices that improve thermal energy management requires thermal regulation with efficiency comparable to the ratios R ∼ 105 in electric regu- lation. Unfortunately, current materials and devices in thermal regulators have only been reported to achieve R ∼ 10. We use atomistic simulations to demonstrate that Ferrocenyl (Fc) molecules under applied external electric fields can alter charge states and achieve high thermal switch ratios R = Gq/G0, where Gq and G0 are the high and low limiting conductances. When an electric field is applied, Fc molecules are positively charged and the SAM-Au interfacial interaction is strong, leading to high heat conductance Gq. On the other hand, with no electric field, the Fc molecules are charge neutral and the SAM-Au interfacial interaction is weak, leading to low heat conductance G0. We optimized various design parameters for the device performance, including the Au-to-Au gap distance L, the system operation temperature T, the net charge on Fc molecules q, the Au surface charge number Z, and the SAM number N. We find that Gq can be very large and increases with increasing q, Z, or N, while G0 is near 0 at L > 3.0 nm. As a result, R > 100 was achieved for selected parameter ranges reported here. 

We have pursued the use of polymer-networked engineered nanoparticles as a candidate material capable of retaining information or perhaps even processing information in some prescribed way. Such operations would be of use for the neuromorphic engineering of materials that can compute intrinsically—that is, that they are in no way subject to a von Neumann architecture—and they have been identified as autonomous computing materials. Using trajectories integrated to much longer time steps than previously observed, we can now confirm that the response of the polymer-networked engineered nanoparticle arrays are highly sensitive to external perturbations. That is, the specific internal connections around given nanopar- ticles can be assigned to states useful for information processing, and the variations in their physical properties can result in specific responses allowing the state to be read. Moreover, their resulting equilibrium properties also depend on such external driving, and hence are subject to control which is a minimal requirement for these materials to be candidates for autonomous computing. We also demonstrate that using long polymer chains can help regulate the networks structures by increasing the 1st nearest links and reducing other links. 

DNA nanotechnology has broad applications in biomedical drug delivery and pro- grammable materials. Characterization of the self-assembly of DNA origami and quan- tum dots (QDs) is necessary for the development of new DNA-based nanostructures. We use computation and experiment to show that the self-assembly of 3D hierarchi- cal nanostructures can be controlled by programming the binding site number and their positions on DNA origami. Using biotinylated pentagonal pyramid wireframe DNA origamis and streptavidin capped QDs, we demonstrate that DNA origami with 1 binding site at the outer vertex can assemble multi-meric origamis with up to 6 DNA origamis on 1 QD, and DNA origami with 1 binding site at the inner center can only assemble monomeric and dimeric origamis. Meanwhile, the yield percentages of differ- ent multi-meric origamis are controlled by the QD:DNA-origami stoichiometric mixing ratio. DNA origamis with 2 binding sites at the αγ positions (of the pentagon) make larger nanostructures than those with binding sites at the αβ positions. In general, increasing the number of binding sites leads to increases in the nanostructure size. At high DNA origami concentration, the QD number in each cluster becomes the limiting factor for the growth of nanostructures. We find that reducing the QD size can also affect the self-assembly because of the reduced access to the binding sites from more densely packed origamis.