Conformal Cytocompatible Ferrite Coatings Facilitate the Realization of a Nanovoyager in Human Blood

Controlled motion of artificial nanomotors in biological environments, such as blood, can lead to fascinating biomedical applications, ranging from targeted drug delivery to microsurgery and many more. In spite of the various strategies used in fabricating and actuating nanomotors, practical issues related to fuel requirement, corrosion, and liquid viscosity have limited the motion of nanomotors to model systems such as water, serum, or biofluids diluted with toxic chemical fuels, such as hydrogen peroxide. As we demonstrate here, integrating conformal ferrite coatings with magnetic nanohelices offer a promising combination of functionalities for having controlled motion in practical biological fluids, such as chemical stability, cytocompatibility, and the generated thrust. These coatings were found to be stable in various biofluids, including human blood, even after overnight incubation, and did not have significant influence on the propulsion efficiency of the magnetically driven nanohelices, thereby facilitating the first successful ``voyage'' of artificial nanomotors in human blood. The motion of the ``nanovoyager'' was found to show interesting stick-slip dynamics, an effect originating in the colloidal jamming of blood cells in the plasma. The system of magnetic ``nanovoyagers'' was found to be cytocompatible with C2C12 mouse myoblast cells, as confirmed using MTT assay and fluorescence microscopy observations of cell morphology. Taken together, the results presented in this work establish the suitability of the ``nanovoyager'' with conformal ferrite coatings toward biomedical applications.

A framework for post-silicon realization of arbitrary instruction extensions on reconfigurable data-paths

In this paper we present a framework for realizing arbitrary instruction set extensions (IE) that are identified post-silicon. The proposed framework has two components viz., an IE synthesis methodology and the architecture of a reconfigurable data-path for realization of the such IEs. The IE synthesis methodology ensures maximal utilization of resources on the reconfigurable data-path. In this context we present the techniques used to realize IEs for applications that demand high throughput or those that must process data streams. The reconfigurable hardware called HyperCell comprises a reconfigurable execution fabric. The fabric is a collection of interconnected compute units. A typical use case of HyperCell is where it acts as a co-processor with a host and accelerates execution of IEs that are defined post-silicon. We demonstrate the effectiveness of our approach by evaluating the performance of some well-known integer kernels that are realized as IEs on HyperCell. Our methodology for realizing IEs through HyperCells permits overlapping of potentially all memory transactions with computations. We show significant improvement in performance for streaming applications over general purpose processor based solutions, by fully pipelining the data-path. (C) 2014 Elsevier B.V. All rights reserved.

A fully-nonlocal energy-based formulation and high-performance realization of the quasicontinuum method

The quasicontinuum (QC) method was introduced to coarse-grain crystalline atomic ensembles in order to bridge the scales from individual atoms to the micro- and mesoscales. Though many QC formulations have been proposed with varying characteristics and capabilities, a crucial cornerstone of all QC techniques is the concept of summation rules, which attempt to efficiently approximate the total Hamiltonian of a crystalline atomic ensemble by a weighted sum over a small subset of atoms. In this work we propose a novel, fully-nonlocal, energy-based formulation of the QC method with support for legacy and new summation rules through a general energy-sampling scheme. Our formulation does not conceptually differentiate between atomistic and coarse-grained regions and thus allows for seamless bridging without domain-coupling interfaces. Within this structure, we introduce a new class of summation rules which leverage the affine kinematics of this QC formulation to most accurately integrate thermodynamic quantities of interest. By comparing this new class of summation rules to commonly-employed rules through analysis of energy and spurious force errors, we find that the new rules produce no residual or spurious force artifacts in the large-element limit under arbitrary affine deformation, while allowing us to seamlessly bridge to full atomistics. We verify that the new summation rules exhibit significantly smaller force artifacts and energy approximation errors than all comparable previous summation rules through a comprehensive suite of examples with spatially non-uniform QC discretizations in two and three dimensions. Due to the unique structure of these summation rules, we also use the new formulation to study scenarios with large regions of free surface, a class of problems previously out of reach of the QC method. Lastly, we present the key components of a high-performance, distributed-memory realization of the new method, including a novel algorithm for supporting unparalleled levels of deformation. Overall, this new formulation and implementation allows us to efficiently perform simulations containing an unprecedented number of degrees of freedom with low approximation error.