Publications by Type: Journal Article

2018
In-plane thermal conductivity measurement with nanosecond grating imaging tehchnique
J. Jeong, Chen, K., Walker, E. S., Roy, N., He, F., Liu, P., Willson, G. C., Cullinan, M., Bank, S. R., and Wang, Y., “In-plane thermal conductivity measurement with nanosecond grating imaging tehchnique,” Nanoscale and Microscale Thermophyical Engineering, vol. 22, no. 2, pp. 83-96, 2018. Publisher's VersionAbstract
We develop a nanosecond grating imaging (NGI) technique to measure in-plane thermal transport properties in bulk and thin-film samples. Based on nanosecond time-domain thermoreflectance (ns-TDTR), NGI incorporates a photomask with periodic metal strips patterned on a transparent dielectric substrate to generate grating images of pump and probe lasers on the sample surface, which induces heat conduction along both cross- and in-plane directions. Analytical and numerical models have been developed to extract thermal conductivities in both bulk and thin-film samples from NGI measurements. This newly developed technique is used to determine thickness-dependent in-plane thermal conductivities (κx) in Cu nano-films, which agree well with the electron thermal conductivity values converted from four-point electrical conductivity measurements using the Wiedemamn–Franz law, as well as previously reported experimental values. The κx measured with NGI in an 8 nm x 8 nm GaAs/AlAs superlattice (SL) is about 10.2 W/m⋅K, larger than the cross-plane thermal conductivity (8.8 W/m⋅K), indicating the anisotropic thermal transport in the SL structure. The uncertainty of the measured κx is about 25% in the Cu film and less than 5% in SL. Sensitivity analysis suggests that, with the careful selection of proper substrate and interface resistance, the uncertainty of κx in Cu nano-films can be as low as 5%, showing the potential of the NGI technique to determine κx in thin films with improved accuracy. By simply installing a photomask into ns-TDTR, NGI provides a convenient, fast, and cost-effective method to measure the in-plane thermal conductivities in a wide range of structures and materials.
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D. S. Choi, Poudel, N., Park, S., Akinwande, D., Cronin, S. B., Watanabe, K., Taniguchi, T., Yao, Z., and Shi, L., “Large Reduction of Hot Spot Temperature in Graphene Electronic Devices with Heat-Spreading Hexagonal Boron Nitride,” ACS Applied Materials & Interfaces, vol. 10 , pp. 11101–11107, 2018. Publisher's Version
S. Qu, Hu, M. - B., Wang, Y., and Song, T., “Modeling the influences of Ag or Au nanoparticles on the solar energy absorption and photocatalytic properties of N-TiO2,” Optics Communications, vol. 407, pp. 375-380, 2018. Publisher's VersionAbstract
Metallic nanoparticles have unique optical properties such as localized surface plasmon resonance (LSPR) effect, which can be used to improve the energy absorption and photocatalytic properties of semiconductor bases. In this paper, we construct a model to study the influence of Ag or Au nanoparticles (cubes or spheres) on the solar energy absorption and photocatalytic properties of nitrogen doped TiO2 (or N-TiO2). Effects of specific nanoparticle coupling parameters, such as particle shape, size, doping period (metal–metal distance) and separation distance (metal–semiconductor distance), on the properties of N-TiO2 are studied in detail. We show that the photocurrent improvement can be optimized by setting suitable geometric parameters. In particular, the separation distance between metallic nanoparticles and N-TiO2D should be around 6–7 nm, and the period of doping P should be around 360 nm. The silver cubes with edge length  show the best performance. The results can help the design of solar energy materials, in which metallic nanoparticles may play an important role.
A. Cherala and Sreenivasan, S. V., “Molecular dynamics modeling framework for overcoming nanoshape retention limits of imprint lithography,” Microsystems & Nanoengineering, vol. 4, no. 3, 2018. Publisher's VersionAbstract
Complex nanoshaped structures (nanoshape structures here are defined as shapes enabled by sharp corners with radius of curvature <5 nm) have been shown to enable emerging nanoscale applications in energy, electronics, optics, and medicine. This nanoshaped fabrication at high throughput is well beyond the capabilities of advanced optical lithography. While the highest-resolution e-beam processes (Gaussian beam tools with non-chemically amplified resists) can achieve <5 nm resolution, this is only available at very low throughputs. Large-area e-beam processes, needed for photomasks and imprint templates, are limited to similar to 18 nm half-pitch lines and spaces and similar to 20 nm half-pitch hole patterns. Using nanoimprint lithography, we have previously demonstrated the ability to fabricate precise diamond-like nanoshapes with similar to 3 nm radius corners over large areas. An exemplary shaped silicon nanowire ultracapacitor device was fabricated with these nanoshaped structures, wherein the half-pitch was 100 nm. The device significantly exceeded standard nanowire capacitor performance (by 90%) due to relative increase in surface area per unit projected area, enabled by the nanoshape. Going beyond the previous work, in this paper we explore the scaling of these nanoshaped structures to 10 nm half-pitch and below. At these scales a new "shape retention" resolution limit is observed due to polymer relaxation in imprint resists, which cannot be predicted with a linear elastic continuum model. An all-atom molecular dynamics model of the nanoshape structure was developed here to study this shape retention phenomenon and accurately predict the polymer relaxation. The atomistic framework is an essential modeling and design tool to extend the capability of imprint lithography to sub-10 nm nanoshapes. This framework has been used here to propose process refinements that maximize shape retention, and design template assist features (design for nanoshape retention) to achieve targeted nanoshapes.
J. Xing, Chen, X., Zhou, Y., Culbertson, J. C., Freitas, J. A., Glaser, E. R., Zhou, J., Shi, L., and Ni, N., “Multimillimeter-sized cubic boron arsenide grown by chemical vapor transport via a tellurium tetraiodide transport agent,” Applied Physics Letters, vol. 112, pp. 261901, 2018. Publisher's Version
C. E. Tinney and Sirohi, J., “Multirotor Drone Noise at Static Thrust,” AIAA Journal, vol. 56, no. 7, pp. 2816-2826, 2018.Abstract
A first principles understanding of the sound field produced by multirotor drones in hover is presented. Propeller diameters ranging from 8 to 12 in. are examined and with configurations comprising an isolated rotor, quadcopter, and hexacopter configuration. The drone pitch, defined as the ratio of drone diameter to rotor diameter, is the same for all multirotor configurations and is valued at 2.25. A six-degree-of-freedom load cell is used to assess the aerodynamic performance of each configuration, whereas an azimuthal array of 1∕2 in. microphones, placed between two and three hub-center diameters from the drone center, is used to assess the acoustic near field. The analysis is performed using standard statistical metrics such as sound pressure level and overall sound pressure level and is presented to demonstrate the relationship between the number of rotors, the drone rotor size, and its aerodynamic performance (thrust) relative to the near-field acoustics.
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Y. Wang, Zhu, H., Yang, H., Argall, A. D., Luan, L., Xie, C., and Guo, L., “Nano functional neural interfaces,” Nano Research, pp. 1-42, 2018. Publisher's VersionAbstract
Engineered functional neural interfaces (fNIs) serve as essential abiotic–biotic transducers between an engineered system and the nervous system. They convert external physical stimuli to cellular signals in stimulation mode or read out biological processes in recording mode. Information can be exchanged using electricity, light, magnetic fields, mechanical forces, heat, or chemical signals. fNIs have found applications for studying processes in neural circuits from cell cultures to organs to whole organisms. fNI-facilitated signal transduction schemes, coupled with easily manipulable and observable external physical signals, have attracted considerable attention in recent years. This enticing field is rapidly evolving toward miniaturization and biomimicry to achieve long-term interface stability with great signal transduction efficiency. Not only has a new generation of neuroelectrodes been invented, but the use of advanced fNIs that explore other physical modalities of neuromodulation and recording has begun to increase. This review covers these exciting developments and applications of fNIs that rely on nanoelectrodes, nanotransducers, or bionanotransducers to establish an interface with the nervous system. These nano fNIs are promising in offering a high spatial resolution, high target specificity, and high communication bandwidth by allowing for a high density and count of signal channels with minimum material volume and area to dramatically improve the chronic integration of the fNI to the target neural tissue. Such demanding advances in nano fNIs will greatly facilitate new opportunities not only for studying basic neuroscience but also for diagnosing and treating various neurological diseases.
L. Luan, Sullender, C. T., Li, X., Zhao, Z., Zhu, H., Wei, X., Xie, C., and Dunn, A. K., “Nanoelectronics enabled chronic multimodal neural platform in a mouse ischemic model,” Journal of neuroscience methods, vol. 295, pp. 68 - 76, 2018. Publisher's VersionAbstract
Background Despite significant advancements of optical imaging techniques for mapping hemodynamics in small animal models, it remains challenging to combine imaging with spatially resolved electrical recording of individual neurons especially for longitudinal studies. This is largely due to the strong invasiveness to the living brain from the penetrating electrodes and their limited compatibility with longitudinal imaging.
X. Wei, Luan, L., Zhao, Z., Li, X., Zhu, H., Potnis, O., and Xie, C., “Nanofabricated Ultraflexible Electrode Arrays for High-Density Intracortical Recording,” Advanced Science, pp. 1700625–n/a, 2018. Publisher's VersionAbstract
Understanding brain functions at the circuit level requires time-resolved simultaneous measurement of a large number of densely distributed neurons, which remains a great challenge for current neural technologies. In particular, penetrating neural electrodes allow for recording from individual neurons at high temporal resolution, but often have larger dimensions than the biological matrix, which induces significant damage to brain tissues and therefore precludes the high implant density that is necessary for mapping large neuronal populations with full coverage. Here, it is demonstrated that nanofabricated ultraflexible electrode arrays with cross-sectional areas as small as sub-10 µm2 can overcome this physical limitation. In a mouse model, it is shown that these electrodes record action potentials with high signal-to-noise ratio; their dense arrays allow spatial oversampling; and their multiprobe implantation allows for interprobe spacing at 60 µm without eliciting chronic neuronal degeneration. These results present the possibility of minimizing tissue displacement by implanted ultraflexible electrodes for scalable, high-density electrophysiological recording that is capable of complete neuronal circuitry mapping over chronic time scales.
X. Chen and Espinoza, N. D., “Ostwald ripening changes the pore habit and spatial variability of clathrate hydrate,” Fuel, vol. 214, pp. 614–622, 2018. Publisher's Version
X. Chen, Verma, R., Espinoza, N. D., and Prodanović, M., “Pore-Scale Determination of Gas Relative Permeability in Hydrate-Bearing Sediments Using X-Ray Computed Micro-Tomography and Lattice Boltzmann Method,” Water Resources Research, vol. 54, pp. 600–608, 2018. Publisher's Version
H. Jung, Singh, G., Espinoza, N. D., and Wheeler, M. F., “Quantification of a maximum injection volume of CO2 to avert geomechanical perturbations using a compositional fluid flow reservoir simulator,” Advances in Water Resources, vol. 112, pp. 160–169, 2018. Publisher's Version
Z. Sun, Espinoza, N. D., and Balhoff, M. T., “Reservoir rock chemo-mechanical alteration quantified by triaxial tests and implications to fracture reactivation,” International Journal of Rock Mechanics and Mining Sciences, vol. 106, pp. 250–258, 2018. Publisher's Version
E. Bakolas, “Distributed Partitioning Algorithms for Locational Optimization of Multi-Agent Networks in SE(2),” IEEE Transactions on Automatic Control, vol. 63, no. 1, pp. 101-116, 2018. Publisher's VersionPDF icon ieee_tac17_eb.pdf
E. Bakolas, “Constrained Minimum Variance Control for Discrete-Time Stochastic Linear Systems,” Systems & Control Letters, vol. 113, no. 3, pp. 109-116, 2018. Publisher's VersionPDF icon mvc_scl_fvrev_8.pdf
E. Bakolas, “Finite-Horizon Covariance Control for Discrete-Time Stochastic Linear Systems Subject to Input Constraints,” Automatica, vol. 91, no. 5, pp. 61-68, 2018. Publisher's VersionPDF icon bakauto2018_fv2.pdf
X. Chen and Espinoza, N. D., “Surface area controls gas hydrate dissociation kinetics in porous media,” Fuel, vol. 234, pp. 358–363, 2018. Publisher's Version
L. Lagardère, Jolly, L. - H., Lipparini, F., Aviat, F., Stamm, B., Jing, Z. F., Harger, M., Torabifard, H., Cisneros, A. G., Schnieders, M. J., and others,Tinker-HP: a massively parallel molecular dynamics package for multiscale simulations of large complex systems with advanced point dipole polarizable force fields,” Chemical Science, 2018.
U. Herwig, Lutz, J., Scherpiet, S., Scheerer, H., Kohlberg, J., Opialla, S., Preuss, A., Steiger, V. R., Sulzer, J., and Weidt, S., “Training emotion regulation through real-time fMRI neurofeedback of amygdala activity,” NeuroImage, 2018.
F. Tian, Song, B., Chen, X., Ravichandran, N. K., Lv, Y., Chen, K., Sullivan, S., Kim, J., Zhou, Y., Liu, T. - H., Goni, M., Ding, Z., Sun, J., Gamage, G. A. G. U., Sun, H., Ziyaee, H., Huyan, S., Deng, L., Zhou, J., Schmidt, A. J., Chen, S., Chu, C. - W., Huang, P. Y., Broido, D., Shi, L., Chen, G., and Ren, Z., “Unusual high thermal conductivity in boron arsenide bulk crystals,” Science, vol. 361, pp. 582–585, 2018. Publisher's VersionAbstract
Conventional theory predicts that ultrahigh lattice thermal conductivity can only occur in crystals composed of strongly bonded light elements, and that it is limited by anharmonic three-phonon processes. We report experimental evidence that departs from these long-held criteria. We measured a local room-temperature thermal conductivity exceeding 1000 watts per meter-kelvin and an average bulk value reaching 900 watts per meter-kelvin in bulk boron arsenide (BAs) crystals, where boron and arsenic are light and heavy elements, respectively. The high values are consistent with a proposal for phonon-band engineering and can only be explained by higher-order phonon processes. These findings yield insight into the physics of heat conduction in solids and show BAs to be the only known semiconductor with ultrahigh thermal conductivity.

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