Bulletin of the American Physical Society
Annual Meeting of the APS Four Corners Section
Volume 62, Number 17
Friday–Saturday, October 20–21, 2017; Fort Collins, CO
Session K4: Biophysics II |
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Chair: Martin Gelfand, Colorado State University Room: Lory Student Center 308 |
Saturday, October 21, 2017 9:25AM - 9:49AM |
K4.00001: High-Speed Low-Energy Superconducting/Magnetic Josephson Junction Neurons and Neural Nets Invited Speaker: Stephen Russek Superconducting single flux quantum (SFQ) circuits form a natural neuromorphic technology with SFQ pulses and superconducting transmission lines simulating action potentials and axons, respectively. Here we present a new component, magnetic Josephson junctions, that have a tunablility and re-configurability that was lacking from previous SFQ neuromorphic circuits. Neuromorphic magnetic Josephson junctions differ from devices designed for digital memory applications, such as spin-valve Josephson junctions, in that they use magnetic nanoclusters as the tunable magnetic element. The nanoscale magnetic structure acts as a tunable synaptic constituent that modifies the junction critical current. High quality Josephson junctions and junction arrays have been fabricated using Mn-doped Si barriers. The magnetic structure can be tuned by rapid thermal annealing and shows superparamagnetic behavior in the zero-field-cooled field-cooled magnetization measurements. The junction critical currents can be modified by 200 ps current pulses and with training energies down to 3 aJ. These circuits can operate near the thermal limit where stochastic firing of the neurons is an essential component of the technology. Magnetic Josephson junction device models have been developed in Verilog A and used to model simple neural structures using SPICE with thermal noise terms. A simple multilayer perceptron neural net has been designed and modelled to demonstrate image processing at GHz rates. This technology can be extended to create complex neural systems with greater than 10$^{\mathrm{18}}$~neural firings per second with less than 1 W dissipation. For reference, the human brain has 10$^{\mathrm{17}}$ neural firings per second and dissipates 100 W. [Preview Abstract] |
(Author Not Attending)
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K4.00002: Electrical Conductivity of Monolayer Films of Ferritin Molecules Alessandro Perego, John Colton, Robert Davis Ferritin is a 12 nm diameter spherical protein with an 8 nm hollow interior, which naturally contains iron oxide nanocrystals. The natural core of ferritin can be removed and other metal oxide nanoparticles can be synthesized inside the empty ferritin cage. The choice of metal used for the growth of the nanoparticles determines different properties for light harvesting and/or for oxidative charge. Knowledge of the electrical conductivity of the protein shell is critical to the performance of ferritin-based nano applications like quantum dots solar cells and nanobatteries. Here we use a 500 $\mu $m diameter gold ball as a contact probe to measure the conductivity of a sub monolayer of ferritin molecules. The contact force between the spherical probe and the surface is gradually increased until a stable I-V curve is obtained. At this current research stage, we show conductivity measurements for apoferritin and for different holoferritin molecules loaded with different amount of iron ions. Results show an increase in conductivity as the iron load increases inside the protein, indicating that for holoferritin most electron-transfer goes through the ferrihydrite core. [Preview Abstract] |
Saturday, October 21, 2017 10:01AM - 10:13AM |
K4.00003: Higher-order correlations uncover hidden information in the fluorescence fluctuation analysis of fast molecular kinetics Farshad Abdollah-Nia, Martin Gelfand, Alan Van Orden The statistical analysis of photons collected from fluorescent molecules as they diffuse and react in solution can provide information about concentrations and reaction rates. Two common techniques, based on correlation (FCS) and histogram (PCH) analysis of photon statistics, are unable to provide a complete picture of fast molecular reactions. Higher-order correlations (HOFCS) can, in principle, overcome such limitations. Historically, attempts to use HOFCS have been hindered by modeling complications in theory, and by shot noise and detector artifacts in experiment. Melnykov and Hall (2009) solved the modeling problem through a cumulant-based formulation of HOFCS [1]. More recently, we have introduced techniques to evaluate artifact-free higher-order correlation functions with improved time resolution, overcoming the experimental limitations [2]. This has enabled us to apply HOFCS to fast reversible reactions for the first time [3].\\ \\$[1]$ A. V. Melnykov and K. B. Hall, The Journal of Physical Chemistry B 113, 15629 (2009)\newline [2] F. Abdollah-Nia, M. P. Gelfand, and A. Van Orden, The Journal of Physical Chemistry B 121, 2373 (2017)\newline [3] F. Abdollah-Nia, M. P. Gelfand, and A. Van Orden, The Journal of Physical Chemistry B 121, 2388 (2017) [Preview Abstract] |
Saturday, October 21, 2017 10:13AM - 10:25AM |
K4.00004: Investigating Cellular Structure via Optical Scattering Profiles from a Near-Infrared Laser Diode Vern Hart, James Graham, Ryan Bevan, Duncan Reeves, Ellie Evans, Chris Berneau, Daniel Blumel, Diana Turcios In the earliest stages of certain cancers, cell nuclei tend to enlarge and elongate. This process occurs at the sub-cellular level, on scales too small to be visible in a CT or MR image, and months before a tumor is visible. The nucleus accounts for a significant amount of the optical scattering which occurs in a cell and recent efforts in diffuse optical tomography have investigated the feasibility of early detection for these sub-cellular changes, ``so-called'' micro-cancer. However, the ability to distinguish these cells requires sufficient understanding of the involved scattering mechanisms. In this study, we investigated optical scattering patterns for five different cancer cell lines, which were irradiated in vitro by diode lasers at wavelengths of 532, 635, and 850 nm. The resulting patterns were collected with a laser beam profiler and were then analyzed in MATLAB using a 2D Fourier transform. Significant differences were observed in the appearance and spectral distributions for the various cell lines. Spherical WEHI-3 cells were used as a control and compared with MIE scattering simulations for spherical particles. Accurate quantification of these patterns could lead to the detection of cancerous cells at low concentrations in otherwise healthy tissue. [Preview Abstract] |
Saturday, October 21, 2017 10:25AM - 10:37AM |
K4.00005: On the Analysis of Time-Dependent Biochemical Systems Via the Utilization of Ising Mean Field Parameters Curtis Peterson, Tommy Byrd, Robert Vogel, Amir Erez, Andrew Mugler Cell behaviors are governed by non-equilibrium systems of interacting molecules. Often, these systems exhibit qualitative transitions in their parameter space, e.g. from one to two stable states. These transitions are reminiscent of critical transitions in equilibrium systems from many-body physics. A particular class of non-equilibrium biochemical systems with feedback has been shown to exhibit the critical scaling properties of the Ising universality class in the mean-field limit, and this prediction is supported by measurements of doubly phosphorylated ppERK in T cells. We extend upon the analysis by studying time-dependent data of ppERK abundance as the system transitions from two stable states to one. Our analysis reveals that T cells experience critical slowing down in their response to drugs. Our approach is broadly applicable to the investigation of critical dynamics in biological systems. [Preview Abstract] |
Saturday, October 21, 2017 10:37AM - 10:49AM |
K4.00006: Biosensing with Spatial Resolution Using Graphene Lauren Zundel, Alejandro Manjavacas Surface plasmons, the collective oscillation of conduction electrons, are a powerful sensing tool due to the extraordinary light confinement they provide. Graphene nanostructures, which have been shown to support strong plasmon resonances in the infrared part of the spectrum, have a strong potential to be used as platforms to develop versatile biosensors, due to the unique ability to tune their resonances by means of electrical doping. Here, we take advantage of these properties to propose an optical sensor with spatial resolution below the diffraction limit. To this end, we design a device consisting of an array of identical nanodisks divided into a number of subarrays, or pixels, each with a uniform doping level. Therefore, by individually adjusting the doping level of each of these pixels, it is possible to bring them sequentially into resonance with the spectrum of the analyte, thus enabling the detection of both its presence and location. The results of this investigation help to set the foundations to develop novel label-free infrared sensors, which can open doors for new applications to sense the chemical composition of complex biological structures with temporal and spatial resolution. [Preview Abstract] |
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