Winter 2017: Colloquium Series

Talks are usually scheduled on Thursdays during common hour (12:50 – 1:50 PM) in Room N304 of the Science and Engineering Building, unless otherwise indicated. Lunch is served starting at 12:20PM. All are welcome!


Thursday January 05, 2017

Summer research opportunities

we will provide information to students about research opportunities at Union and outside Union.


 


Thursday February 9, 2017 — Moved to April 27 due to Weather

A Career in Big Data: Physics and the Software Industry

Jason Slaunwhite ’04

During this talk I will share a few short stories from my career in Big Data. After graduating from Union in 2004, I did research in High Energy Particle Physics and went on work at the CERN laboratory in Switzerland. I have continued to work with Big Data as a software developer for an analytic database company. I hope that by sharing a few of my experiences with current physics majors, I can provide some perspective on the different opportunities that they may consider pursuing after graduation.


Thursday February 16, 2017

Synchronization in Networks of Biomimetic Artificial Neurons

Harold M Hastings
Division of Science, Bard College at Simon’s Rock, and Department of Physics and Astronomy, Hofstra University

There has been a long tradition of the study of model neurons, beginning with pioneering work of Hodgkin and Huxley. Subsequently FitzHugh, Nagumo and colleagues developed a simplified two variable conductance model for neuronal dynamics, consisting membrane potential whose (fast) dynamics reflect a non-linear sodium current and a (slow) gate variable (potassium current). FitzHugh-Nagumo neurons can display either excitable (sufficiently large stimuli generate action potentials before returning to steady state) or oscillatory dynamics, depending upon parameter values. We explore the dynamics networks of FitzHugh-Nagumo neurons and analogues, especially Keener’s modification of the original Nagumo circuit and the Belousov-Zhabotinsky chemical reaction, the prototype chemical oscillatory system. A wide variety of complex synchronization and emergent behavior is seen. There are potential applications to computer science, biology, and biomedicine.

Selected References:

  • Alford, S.T., Alpert, M.H., A synaptic mechanism for network synchrony. Frontiers Cellular Neuroscience 8, doi.org/10.3389/fncel.2014.00290 (2014)
  • Arumugam, E.M.E., Spano, M.L., A chimeric path to neuronal synchronization. Chaos 25, 013107 (2015)
  • Belair, J., et al., Dynamical disease: identification, temporal aspects and treatment strategies of human illness. Chaos 5, 1 (1995)
  • Beuter, A., Bélair, J., Labrie, C., Feedback and delays in neurological diseases: a modeling study using dynamical systems. Bull. Math. Biol. 55, 525 (1993).
  • FitzHugh, R., Impulses and physiological states in theoretical models of nerve membrane. Biophys. J. 1, 445 (1961).
  • Hastings, H.M., Field, R.J., Sobel, S.G., Microscopic fluctuations and pattern formation in a supercritical oscillatory chemical system. The Journal of chemical physics, 119, 3291 (2003).
  • Hastings, H.M., et al., Bromide control, bifurcation and activation in the Belousov− Zhabotinsky Reaction. J. Phys. Chem. A 112, 4715-4718 (2008).
  • Hastings, H.M. et al., Oregonator Scaling Motivated by Showalter-Noyes Limit. J. Phys. Chem. A 120, 8006 (2016).
  • Hastings, H.M. et al., Dynamics of Biomimetic Electronic Artificial Neural Networks, Proceedings of the 4th International Conference on Applications in Nonlinear Dynamics (ICAND 2016), Ed: V. In, P. Longhini, A. Palacios, Springer (in press, to appear in 2017).
  • Keener, J.P., Analog circuitry for the van der Pol and FitzHugh-Nagumo equations. IEEE Trans. Systems Man Cybernetics 5, 1010 (1983).
  • Nagumo, J., Arimoto, S., Yoshizawa, S., An active pulse transmission line simulating nerve axon. Proc. IRE 50, 2061 (1962).
  • Tompkins, N., et al., Creation and perturbation of planar networks of chemical oscillators. Chaos 25, 064611 (2015).
  • Tuma, T., et al., Stochastic phase-change neurons. Nature Nanotech. 11, 693 2016).

Thursday February 23, 2017

Founders Day


Thursday March 2, 2017

Craig Luckfield
PASCO scientific


Thursday March 9, 2017

Synthesis of Device-Quality Graphene Films

Carl A. Ventrice, Jr.
Colleges of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, NY

Graphene is a single atomic layer of carbon that is crystallized in the honeycomb configuration. It has many unique properties that are of particular interest for the development of nanoscale electronic devices and sensors. In particular, it is a semi-metal whose charge carrier density can be continuously tuned from n-type to p-type by applying an external electric field and has a linear energy-momentum dispersion in the vicinity of the Dirac point, which results in carrier mobilities that are higher than almost all semiconductors. It also has a very large in-plane thermal conductivity and exceptional mechanical properties. However, one of the primary issues that must be addressed before nanoscale electronic devices and sensors can be routinely fabricated is the development of methods for growing large-scale, device-quality, graphene films with uniform thickness at a relatively low cost. An overview will be given of the techniques currently used for graphene synthesis and the research being done in my laboratory to synthesize single crystal films of graphene.


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