Refreshments: 3:30, talk 4:00 - 5:00 p.m.

2019

Nov
20
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Nov
13
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Nov
6
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Oct
30
2019
Title and abstract to be announced.
Sage 3303 4:00 pm

Oct
23
2019
Dr. Donnell Walton, Corning Incorporated
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Oct
16
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Oct
9
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Sep
25
2019
Light-matter interactions of quantum materials and their novel sensing applications

Emerging quantum materials, such as novel two-dimensional (2D) materials and topologically nontrivial materials, have gained increasing attention due to their unique electronic and photonic properties. The realization of the optoelectronic applications of these materials still faces several challenges. For example, it is critical to gain clear understandings of (1) the fundamental light-matter interactions, which govern many of the key material properties, and (2) the coupling with other nanostructures, which is a required structure for devices and systems. This talk introduces new discoveries and pioneer work using optical spectroscopic techniques on these critical challenges, and novel applications of 2D materials in sensing. The first part of this talk presents the essential material properties investigated using spectroscopy, including interlayer coupling of Moirè patterns of 2D materials, and anisotropic light-matter interactions of 2D materials and Weyl semimetals. The second part of this talk focuses on the interaction of 2D materials with other nanostructures and the related applications. The interactions of 2D materials and selected organic molecules revealed novel enhancement effect of Raman signals for molecules on 2D surface, which offers a new paradigm in biochemical sensing. The works presented in this talk are significant in fundamental nanoscience, and offer important guidelines for practical applications in optoelectronics, sensing, and quantum technologies. The methodologies used here also provide a framework for the future study of many new quantum materials.

Low Center for Industrial Innovation (CII) 3051 4:00 pm

Apr
18
2019
“ENGINEERING MATTER IN A PHOTON BOX”

Interaction of light with matter lies at the heart of a plethora of fundamental phenomena and technological applications. The strength of this interaction can be controlled by engineering the electromagnetic environment surrounding the matter. In this talk I will discuss the ongoing work in my group to explore emergent material properties that arise through the coherent interaction between material excitations and artificially engineered electromagnetic media. This work is motivated by the quest to understand the ultimate limits of controlling optical transitions, carrier transport, energy harvesting, nonlinear optical response and quantum effects. Specifically, we will discuss the regimes of weak and strong light-matter interactions and their implication on the material response. I will begin with a discussion of strong light-matter coupling realized by embedding two-dimensional materials in a photon box (a.k.a optical cavity) [Nature Photon. 9, 30 (2015)] and approaches to control them optically [Nature Photon. 11, 491 (2017)] and electrically. Following this, I will present results on modifying properties such as energy transfer and luminescence of organic molecular materials through strong light-matter coupling [PNAS 116, 5214 (2019)]. In the second part of the talk, I will discuss the regime of weak light-matter coupling to enhance luminescence from low-dimensional semiconductors by designing artifical optical media based on ideas from topology [Science 336, 205 (2012); PNAS 114, 5125 (2017)].  Finally, I will briefly talk about defect engineering in van der Waals materials as a means to realize deterministic quantum emitters [Optica 5, 1128 (2018)] and approaches to couple their emission to high finesse optical cavities. These four example topics all have the underlying theme of controlling light-matter interaction at the nanoscale as a means for engineering matter to realize emergent optoelectronic properties.

Darrin Communication Center (DCC) 324 4:00 pm

Apr
10
2019
“Plasmon-driven photoelectrochemistry: hot electrons, hot holes, and hot metal”

Plasmonic nanostructures have long been appreciated for their ability to harvest photon energy and transform it into other forms, including chemical energy (through the production of hot charge carriers) and thermal energy.  Hot carrier production has enabled a variety of photoelectrochemical reactions at plasmonic nanoparticle electrodes, driven by either hot electrons or hot holes.  However, at the same time, thermal energy increases mass transport of reactants to the surface and can shift the standard potential of electrochemical reactions, further impacting the rate of photoelectrochemical reactions.  Decoupling the relative contributions of plasmon-mediated local heating from hot carrier effects on these reactions has long been an experimental challenge, because we do not have the ability to control each plasmon decay pathway independently.  Moreover, plasmon-generated hot carriers quickly lose their energy due to collisions, generating a distribution of hot carrier energies with varying oxidizing or reducing power.  This talk will describe our work to isolate local heating effects from hot carrier effects as well as provide quantitative values for hot carrier energies using scanning electrochemical microscopy (SECM) on gold nanoparticles at semiconductor interfaces.  We generate real temperature values as well as effective hot carrier temperatures, allowing us to understand how plasmon excitation promotes reactions on plasmon substrates.

Low Center for Industrial Innovation (CII) 3051 4:00 pm

Apr
3
2019
“The light years: Nanophotonic methods to visualize dynamic chemical and cellular processes with near-atomic-scale resolution”

Pearl Jam’s hit, “The Light Years,” declares “We were but stones, light made us stars.” Nanophotonic materials and methods promise to elucidate many unknown dynamic processes at the molecular and nanoscale, provided they can ‘shine’ in reactive environments. Here we present our research developing nanophotonic techniques for dynamic, in-situ imaging of photocatalysis, single cell processes, and in-vivo force transduction at the nanoscale. First, we present methods to visualize plasmon-induced chemical transformations with sub-2nm spatial resolution. Our goal is to help unravel the means by which plasmons mediate and control the local chemistry, and ultimately, use that knowledge to optimize photocatalyst performance. As a model reaction, we study the gas-phase photocatalytic dehydrogenation of Au-Pd systems, in which the Au acts as a plasmonic light absorber and Pd serves as the catalyst. Under controlled hydrogen pressures, temperatures, and illumination conditions, we study the study the kinetics of the desorption reaction triggered by the optical excitation of plasmons. We find that plasmons increase the overall rate more than ten-fold and open a new reaction pathway that is not observed without illumination. These results help elucidate the role of plasmons in light-driven phase transformations, en-route to design of site-selective and product-specific photocatalysts. Second, we combine Raman spectroscopy and deep learning to accurately classify bacteria by both species and antibiotic resistance in a single step. We design a convolutional neural network (CNN) for spectral data and train it to identify 30 of the most common bacterial strains from single-cell Raman spectra, achieving antibiotic treatment identification accuracies exceeding 99% and species identification accuracies similar to leading mass spectrometry identification techniques. Our combined Raman-CNN system represents a proof-of-concept for rapid, culture-free identification of bacteria and their antibiotic resistance. Finally, we introduce a new class of in vivo optical probes to monitor biological forces with high spatial and temporal resolution. Our design is based on upconverting nanoparticles that, when excited in the near-infrared, emit light of a different color and intensity in response to microNewton forces. The nanoparticles are sub-30nm in size, do not bleach or photoblink, and can enable deep tissue imaging with minimal tissue autofluorescence. We present the design, synthesis, and characterization of these nanoparticles both in vitro and in vivo, focusing on the forces generated by the roundworm C. elegans as it feeds and digests its bacterial food. Chronic cytotoxicity assays are used to confirm biocompatibility. Our force measurements are coupled with electrical measurements of muscle contractions in both wild-type and mutant animals, providing insight into the interplay between mechanical, electrical, and chemical signaling in vivo.

 

Biography:

Jennifer Dionne is an associate professor of Materials Science and Engineering at Stanford, and an affiliate faculty of the Wu Tsai Neurosciences Institute, TomKat Center for Sustainable Energy, Institute for Immunity, Transplantation, and Infection, and Bio-X. She serves as director of the Department of Energy funded Photonics at Thermodynamic Limits Energy Frontier Research Center and faculty co-director of Stanford’s Photonics Research Center. Jen received her B.S. degrees in Physics and Systems Science and Mathematics from Washington University in St. Louis in 2003 and her Ph. D. in Applied Physics at the California Institute of Technology in 2009, advised by Harry Atwater. Prior to joining Stanford, she served as a postdoctoral researcher in Chemistry at Berkeley, advised by Paul Alivisatos.  Jen’s research develops new materials and microscopies to observe chemical and biological processes as they unfold with nanometer scale resolution. She then uses these observations to help improve energy-relevant processes (such as photocatalysis and energy storage) and medical diagnostics. Her work has been recognized with a Moore Inventor Fellowship, the Materials Research Society Young Investigator Award, Adolph Lomb Medal, Sloan Foundation Fellowship, and the Presidential Early Career Award for Scientists and Engineers, and was featured on Oprah’s list of “50 Things that will make you say ‘Wow’!”. When not in the lab, Jen enjoys teaching both undergraduate and graduate classes (including “Waves and Diffraction,” “Materials Chemistry”, “Optoelectronics”, and “Science of the Impossible”), exploring the intersection of art and science, cycling the latest century, and reliving her childhood with her two young sons.

The Herta Leng Memorial Lecture
Darrin Communication Center (DCC) 324 4:00 pm

Mar
13
2019
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Feb
13
2019
A Theoretical Study of Schwarzites and Linear Carbon

Pure carbon structures contain a wealth of information and potential properties, we focus on two, long linear carbon chains and Schwarzites. Long linear carbon chains, a one dimensional sp hybridized carbon chain,
have been observed to be encapsulated by a carbon nanotube. Together this system produces a resonant Raman signal from 1770-1860 cm-1, known as the C-mode. The origin of this signal is still under scrutiny. We explore the nature of Raman activity in long linear carbon chains through the use of first principles density functional theory and identify the effect of exact exchange in calculations using hybrid functionals. With exact exchange the most intense Raman active mode, the longitudinal optical mode, converges, with respect to length, to 1831
cm-1, within the range of reported measurements of the C-mode. Also the electronic gap converges, with respect to length, to 1.8 eV, near the known resonance energy.

Schwarzites are sp2, or hexagonal, triply periodic minimal carbon surfaces with negative Gaussian curvature from the introduction of 7-, 8-, 9-, and 10-membered rings. Recently theoretical impregnation of zeolites, simulating the templating processes, has produced Schwarzites.
We present first principles and classical dynamics calculations of electronic and vibronic density of states calculations to establish a connection between the theoretical structures proposed to the experimentally obtained materials. We identify the theoretical structures as energetically and dynamically stable, graphitic in nature, and semimetallic.

Ross Siegel, RPI
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Jan
30
2019
Efficiently Embedding QUBO Problems on Adiabatic Quantum Computers; A Classical-Quantum Hybrid Approach for Unsupervised Probabilistic Machine Learning

Abstract 1: Adiabatic quantum computers like the D-Wave 2000Q can approximately solve the QUBO problem, which is an NP-Hard problem, and have been shown to outperform classical computers on several instances. Solving the QUBO problem literally means solving virtually any NP-Hard problem like the Traveling Salesman Problem (TSP), Airline Scheduling Problem, Protein Folding Problem, Genotype Imputation Problem etc., thereby enabling significant scientific progress, and potentially saving millions / billions of dollars in logistics, airlines, healthcare and many other industries. However, before QUBO problems are solved on quantum computers, they must be embedded (or compiled) onto the hardware of quantum computers, which in itself is a very hard problem. In this work, we propose an efficient embedding algorithm, that lets us embed QUBO problems fast, uses less qubits and gets the objective function value close to the global minimum value.  We then compare the performance of our embedding algorithm to that of D-Wave's embedding algorithm, which is the current state of the art, and show that our embedding algorithm convincingly outperforms D-Wave's embedding algorithm. Our embedding approach works with perfect Chimera graphs, i.e. Chimera graphs with no missing qubits.

Abstract 2: For training unsupervised probabilistic machine learning models, matrix computation and sample generation are the two key steps. While GPUs excel at matrix computation, they use pseudo-random numbers to generate samples. Contrarily, Adiabatic Quantum Processors (AQP) use quantum mechanical systems to generate samples accurately and quickly, but are not suited for matrix computation. We present a Classical-Quantum Hybrid Approach for training unsupervised probabilistic machine learning models, leveraging GPUs for matrix computations and the D-Wave quantum sampling library for sample generation. We compare this approach to classical and quantum approaches across four performance metrics. Our results indicate that while the hybrid approach--which uses one AQP and one GPU--outperforms quantum and one of the classical approaches, it performs comparably to the GPU approach, and is outperformed by the CPU approach, which uses 56 high-end CPUs. Lastly, we compare sampling on AQP versus sampling library and show that AQP performs better.

Prasanna Date, RPI
Low Center for Industrial Innovation (CII) 3051 4:00 pm

2018

Nov
14
2018
Neutrino Physics and the PROSPECT Experiment

Neutrinos, the most ghostly of Standard Model particles, were first detected by Clyde Cowan and Frederick Reines in 1956. Although these particles are included in the Standard Model, their properties such as mass and mixing parameters are not predicted and must be measured. Ever since their discovery, physicists have been trying to piece together a comprehensive understanding of the neutrino and over the past 6 decades a nearly complete picture has emerged. However, there are still some undetermined parameters as well as phenomena that have resisted explanation. One of these unexplained phenomena that has arisen rather recently termed the "reactor antineutrino anomaly" is the deficit in the measured flux of antineutrinos from nuclear reactors relative to the expected flux from calculation. Furthermore, the energy spectrum of reactor antineutrinos from recent experiments deviates from the calculated shape in the region of 5-7 MeV antineutrino energy. PROSPECT, the Precision Reactor Oscillation and Spectrum experiment, currently taking data at Oak Ridge National Lab, aims to shed some light on these anomalies by measuring the flux a few meters from the core of a highly enriched uranium (HEU) research reactor. In so doing, many obstacles had to be overcome, not the least of which was designing a detector that could isolate antineutrino events from huge backgrounds inherent in the environment at the surface of the Earth and next to a reactor.  In this talk, I will give a brief history of neutrinos and how their properties were determined highlighting some key experiments. Special emphasis will be given to the PROSPECT experiment with recent data and analysis shown.

Low Center for Industrial Innovation (CII) 3051 4:00 pm

Oct
24
2018
Yung Joon Jung, Northeastern University
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Oct
17
2018
The Robert Resnick Lecture
Stephon Alexander, Brown University
Sage 3303 4:00 pm

Oct
3
2018
Integrated Slow-Light Silicon Photonic Devices and Systems for RF Photonic and Optical Computing Applications

Significant research and development in the field of Si Photonics have been done in the past two decades leading to the worldwide establishment of Si Photonics foundry services. The technology advancement includes hybrid integration of III-V laser diodes on Si platform, micro-ring or disk resonators, integrated PN junction based Mach-Zehnder (MZ) light modulators, SiGe on Si photodetectors, SiN low-loss waveguides, integrated optical delay line, array waveguide gratings etc. In my group, the current focus of research is slow-light Bragg grating rib waveguides and slot waveguides on Si substrate. Slow-light waveguide has enhanced light-matter interaction so allowing significant size reduction in active photonic devices such as MZ light modulators. The MZ modulator is a basic building block for a large array of tunable optical interference units for the on-chip optical neuromorphic computing application in which the MZ interferometer serves as an arbitrary unitary matrix. The passive slow-light waveguide is also a key element for chip scale photonic system integration in many application areas. For example, the slow-light Bragg grating waveguide has been used to construct tunable optical delay lines for beamforming in phased array antennas. For on-chip optical reservoir computing, a dispersive Bragg grating is a critical element in obtaining nanoseconds of true-time delay for storage of memories.

Low Center for Industrial Innovation (CII) 3051 4:00 pm

Sep
19
2018
Yiping Zhao, University of Georgia
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Sep
12
2018
Michael Agiorgousis, RPI
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Apr
25
2018
Marc Miskin, Cornell University

Apr
11
2018
Steven G. Louie, University of California at Berkeley and Lawrence Berkeley National Lab

Mar
21
2018
J. Michael Kosterlitz, Brown University

Feb
28
2018
Guy Consolmagno, Vatican Observatory

Feb
21
2018

Feb
14
2018

Jan
31
2018

Jan
24
2018
Boleslaw Szymanski, Rensselaer Polytechnic Institute