Via WebEx scheduled to begin at 4:45 p.m.

 

2020

Nov
11
2020
Albert Davidov, NIST
Webex 4:45 pm

Oct
28
2020
WebEx: https://rensselaer.webex.com/rensselaer/j.php?MTID=mb7e43fdde395c6131476495268b5925b 4:45 pm

Oct
14
2020
WebEx: https://rensselaer.webex.com/rensselaer/j.php?MTID=m45a61a5e6ba6c827cfe7ba8b928894c6 4:45 pm

Oct
7
2020
WebEx: https://rensselaer.webex.com/rensselaer/j.php?MTID=m498c139acd90d695bcc8380e2d138451 4:45 pm

Sep
30
2020
WebEx link. https://rensselaer.webex.com/rensselaer/j.php?MTID=m986f2aeb3ea30714602d4e466ab78523
Dr. Stephanie Tomasulo, US Naval Research Laboratory
WebEx: https://rensselaer.webex.com/rensselaer/j.php?MTID=m986f2aeb3ea30714602d4e466ab78523 4:45 pm

Sep
9
2020
Professor Humberto Terrones, Rensselaer

Feb
26
2020
DEFECT ENGINEERING IN 2D MATERIALS

The rise of two-dimensional (2D) materials has opened up possibilities for exploring new physical phenomena that motivate the synthesis of more complex low dimensional systems. In this colloquium, we will discuss doping routes that allow the tunability of electronic properties in 2D semiconducting transition metal dichacogenides (TMDs). Zero dimensional (0D) defects such as vacancies and substitutional dopants within tungsten disulfide (WS2) monolayers, will be discussed. In particular, TMD substitutional doping with CH units can be achieved using a novel radio-frequency plasma assisted (RF-PA) approach. Electron microscopy studies confirmed the presence of CH units within the WS2 lattice of plasma treated islands, and DFT calculations confirm the stability of these CH species in sulfur mono-vacancies. Furthermore, field effect transistors fabricated using these CH-doped WS2 exhibit an ambipolar behavior, instead of the n-type transport showed by pristine WS2. The photoluminescence (PL) emission (at 77K) of defective TMD monolayers will also be presented. In particular, sulfur mono-vacancies are concentrated along the edges of triangular WS2 monocrystals. We observed the appearance of bound excitons located 300 meV below the neutral (A) exciton. DFT calculations reveal that sulfur monovacancies introduce midgap states exactly 300 meV below the edge of the conduction band. High–resolution scanning transmission electron microscopy (HR-STEM) images indicate that edges of the WS2 monolayers that exhibit bound excitons contain a very large concentration of sulfur mono-vacancies. Finally, the challenges and new directions in defect engineering of 2D materials will be introduced.

Dr. Ana Laura Elias, SUNY Binghamton
Low Center for Industrial Innovation (CII) 3051 4:00 pm

Feb
12
2020
Gwo-Ching Wang, Physics, Applied Physics and Astronomy, Rensselaer
Low Center for Industrial Innovation (CII) 3051 4:00 pm 4:00 pm

2019

Nov
20
2019
Metasurface enabled Spatio-temporal Shaping of Optical Fields

Over the last decade, flat optical elements composed of an array of deep-subwavelength dielectric or metallic nanostructures of nanoscale thicknesses – referred to as metasurfaces – have revolutionized the field of optics and nanophotonics. Because of their ability to impart an arbitrary phase, polarization or amplitude modulation to an optical wavefront as well as perform multiple optical transformations simultaneously on the incoming light, they promise to replace the traditional bulk optics in applications requiring compactness, integration and/or multiplexing.

In this talk, we discuss the ability of metasurfaces to arbitrarily shape both the temporal and spatial evolution of optical fields, ranging from the deep-ultraviolet to the terahertz frequency range. This requires independent control over the amplitude, phase and/or polarization, achieved here by designing individual metasurface elements to act as nanoscale half-wave plates. We will discuss the various nanofabrication strategies and material constraints governing for their design for operation at these various frequency ranges and outline the advantages of the metasurface approach to light shaping over the more traditional use of spatial light modulators to do the same.

Finally, we demonstrate the versatility of spatial shaping metasurfaces to be directly integrated on integrated photonic chips for their applications as an interface to quantum or biological systems. Through spatial multiplexing of metasurfaces integrated with grating out-couplers directly on a nanophotonic chip, we show the ability to create arbitrary optical fields in the far-field for applications in cold atom traps, biosensing or LIDAR.

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

Nov
6
2019
Two-dimensional materials, metamaterials, and machine learning

 This talk will address two-dimensional materials properties and the use of machine learning to predict and understand dynamical phenomena. The discovery of graphene and related two-dimensional materials enables the possibility of engineering metamaterials with desired electronic and optical properties. Plasmonic nanocrystals are optical metamaterials that consist of engineered structures at the sub-wavelength scale. They exhibit optical properties, such as negative-refractive-index and epsilon-near-zero (ENZ) behavior, that are not found under normal circumstances in nature. We will describe a systematic approach for constructing graphene-based tunable metamaterials that exhibit anisotropic ENZ behavior. Subsequently, we will focus on graphene and Dirac solids that constitute two-dimensional materials where the electronic flow is ultra-relativistic. When graphene is deposited on a substrate with roughness, a local random potential develops through an inhomogeneous charge impurity distribution. This disordered potential induces a chaotic pattern in the electronic flow in the form of current branches. We will describe the physics that governs this ultra-relativistic electronic branched flow and demonstrate analytically and numerically the laws of the onset of branching. Finally we will address Machine learning (ML) methods that are currently employed for understanding physical systems as well as for designing materials. We use ML techniques in graphene and produce results that show how ML can predict the electronic branching by learning from past temporary states of the flow. In addition to the data-driven forecasting, we show how unsupervised neural networks can solve differential equations. We focus on energy-conserving equations and propose an architecture that is time invariant and guarantees the energy conservation through an embedded Hamiltonian symplectic structure.

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

Oct
30
2019
The Herta Leng Memorial Lecture

In this talk I will describe how a radio astronomy search for more of the puzzling objects known as quasars led to the accidental discovery of some even more puzzling radio sources, or pulsars. I will briefly outline the properties of pulsars and recount some earlier instances where pulsars were nearly discovered.

 

Bio: Jocelyn Bell Burnell inadvertently discovered pulsars as a graduate student in radio astronomy in Cambridge, opening up a new branch of astrophysics - work recognised by the award of a Nobel Prize to her supervisor.

 

She has subsequently worked in many roles in many branches of astronomy, working part-time while raising a family. She is now a Visiting Academic in Oxford, and the Chancellor of the University of Dundee, Scotland.  She has been President of the UK’s Royal Astronomical Society, in 2008 became the first female President of the Institute of Physics for the UK and Ireland, and in 2014 the first female President of the Royal Society of Edinburgh. She was one of the small group of women scientists that set up the Athena SWAN scheme.

 

She has received many honours, including a $3M Breakthrough Prize in 2018.

 

The public appreciation and understanding of science have always been important to her, and she is much in demand as a speaker and broadcaster.  In her spare time she gardens, listens to choral music and is active in the Quakers. She has co-edited an anthology of poetry with an astronomical theme – ‘Dark Matter; Poems of Space’.

'The discovery of pulsars - a graduate student's tale' (Contact: Dr. Esther Wertz, 518-276-2674)
Sage 3303 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