Past Seminars

Prof. Michael Yu Wang (HKUST): Material and Structure Design and Optimization in the Era of Additive Manufacturing

Abstract: Additive manufacturing (AM) today affords complete freedom in controlling geometric details and material composition in three-dimensional fabrication. They provide new routes for manufacturing parts with structural properties in high-strength, light-weight, and exceptional performance. To further the adoption of the AM technologies, there is a need for “Design for Additive Manufacturing” methodologies and computer tools that empower designers to realize products that can fully capitalize on the AM capabilities.

Our approach to Design for Additive Manufacturing is an optimization-driven methodology for design exploration, synthesis and multi-disciplinary optimization. Our primary development is a topology optimization method integrated with analysis models for optimal material design of functional components. The required material properties are achieved by optimizing the important factors governing void geometry and material distribution. It generates structurally optimal design concepts from supplied information on loads, constraints and required product performance and manufacture conditions. The method has found a wide range of applications in the design of multi-functional structures, auxetic materials, and light-weight aero-structures. The applications for cellular structures and shellular materials will be particularly discussed.

Bio Sketch: Michael Yu Wang is a Chair Professor and the Founding Director of Robotics Institute at Hong Kong University of Science and Technology. He earned his PhD from Carnegie Mellon University and previously taught at University of Maryland, Chinese University of Hong Kong, and National University of Singapore. He has numerous professional honors–including Ralph R. Teetor Educational Award from Society of Automotive Engineers, 1994; LaRoux K. Gillespie Outstanding Young Manufacturing Engineer Award from Society of Manufacturing Engineers, 1995; Boeing–A.D. Welliver Faculty Summer Fellow, 1998; China State Natural Science Prize (Second Class) from the Ministry of Science & Technology of China (2012), and ASME Design Automation Award (2013) from ASME. He is a Fellow of ASME, HKIE, and IEEE.

Prof. Ronald K. Hanson (Stanford): PW Distinguished Lecture: New Strategies for Laser Diagnostics and Shock Tube Imaging

Abstract: This presentation will introduce two new ideas for laser diagnostics applicable to combustion and propulsion and two new ideas for high-speed imaging of combustion phenomena in a shock tube.  The first laser diagnostic to be discussed is Spectrally-Resolved Fluorescence, in which a narrow-linewidth wavelength-tunable laser source is rapidly scanned over one or more absorption transitions, allowing collection of a spatially resolved laser-induced fluorescence signal that reflects the strength and shape of the absorption feature.  This diagnostic can potentially provide accurate determinations of temperature, pressure, flow velocity and the concentration of the absorbing species.  The example to be presented will be of OH excited and detected in the ultraviolet (UV).  The second new laser diagnostic utilizes a narrow-linewidth infrared laser source that can be scanned rapidly over a relatively wide wavelength range, thereby enabling acquisition of spectral absorption cross-sections over a full rovibrational absorption band of combustion-relevant species in a short time (a few milliseconds), compatible with the test times available in reflected shock wave experiments.   The goal of the experiments is to generate a unique data base for cross-sections over a wide range of temperature, not feasible in a heated static cell.  Two other experiments will be presented, both based on imaging of shock-heated gases. In the first experiment, high-speed imaging is used to visualize and characterize aspects of inhomogeneous ignition that can occur in reflected shock wave experiments of hydrocarbon fuel ignition; such inhomogeneous ignition is undesirable and can contaminate data sets aimed at providing high-quality information on ignition delay times.  As a second example of imaging in a shock tube, a new experiment will be introduced that measures the burning velocity of a flame produced by laser ignition of combustible gases behind a reflected shock wave.  The objective is to enable flame speed measurements at elevated temperatures not accessible with conventional flame speed techniques.  Such conventional methods are limited by the partial reaction of the mixture that occur during the lengthy period of preparing reactive mixtures, whereas with a shock tube experiment the time interval between shock wave heating and ignition can be adjusted to be quite small.  Results obtained in heptane-air flames provide clear evidence of cool flame effects not previously seen in flame speed experiments.  In current work, the observation of flame speed from the time-resolved position of chemiluminescent emission is also being augmented by various laser absorption diagnostics to additionally characterize the burned gases behind the flame.

Bio Sketch: Professor Hanson received his bachelor’s degree from Oregon State University in mechanical engineering and his doctoral degree from Stanford University where he currently holds the Woodard Chair in Mechanical Engineering.  He has been an international leader in the development of laser-based diagnostic methods for combustion and propulsion, and in the development of shock tube methods for accurate determination of chemical reaction rate parameters needed for modeling combustion and propulsion systems, and together with his students he has made several pioneering contributions that have advanced the pace of propulsion research and development worldwide.  He is a Fellow of AIAA, ASME and OSA, a member of the National Academy of Engineering, and a recipient of gold medal awards from the Combustion Institute, the Institute for Dynamics of Explosions and Reactive Systems, and multiple gold medals from the AIAA. He has published over one thousand papers and advised over 100 doctoral students, including 31 now holding faculty appointments around the world.

Dr. Ruhong Zhou (IBM): Large Scale Molecular Simulation of Nanoparticle-Biomolecule Interactions

Abstract: ​Nanoscale particles have become promising materials in various biomedical applications, however, in order to stimulate and facilitate these applications, there is an urgent need for a better understanding of their biological effects and underlying physics. In this talk, I will discuss some of our recent works, mostly molecular modelling, at bio-nano interface and their underlying molecular mechanism. We show that carbon-based nanoparticles (carbon nanotubes, graphene nanosheets, and fullerenes) can interact and disrupt the structures and functions of many important proteins. The hydrophobic interactions between the carbon nanotubes and hydrophobic residues, particularly aromatic residues through the so-called π-π stacking interactions, are found to play key roles. Meanwhile, metallofullerenol Gd@C82(OH)22 is found to inhibit tumour growth and metastases with both experimental and theoretical approaches. Graphene and graphene oxide (GO) nanosheets show strong destructive interactions to ​E. coli cell membranes (antibacterial activity) with unique molecular mechanisms, while PEGylated GO nanosheets stimulate potent cytokine responses in peritoneal macrophages. On the other hand, GO nanosheets also show a strong supportive role in enzyme immobilisation such as lipases through lid opening. In particular, the lid opening is assisted by lipase’s sophisticated interaction with GO, which allows the adsorbed lipase to enhance its enzyme activity. The lipase enzymatic activity can be further optimized through fine tuning of the GO surface hydrophobicity. These findings might provide a better understanding the underlying physics at bio-nano interface, with implications in future ​de novo​ nanomedicine design.

Biographical Sketch: ​Ruhong Zhou, AAAS Fellow, APS Fellow, is currently a Distinguished Research Staff Member and Manager of Soft Matter Science, IBM Healthcare and Life Science Research, and an Adjunct Professor at Department of Chemistry, Columbia University. He received his Ph.D. with Prof. Bruce Berne in chemistry from Columbia University in 1997. He joined IBM Research in 2000, after spending two and a half years working with Prof. Richard Friesner (Columbia Univ) and Prof. William Jorgensen (Yale Univ) on polarizable force fields. He has authored and co-authored 240 journal publications (including 29 in Cell, Science, Nature, Nature subjournals and PNAS), and 26 patents, delivered 200+ invited talks at major conferences and universities worldwide, and chaired and co-chaired many conferences in computational biology, computational chemistry, and biophysics fields. He is part of the IBM Blue Gene team who won the 2009 National Medal on Technology and Innovation. He has won the IBM Outstanding Technical Achievement Award (OTAA) in 2018, 2016, 2014, 2008 and 2005; IBM Outstanding Innovation Award in 2015 and 2012; Columbia University Hammett Award (for best graduates); and American Chemical Society DEC Award on Computational Chemistry. He is Editor-in-Chief of Current Physical Chemistry, Guest Editor of Nanoscale, Editor of (Nature) Scientific Reports, and Editorial Board Member of six other international journals. He also serves as Board of Directors, Telluride Science Research Center (TSRC), and Scientific Advisory Board, Center for Multiscale Theory and Simulation, University of Chicago. He was elected to AAAS Fellow (American Association of Advancement of Science) and APS Fellow (American Physical Society) in 2011, and IBM Distinguished Research Staff Member (DRSM) in 2014.

Integration of Materials Design, Additive Manufacturing and Machine Learning for Personalized Heart Surgery Planning and Optimization

Abstract: ​This seminar presents a research study for personalized heart surgery planning and optimization with integration of advanced materials design, multi-material 3D printing, and machine learning techniques. In this study, a meta-material design approach was first developed to create a mechanical structure that can mimic mechanical behavior of human aortic valves. The tissue-mimicking heart valves were then fabricated using a multi-material 3D printing process. The 3D printed heart valves can be used for pre-surgery planning of heart disease treatment and intervention. The patient-specific heart valves can serve as “virtual patients” which can be used to generate treatment or surgery data for various patients and conditions. In this research, these 3D printed heart valves were used to augment data from relatively small number of available real patients to create more accurate predictive model with machine learning. This model can be used by physicians and surgeons to make more informed decisions for personalized heart surgery planning and optimization. This methodology and its effectiveness were demonstrated through an application case of planning of transcatheter aortic valve replacement (TAVR) surgery.

Biographical Sketch: ​Dr. Chuck Zhang is the Harold E. Smalley Professor at H. Milton Stewart School of Industrial & Systems Engineering of Georgia Institute of Technology. His current research interests include additive manufacturing, cyber-physical systems, and advanced composites/nanocomposites manufacturing and maintenance. Dr. Zhang has managed or conducted numerous research projects sponsored by major federal agencies including National Science Foundation, National Institute of Standards and Technology, Department of Defense, and Department of Veterans Affairs, as well as industrial companies such as ATK, Cummins, Delta Air Lines and Lockheed Martin. He is a fellow of IISE. Dr. Zhang has published over 190 refereed journal articles and 220 conference papers. He also holds 24 U.S. patents.

A Tea Light Candle and the Global Waste Problem

Abstract: In 2012, the World Bank estimated that each person living on planet earth produces approximately 1.2 kg waste per day amounting to 1.2 billion tons per year. By 2025 this number is expected to reach a staggering 2.2 billion tons, which raises the fundamental question:

What is and what happens to waste?

Most of the world’s population lives in developing countries where waste collection services do not work or are non-existent, and domestic burning of waste is a frequent disposal technique. Further, in many developing countries, even when waste is moved to dump sites, it is not uncommon for the material to be burned by open, uncontrolled fires.

In short, fire is the primary mode of waste disposal.

Fire provides volume reduction and prevents disease, but inefficient combustion brings its own hazards in the form of toxic/noxious gasses. In this talk I will discuss the work we have been doing at WPI related to burning hazardous waste cleanly and efficiently. More importantly, I will discuss the inception of the project, which started by observing the burning of a tea light candle and extended to a multi million-dollar effort fueled by students like you!

Biographical Sketch: Ali S. Rangwala is a professor in the department of Fire Protection Engineering at Worcester Polytechnic Institute (WPI) (2006 – present). He has a BS in Electrical Engineering, from the Government College of Engineering, Pune, India (2000), an MS in Fire Protection Engineering from the University of Maryland, College Park (2002), and a PhD in Mechanical and Aerospace Engineering from the University of California, San Diego (2006). Professor Rangwala’s research interests are in the broad areas of environment, industrial fires, and explosion safety.

Credible Computational Solid Mechanics for Critical Decision Making in Engineering

Abstract: Advanced computational modeling, high performance computing technology, and extensive knowledge of simulation form a strong and unique foundation of research, development and engineering at Sandia National Laboratories that enable the Lab to meet its commitment of ensuring the national security of the United States.  Computational models are utilized extensively to predict the complex behavior of materials in multiphysics environments across a wide range of length and time scales, and analysts run simulations routinely to evaluate the performance and reliability of complicated engineering systems designed for national security applications.  In the past three decades, capabilities of simulation tools and models were advanced significantly, and numerous scientific questions and engineering challenges were resolved successfully with the help from computational simulations.  Examples include providing insight of non-linear material response in complex loading environments, examining the integrity of engineering structure when test data are insufficient, modeling microstructure and its linkage to material properties, and predicting aging and material property changes during service.  Although the progress of developing computational predictive capabilities has been highly encouraging so far, it is well recognized in the computational mechanics community that many issues in theories and numerical algorithms yet to be addressed.  While modeling and simulation are being used increasingly as the information-generating and decision-making tools in the cycle of engineering product from design to retirement, how to create and demonstrate credibility of computational analyses, especially for applications in the solid mechanics discipline, is becoming an inevitable challenge for model developers and computational analysts simply because neither codes nor models are perfect.

At this seminar, years of efforts at Sandia to advance the capability of computational solid mechanics modeling for national security and industry applications will be presented, highlighting their challenges and successes.  Lessons learned from bridging physics at different length scales and coupling different simulation codes will be shared.  Most importantly, strategies, including effective and ineffective ones, of developing and presenting model credibility will be discussed. 

Biographical Sketch: Dr. Eliot Fang is the Manager of the Solid Mechanics Department at Sandia National Laboratories. He received his B.S. degree from the National Central University in Taiwan and M.S. and Ph.D. degrees from the University of California at Santa Barbara, all in mechanical engineering. Dr. Fang’s research interest is to apply modeling approaches and high performance computing to elucidate mechanisms of material behaviors and to predict material behaviors at various length scales in different environments.  He has over 60 publications and 70 invited presentations reporting his technical accomplishments and contributions to materials modeling and mechanical simulations.  Dr. Fang is a Fellow of the American Society of Mechanical Engineers and a recipient of the 2006 Asian American Engineer of the Year Award.

Modeling and Control Additive Manufacturing Processes for Ceramics and Glass

Abstract: Additive Manufacturing (AM), which has been referred to as the 4th revolution in manufacturing, is a truly disruptive class of manufacturing. In AM, location-specific mechanical properties can be tailored by grading materials and microstructure, complex geometries that cannot be manufactured with traditional processes can be fabricated, and cost-effective part repair and low volume manufacturing can be realized. However, AM processes have tremendous variability and are not well understood. This has led to significant research efforts into controlling these processes. This talk will discuss our research efforts in the control-oriented modeling and feedback control of two AM processes. The first process is a ceramic extrusion process known as Freeze-form Extrusion Fabrication (FEF) of ceramics, where an aqueous-based ceramic paste is extruded in a freezing environment. This process is ideal for the fabrication of ceramic parts with complex geometries and multiple materials. We will explore the major variations in this process, empirical modeling techniques to describe its dynamic behavior and construct control-oriented models, and methods to control the extrusion force. We will then transition to our work in the first principle, control-oriented modeling of the extrusion force and filament freezing time, and the understanding of the process that is elucidated from these models. The second AM process we will discuss is a new direct energy deposition process to additively manufacture glass. In the AM glass process, filament or fiber is fed into a molten pool of glass formed by a laser energy source. The process can be used to fabricate fully dense transparent free-form parts for gradient index optics, complex structures for embedded optics and waveguides, and freeform structures that open up the glass design space. We will discuss our work in understanding the process and discovering process parameter spaces suitable for fabrication. Two issues that limit the AM glass process are bubble formation and the challenge of placing the glass in a desired location. We will discuss our work in controlling these two issues and discuss future directions for this process.

Biographical Sketch: Dr. Robert G. Landers (landersr@mst.edu) is a Curators’ Distinguished Professor of Mechanical Engineering in the Department of Mechanical and Aerospace Engineering at the Missouri University of Science and Technology (formerly University of Missouri Rolla) and served as the department’s Associate Chair for Graduate Affairs for eight years. He received his Ph.D. degree in Mechanical Engineering from the University of Michigan in 1997. His research interests are in the areas of modeling, analysis, monitoring, and control of manufacturing processes (laser metal deposition, glass direct energy deposition, selective laser melting, freeze–form extrusion fabrication, wire saw machining, metal cutting, friction stir welding), estimation and control of lithium ion batteries and hydrogen fuel cells, and digital control applications. He has over 200 refereed technical publications, including 79 journal articles, an h index of 22 with 1734 citations (Scopus), and $6.4M in funding. He received the Society of Manufacturing Engineers’ Outstanding Young Manufacturing Engineer Award in 2004 and the ASME Journal of Manufacturing Science and Engineering Best Paper Award in 2014, is a Fellow of ASME, a senior member of IEEE and SME, and a member of ASEE. He is currently a program manager at the National Science Foundation, served as associate editor for the ASME Journal of Dynamic Systems, Measurement, and Control (2009–2012), ASME Journal of Manufacturing Science and Engineering (2010–2014), and the IEEE Transactions on Control System Technology (2006–2012), and is currently an associate editor for Mechatronics.

Reversible Solid Oxide Cells and Protonic Ceramic Fuel Cell Technologies as Flexible, Dispatchable Energy Resources

Abstract: ​L​ow-cost, high efficiency, electrical energy storage (EES) is needed for the future electric grid which will include more variable energy resources, such as wind and solar. Movement towards predominately low-carbon energy systems requires renewable resources and could be accelerated by integration of high temperature electrochemical technologies. Currently, substantial penetration of wind and solar resources into the electric power grid is challenged by their intermittency and the timing of generation which can place huge ramping requirements on central utility plants, which are also limited in dynamic response capability. This talk will discuss employing novel EES systems derived from reversible fuel cell technology and advances in protonic ceramics as dispatchable energy resources. Reversible solid oxide cells (ReSOCs) are capable of providing high efficiency and cost-effective electrical energy storage. These systems operate sequentially between fuel-producing electrolysis and power-producing fuel-cell modes with storage of reactants and products (CO​2/​ CH​4g​ ases) in tanks for smaller-scale (kW) applications and between grid and natural gas infrastructures for larger scale (MW) systems. In this talk, the use of ReSOC technology for both grid-scale energy storage and as a Power-to-Gas platform that can address issues with high renewables penetration is presented. In stand-alone systems, strategies for effective thermal management and balance-of-plant systems integration in both operating modes are critical to achieving high roundtrip efficiencies. Design challenges and techno-economic analyses which suggest levelized cost of storage that ranges between 15 – 30 $/MWh are highlighted. A brief overview of recent progress in the performance of intermediate temperature (500-600°C) protonic ceramic fuel cells (PCFCs) which have demonstrated both fuel flexibility and increasing power density that approach commercial application requirements will also be given. The PCFCs investigated in this work are based on a BaZr​0.8Y​ ​0.2O​ ​3-δ(​ BZY20) thin electrolyte supported by BZY20/Ni porous anodes, and a triple conducting cathode material comprised of BaCo​0.4F​ e​0.4Z​ r​0.1Y​ ​0.1O​ ​3-δ(​ BCFZY0.1). Performance characteristics, modeling challenges, and techno-economic outlook of mixed-charge conducting PCFCs are presented.

Biographical Sketch: ​Dr. Robert Braun is Associate Professor of Mechanical Engineering at the Colorado School of Mines. He received a Ph.D. from the University of Wisconsin–Madison in 2002. From 2002-2007, Dr. Braun was at United Technologies Fuel Cell and Research Center divisions where he last served as project leader for UTC’s mobile solid oxide fuel cell (SOFC) power system development program. Dr. Braun has multidisciplinary background in mechanical and chemical engineering and his research focuses on energy systems modeling, analysis, techno-economic optimization, and numerical simulation of transport phenomena occurring within fuel cell and alternative energy systems. His industry experience encompasses development of low-NOx burners, CO​2-​ based refrigeration, and fuel cell technologies (including PEM, PAFC, MCFC, SOFC, and PCFC). Dr. Braun’s current research activities focus on high efficiency hybrid fuel cell/engine systems, renewable energy pathways to synthetic fuel production, grid-scale energy storage, novel protonic ceramics, supercritical CO​2 p​ ower cycles, and dispatch optimization of concentrating solar power plants. He is a Link Energy Foundation Fellow, a member of ASME, ECS, and ASHRAE, and holds 6 U.S. patents.

Physical biology at the semiconductor-enabled biointerfaces

Abstract: ​Recent studies have demonstrated that in addition to biochemical and genetic interactions, cellular systems also respond to biophysical cues, such as electrical, thermal, and mechanical signals. However, we only have limited tools that can introduce localized physical stimuli and/or sense cellular responses with high spatiotemporal resolution. Inorganic semiconductors display a spectrum of physical properties and offer the possibility of numerous device applications. My group integrates material science with biophysics to study several semiconductor-based biointerfaces. In this talk, I will first pinpoint domains where semiconductor properties can be leveraged for biointerface studies, providing a sample of numbers in semiconductor-based biointerfaces. Next, I will present a few recent studies from our lab and highlight key biophysical mechanisms underlying the non-genetic optical modulation interfaces. In particular, I will present a biology-guided two-step design principle for establishing tight intra-, inter-, and extracellular silicon-based interfaces in which silicon and the biological targets have matched mechanical properties and efficient signal transduction. Finally, I will discuss new materials and biological targets that could catalyze future advances.

Biographical Sketch: ​Bozhi Tian received his Ph.D. degree in physical chemistry from Harvard University in 2010. He is now an associate professor at the University of Chicago, working on semiconductor-enabled fundamental studies of subcellular biophysics and soft matter dynamics. Dr. Tian’s accolades from his independent career include the Inaugural ETH Materials Research Prize for Young Investigators (2017), Presidential Early Career Awards for Scientists and Engineers (2016), and TR35 honoree (2012).