ME Seminar: Tao Sun
X-ray Vision of Metal Additive Manufacturing

Monday, October 20, 2025
3:00 PM
L211 Tech

Zoom Link: https://northwestern.zoom.us/j/96276860893

Additive manufacturing (AM, or 3D printing) is a suite of disruptive technologies that build three-dimensional objects by adding materials layer by layer based on digital designs. In particular, metal AM has developed rapidly in the last three decades and found many applications in medical, aerospace, energy, and defense sectors. Numerous 3D printer manufacturers have emerged, and new business models centered on AM are being established across industries. However, despite the excitement surrounding its potential, the qualification and certification of AM parts in risk-averse industries remain significant challenges, hindering the broader adoption of these technologies. This is largely due to the complex interplay of multiple highly dynamic processes inherent to metal AM.

Synchrotron x-ray techniques have emerged as powerful tools for studying metal AM processes. Leveraging high-intensity, high-energy X-ray sources, researchers have investigated a wide range of highly transient phenomena and non-equilibrium structural dynamics in AM using operando X-ray imaging and diffraction techniques. These experiments have advanced the field by:
(i) quantitatively measuring key process and material parameters for model calibration and validation;
(ii) enabling mechanistic studies of defect formation and microstructure evolution; and
(iii) providing high-fidelity ground truth for benchmarking process sensing techniques.

Since the first successful experiment at the Advanced Photon Source in 2016, the research community has expanded rapidly, with operando experiments now conducted at nearly all major synchrotron facilities worldwide and applied across a broad spectrum of AM processes. In this presentation, I will highlight insights from our synchrotron studies on laser powder bed fusion and directed energy deposition, and discuss open questions that could shape the next phase of research.

BIO
Dr. Tao Sun is an Associate Professor of Mechanical Engineering at Northwestern University. He earned his B.S. and M.S. in Materials Science and Engineering (MSE) from Tsinghua University and his PhD in MSE from Northwestern University. Dr. Sun conducted postdoctoral research at Argonne National Laboratory, where he later advanced to Assistant Physicist and Physicist positions. In 2019, he began his academic career at the University of Virginia and then joined Northwestern University in 2023.

Dr. Sun’s research expertise spans X-ray science, additive manufacturing, materials characterization, and advanced instrumentation. His team focuses on uncovering the fundamental physics governing energy-matter interactions, heat and mass transfer, multiphase flow, and non-equilibrium material structure evolution in additive manufacturing. Dr. Sun is recognized as a Highly Cited Researcher by Clarivate.

The Ted Belytschko Seminar

Algorithmic Alloys for Forecasting and Control of Complex Systems

Petros Koumoutsakos
Harvard University, Cambridge, MA
Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering

BIO
Petros Koumoutsakos is Herbert S. Winokur, Jr. Professor of Computing in Science and Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) and currently on sabbatical as a Visiting Research Scientist at Google Deep Mind. He studied Naval Architecture (Diploma-NTU of Athens, M.Eng.-U. of Michigan), Aeronautics and Applied Mathematics (PhD-Caltech). He has conducted post-doctoral studies at the Center for Parallel Computing at Caltech and at the Center for Turbulent Research at Stanford University and NASA Ames. He has served as the Chair of Computational Science at ETHZ Zurich (1997-2020). Petros is elected Fellow of the American Society of Mechanical Engineers (ASME), the American Physical Society (APS), the Society of Industrial and Applied Mathematics (SIAM). He is recipient of the ACM Gordon Bell prize in Supercomputing and elected International Member to the US National Academy of Engineering (NAE). Research in his group explores the fundamentals and applications of computing and AI to understand, predict and optimize complex systems in engineering and medicine.

ABSTRACT
Computational science and Artificial Intelligence have been drivers and benefactors of advances in algorithms and hardware, each in different ways, and originally with different targets. The intellectual space between these two fields is home to exciting opportunities for scientific discovery and engineering innovation. I will describe our decades long explorations on this space and discuss algorithmic alloys based on the fusion of data driven and equation driven methodologies for the prediction and control of complex flows. I will discuss in particular how particle based methods, as pioneered by Ted Belytschko, are today at the foundation of core Machine Learning tools such as graph neural networks. I will also present ideas of developing algorithmic alloys for fusing experiments and simulations for understanding and controlling complex systems.

ABOUT TED BELYTSCHKO
Treasured member of the Northwestern faculty from 1977 until his death in 2014, Ted Belytschko was a central figure in the McCormick community and an internationally renowned researcher who made major contributions to the field of computational structural mechanics. One of the most cited researchers in engineering science, Belytschko developed explicit finite element methods that are widely used in crashworthiness analysis and virtual prototyping in the auto industry. He received numerous honors, including membership in the U.S. National Academy of Engineering, U.S. National Academy of Science, and the American Academy of Arts and Sciences. He was a founding director of the U.S. Association for Computational Mechanics, and in 2012, the association named a medal in his honor. The ASME Applied Mechanics Award was renamed the ASME Ted Belytschko Applied Mechanics Division Award in November 2007. Belytschko also served as editor-in-chief of the International Journal for Numerical Methods in Engineering, and he was co-author of the books “Nonlinear Finite Elements for Continua and Structures” and “A First Course in Finite Elements.”

Thursday, October 23, 2025
3:00 The Hive 2-350 Ford
With Reception to follow in the Willens W

Monday, October 27, 2025
3:00 PM
L211 Tech

Zoom Link: https://northwestern.zoom.us/j/99215996751

ABSTRACT
My research group explores high-resolution optical techniques to investigate elastic wave and heat transport phenomena in condensed matter. In the first half of my talk, I will describe our work on thermal conductivity imaging near single grain boundaries (GBs) in thermoelectric materials. GBs are critical microstructural components that control the performance of thermoelectric materials by reducing the bulk thermal conductivity through the scattering of lattice waves. To date, most GB-thermal conductivity studies have primarily focused on grain size as a fundamental structural property that is important for reducing thermal conductivity. However, it is unclear if the right strategy for optimizing the thermoelectric performance is suppressing the thermal conductivity using small (or nanosized) grains or proliferating thermally resistive GBs. Addressing this fundamental question will be critical to developing next-generation thermoelectric generators for deep space exploration and commercial solid-state refrigerators for mobile phone and electric vehicle applications. In our work, we examine the impact of the GB morphology (e.g., misorientation angle, roughness of the GB plane, nanotwinning, porosity, etc.) on the local thermal conductivity suppression near individual GBs. Our measurements show that the “all GBs are the same” picture adopted in thermal conductivity homogenization modeling is not accurate. Alternatively, each GB is best described as a unique complexion that differs from the surrounding bulk phase. The GB complexion may be controlled by adjusting the thermodynamic parameters of processing methods, leading to complexion transitions similar to those in bulk materials, which can result in drastic changes in bulk transport properties and enhance thermoelectric performance. In the last half of my talk, I will present a dynamic optical coherence elastography (OCE) technique that relies on optical measurement of bulk shear wave propagation for the characterization and mapping of shear viscoelastic properties. My group has adapted the method for viscoelastic characterization of wastewater biofilm membranes and beads. These materials are heterogeneous and may be layered, leading to guided or interfacial elastic waves. I will discuss how we harnessed these wave modes to probe spatial variations in viscoelastic properties, track changes in pH and crosslinking time, and address the influence of stretch-dependent properties.

BIO
Oluwaseyi Balogun is an Associate Professor of Mechanical Engineering and Civil and Environmental Engineering at Northwestern University. He received the B.S. degree from the University of Lagos, Nigeria, and the M.S. and Ph.D. degrees from Boston University, all in Mechanical Engineering. Dr. Balogun’s research focuses on micro- and nanoscale heat transport, elastic wave phenomena, and high-resolution optical and scanning probe microscopy. His research is relevant to applications that involve heat conduction in condensed matter, material characterization based on optical and elastic wave measurements, and high-frequency nanoacoustic devices. He currently serves as the co-director for the Center for Smart Structures and Materials at Northwestern University. He is a member of the IEEE UFFC and IEEE Nanotechnology Societies and a recipient of the 2020 & 2021 IEEE Nanotechnology Council Distinguished Lecturer awards.

Abstract:

In this lecture, mass lumped, rate-type C continuous finite element models of arbitrarily higher order using shear deformable beam, plate, and shell elements are discussed. Higher-order elements provide true curvature, improved performance in bending and buckling, and avoid hourglass modes and numerical locking without ad hoc treatments. Historically, first-order shear deformation finite elements have been predominant in explicit finite element codes because of difficulties achieving robust and reliable mass-lumping. We spatially discretize using a standard weak-form 0 Galerkin finite element approximation and optimal C Lagrange shape functions of arbitrarily higher order and integrate throughout time using a central-difference method and a lumped mass matrix. Several numerical examples of nonlinear finite deformation demonstrating the accuracy and utility of the lumped-mass elements developed are presented.

Bio:

Dr. Reddy is a Distinguished Professor, Regents’ Professor, and the holder of the O’Donnell Foundation Chair IV in Mechanical Engineering at Texas A&M University. He is known for his significant contributions to the field of applied mechanics through the authorship of many textbooks (25) and journal papers (>800). His pioneering works on the development of shear deformation theories have had a major impact and have led to new research developments and applications. In recent years, Reddy's research has focused on the development of locking-free shell finite elements and nonlocal and non-classical continuum mechanics problems dealing with architected materials and structures and damage and fracture in solids. Dr. Reddy has received some of the highest awards, including the Leonardo da Vinci Award from the European Academy of Sciences, the IACM Congress (Gauss-Newton) Medal from the International Association of Computational Mechanics, and the SP Timoshenko Medal from American Society of Mechanical Engineers, He is a member eight national academies.

ABOUT JAN D. ACHENBACH:

Jan D. Achenbach was the Walter P. Murphy Professor and Distinguished McCormick School
Professor Emeritus-in-Service at the McCormick School of Engineering and Applied Science at Northwestern University until his death in August, 2020. He made distinguished contributions to many areas of applied mechanics including fracture mechanics, wave propagation, and quantitative nondestructive evaluation. During his tenure spanning nearly six decades at the McCormick School of Engineering, Prof. Achenbach mentored over 40 Ph.D. students and countless postdocs, many of whom became leaders in industry and academia. His innovations in non-destructive evaluation, such as ultrasonic approaches for inspecting DC-9 aircraft wings without disassembly improved aircraft reliability, saving lives and millions of dollars. Prof. Achenbach received top honors from many professional organizations such as ASME, ASCE, and SES. He was a member of both the National Academy of Engineering and National Academy of Sciences, an elected fellow of the American Academy of Arts and Sciences, and a recipient of both the U.S. National Medal of Technology and the National Medal of Science.

Abstract:

The functioning of Li metal-solid state batteries (LMSSB) requires that interfacial contact between the Li metal anode and the solid electrolyte (SE) be maintained during cycling. A reduction in contact area during Li stripping will increase the local current density during subsequent Li plating, fostering dendrite nucleation. The contact area is influenced by the rate of Li transport within the anode towards the interface. Relevant transport mechanisms include diffusion and creep, with faster rates of these processes resulting in improved performance. Given the importance of these transport modes, predicting them as a function of the anode’s microstructure, stress state, and temperature will be helpful in the design of LMSSB. Here, the rates of diffusion and creep in Li are predicted using atomic scale simulations. A primary goal is to understand if and how Li microstructure impacts the performance of LMSSB. First, molecular dynamics is used to estimate the rate of Li diffusion along dislocations and in grain boundary triple junctions. By combining this data with that from a prior study of grain boundary diffusion, the dominant diffusion mechanisms and overall rates of self-diffusion in Li polycrystals are predicted as a function of grain size, grain shape, dislocation density, and temperature. A 1D continuum model for interfacial contact is parameterized using the computed diffusion data. The model predicts that high dislocation densities (~10 12 /cm 2 ) and/or small grain sizes (~10 m) enable achieving battery performance targets. Secondly, the dominant creep deformation mechanisms are predicted as a function of applied stress, grain size, and temperature. Grain boundary sliding and coble creep are observed to be the primary mechanisms for micron-sized grains. Finally, a kinetic lattice Monte Carlo model is developed to monitor the dynamics of Li voids as a function of interfacial thermodynamics and the presenceof grain boundaries.

Bio:

Don Siegel is Professor and Chair of the Walker Department of Mechanical Engineering at the University of Texas at Austin. He also has appointments in the Oden Institute for Computational Engineering and Sciences and the Texas Materials Institute. At UT he is a Temple Foundation Endowed Professor and holds a Cockrell Family Chair for Departmental Leadership. Prior to joining UT in 2021, Prof. Siegel spent 12 years at the University of Michigan, with earlier posts in industry (Ford Motor Company) and at national laboratories (Sandia National Lab and the U.S. Naval Research Lab). Siegel is a computational materials scientist whose research targets the development of energy storage materials and lightweight alloys. He is a recipient of the NSF Career Award and a Gilbreth Lectureship from the National Academy of Engineering.