Chiwoo Park

University of Washington | UW · Department of Industrial and Systems Engineering

This chapter presents a dynamic, data-driven modeling methodology, capable of tracking and predicting the transient dynamics of nanoparticle self-assembly processes. The proposed Nanoparticle Self-assembly Process Control and Tracking (NSPECT) methodology combines two different instrumentation technology of complementing capabilities: a dynamic lig...

Active learning of Gaussian process (GP) surrogates has been useful for optimizing experimental designs for physical/computer simulation experiments, and for steering data acquisition schemes in machine learning. In this paper, we develop a method for active learning of piecewise, Jump GP surrogates. Jump GPs are continuous within, but discontinuou...

Many semiconductor fabrication plants (fabs) prefer simulation-based decision making for vehicle dwelling policies because it can capture a fab’s scalability and complexity. Vehicle dwelling policies assign idle vehicles to intra-bay and outer loops in automated material handling systems (AMHSs) to respond quickly to transportation demands. Fabs ar...

This study proposes an average flow time estimation model based on Gaussian process regression that can be applied to adjust the storage locations of partial products and manages demand fluctuations and other dynamic order picking issues. We use the historical order picking data of a progressive zone picking system to extract features for the model...

Data Science for Motion and Time Analysis Motion and time analysis has been a popular tool in operations research for analyzing work performance in manufacturing and service operations. The current practice in motion and time analysis involves many labor-intensive steps such as stop-watching, videotaping, and manual data analysis. It is too ineffic...

Observations of nanoparticle superlattice formation over minutes during colloidal nanoparticle synthesis elude description by conventional understanding of self-assembly, which theorizes superlattices require extended formation times to allow for diffusively driven annealing of packing defects. It remains unclear how nanoparticle position annealing...

Selecting input variables or design points for statistical models has been of great interest in adaptive design and active learning. Motivated by two scientific examples, this paper presents a strategy of selecting the design points for a regression model when the underlying regression function is discontinuous. The first example we undertook was t...

We propose a mixture factor analysis (MFA) method for estimating missing values in building electric load data. Buildings consume a tremendous amount of energy. Thanks to the recent advances in data technologies such as machine learning and applied statistics, data-driven approaches to making buildings more energy-efficient become a major research...

This paper presents a new approach to a robust Gaussian process regression, creating a non-parametric Bayesian regression estimate robust to outliers. Most existing approaches replace an outlier-prone Gaussian likelihood with a non-Gaussian likelihood induced from a heavy tail distribution, such as the Laplace distribution and Student-t distributio...

A large-scale production of carbon nanotubes has been of great interest due to their practical needs, which is limited by the difficulty of producing them with controlled structures and properties. We seek for a surrogate modeling to predict the process yield for a given process configuration under control uncertainties. The predictive power can be...

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of clo...

This paper presents a Gaussian process (GP) model for estimating piecewise continuous regression functions. In scientific and engineering applications of regression analysis, the underlying regression functions are piecewise continuous in that data follow different continuous regression models for different regions of the data with possible discont...

In the materials research, material characterization is an important step to probe and measure the structures and properties of materials from experiments. Imaging instruments play a vital role in material characterization because of their unique and irreplaceable ability to reveal the microstructures of a material. Material scientists has exploite...

In situ microscopes are capable of imaging the transient dynamics of material processes at the nano-scale spatial resolution. The resulting material images contain the structures of material objects that change over the course of a material process. If one is interested in knowing how a population of material objects is collectively evolved in thei...

Material scientists have discovered that certain properties of a composite, for instance, the strength, conductivity or transparency, can be remarkably enhanced by blending nanoparticles into the host materials. The resulting improvement in material properties is believed to depend, to a large degree, on how uniformly nanoparticles are mixed into t...

In situ transmission electron microscope is a promising instrument to explore for the nanoscale world, allowing motion pictures to be taken while nano objects are initiating, crystalizing, and morphing into different sizes and shapes. To enable in-process control of nanocrystal production, this technology innovation needs a data science solution ad...

Many material science problems are centered around understanding the relationship between material structures and material properties/functionalities. Material structures are often imaged and characterized using microscopy techniques and described by the outlines of material interior and exterior structures, as well as the geometric features of the...

Probing the dynamic evolution of material structures, in response to physical or chemical stimuli, is of great interest to material scientists for the purpose of studying and designing novel materials. Studies of the dynamic evolutions are enabled through analyzing a sequence of microscopic images taken at different times or different stages of the...

Image segmentation is the process of partitioning an image into non-overlapping regions of homogeneity, where homogeneity is defined in terms of an image feature such as intensity and certain textures. In the material image analysis, the segmentation task is a necessary pre-processing step to extract important information concerning material struct...

Beyond morphology, studies on the spatial positioning and arrangements of smaller scale elements within bulk materials are of great interest to material scientists, because analysis of such arrangements could yield insights concerning the functionalities of materials. Towards that end, Chap. 5 presents the location and dispersion analysis of nanoma...

In situ TEM and other dynamic imaging instruments alter the landscape of materials science and engineering. The unique and unprecedented ability to observe the transformation of nanoscale objects as it occurs is unparalleled in comparison to other material characterization methods, and is of tremendous value to material scientists and engineers who...

This chapter is concerned with super-resolution methods for image enhancement. Development of super-resolution methods is dated back to early 1980s, and the effort intensifies greatly in the past two decades. The essential objective of super-resolution is to enhance the quality of a low-resolution image, using a high-resolution counterpart. The sup...

This paper proposes a day-ahead electric load forecasting model for buildings where daily load curves follow a few distinctive patterns. A pattern lasts for several days before changing into another. We particularly explore the problem that the day-ahead curve mostly depends on the load pattern history and is relatively insensitive to external envi...

This book combines two distinctive topics: data science/image analysis and materials science. The purpose of this book is to show what type of nano material problems can be better solved by which set of data science methods. The majority of material science research is thus far carried out by domain-specific experts in material engineering, chemist...

A natural disaster often generates large quantities of debris and waste, which challenges local waste management systems. Therefore, it is important to effectively prioritize affected areas for debris collection, mobilize limited resources, and manage local waste management systems based on resilience. The impact of disaster debris spatially varies...

We present a data-driven distribution tracking system that is capable of tracking the process quality in a chemical synthesis process for nanoparticles. In the process, the process quality is defined as a distribution of particle sizes and shapes, which influence the functionalities of nanoparticles. A system of tracking the distribution of nanopar...

This paper presents a new variable selection approach integrated with Gaussian process (GP) regression. We consider a sparse projection of input variables and a general stationary covariance model that depends on the Euclidean distance between the projected features. The sparse projection matrix is considered as an unknown parameter. We propose a f...

The motion-and-time analysis has been a popular research topic in operations research, especially for analyzing work performances in manufacturing and service operations. It is regaining attention as continuous improvement tools for lean manufacturing and smart factory. This paper develops a framework for data-driven analysis of work motions and st...

Liquid Cell Transmission Electron Microscopy (LCTEM) is a powerful in situ videography technique that has the potential to allow us to observe solution phase dynamic processes at the nanoscale, including imaging the diffusion and interaction of nanoparticles. Artefactual effects imposed by the irradiated and confined liquid-cell vessel alter the sy...

Electron tomographic reconstruction is a method for obtaining a three-dimensional image of a specimen with a series of two dimensional microscope images taken from different viewing angles. Filtered backprojection, one of the most popular tomographic reconstruction methods, does not work well under the existence of image noises and missing wedges....

This paper presents a new approach to a robust Gaussian process (GP) regression. Most existing approaches replace an outlier-prone Gaussian likelihood with a non-Gaussian likelihood induced from a heavy tail distribution, such as the Laplace distribution and Student-t distribution. However, the use of a non-Gaussian likelihood would incur the need...

This paper presents a new Gaussian process (GP) metamodeling approach for predicting the outcome of a physical experiment for a given input factor setting where some of the input factors are controlled by other manipulating factors. Particularly, we study the case where the control precision is not very high, so the input factor values vary signifi...

Spatially Mapping Heterogeneous Nucleation Kinetics of Silver Nanocrystals with Liquid Cell Scanning Transmission Electron Microscopy - Volume 25 Supplement - M. Wang, T.U. Dissanayake, C. Park, T.J. Woehl

Visualizing Platinum Supraparticle Formation with Liquid Cell Electron Microscopy and Correlative Investigation of Catalytic Activity - Volume 25 Supplement - Mei Wang, Chiwoo Park, Taylor J. Woehl

Nucleation underlies the formation of many liquid-phase synthetic and natural materials with applications in materials chemistry, geochemistry, biophysics, and structural biology. Most liquid-phase nucleation processes are heterogeneous, occurring at specific nucleation sites at a solid-liquid interface; however, the chemical and topographical iden...

p>Nucleation underlies the formation of many liquid-phase synthetic and natural materials with applications in materials chemistry, geochemistry, biophysics, and structural biology. Most liquid-phase nucleation processes are heterogeneous, occurring at specific nucleation sites at a solid-liquid interface; however, the chemical and topographical id...

In this paper, we show the rapid generation of phase diagrams for block copolymer amphiphiles. We demonstrate the high-Throughput approach for two separate types of amphiphilic block copolymers: One type consisting of poly(ethylene glycol)-b-poly(2-hydroxypropyl methacrylate) and the other consisting of poly(2-(dimethylamino)ethyl methacrylate)-b-p...

Advancements in temporal and spatial resolutions of microscopes promise to expand the frontiers of understanding in materials science. Imaging techniques produce images at a high-frame rate, streaming out a tremendous amount of data. Analysis of all these images is time-consuming and labor intensive, creating a bottleneck in material discovery that...

Toward Quantitative Liquid Cell Electron Microscopy through Kinetic Control of Solution Chemistry - Volume 25 Issue S1 - Mei Wang, Chiwoo Park, Taylor Woehl

In this article, we report on complex nanochemistry and transport phenomena associated with silver nanocrystal formation by electron beam induced growth and liquid cell electron microscopy (LCEM). We synthesized silver nanocrystals using scanning transmission electron microscopy (STEM) electron beam induced synthesis and systematically varied the e...

Quantitative Modeling of Kinetically Controlled Nanocrystal Synthesis with Liquid Cell Electron Microscopy - Volume 24 Supplement - Mei Wang, Taylor J. Woehl, Chiwoo Park

In this paper, we describe the use of liquid cell transmission electron microscopy (LCTEM) for inducing and imaging the formation of spherical micelles from amphiphilic block copolymers. Within the irradiated region of the liquid cell, diblock copolymers were produced which self-assembled, yielding a targeted spherical micellar phase via polymeriza...

This paper presents a robust regression approach for image binarization under significant background variations and observation noise. The work is motivated by the need of identifying foreground regions in noisy microscopic images or degraded document images, where significant background variations and observation noise make image binarization chal...

In situ liquid cell transmission electron microscopy (LC-TEM) allows dynamic nanoscale characterization of systems in a hydrated state. Although powerful, this technique remains impaired by issues of repeatability that limit experimental fidelity and hinder the identification and control of some variables underlying observed dynamics. We detail new...

This paper presents a regularized regression model with a two-level structural sparsity penalty applied to locate individual atoms in a noisy scanning transmission electron microscopy image (STEM). In crystals, the locations of atoms is symmetric, condensed into a few lattice groups. Therefore, by identifying the underlying lattice in a given image...

Assembly through mating a pair of machined surfaces plays a crucial role in many manufacturing processes such as automotive powertrain production, and the mating errors during the assembly (i.e., gaps between surfaces) can cause significant internal leakage and functional performance problems. The surface mating errors are difficult to diagnose bec...

div>In this article, we report on complex nanochemistry and transport phenomena associated with nanocrystal formation by electron beam induced growth and liquid cell electron microscopy (LCEM). We synthesized silver nanocrystals using scanning transmission electron microscopy (STEM) electron beam induced synthesis and systematically varied the elec...

Revolutions in science and engineering frequently result from the development, and wide adoption, of a new, powerful characterization or imaging technique. Beginning with the first glass lenses and telescopes in astronomy, to the development of visual-light microscopy, staining techniques, confocal microscopy, and fluorescence super-resolution micr...

Amphiphilic small molecules and polymers form commonplace nanoscale macromolecular compartments and bilayers, and as such are truly essential components in all cells and in many cellular processes. The nature of these architectures, including their formation, phase changes, and stimuli-response behaviors, is necessary for the most basic functions o...

Multi-Modal Characterization of New Battery Technologies by Operando ec-STEM - Volume 23 Issue S1 - B. L. Mehdi, J. Chen, A. Stevens, C. Park, L. Kovarik, A. V. Liyu, W. A. Henderson, J-G. Zhang, K. T. Mueller, N. D. Browning

This paper presents a new approach for Gaussian process (GP) regression for large datasets. The approach involves partitioning the regression input domain into multiple local regions with a different local GP model fitted in each region. Unlike existing local partitioned GP approaches, we introduce a technique for patching together the local GP mod...

Covalent organic frameworks (COFs) are two- or three-dimensional (2D or 3D) polymer networks with designed topology and chemical functionality, permanent porosity, and high surface areas. These features are potentially useful for a broad range of applications, including catalysis, optoelectronics, and energy storage devices. But current COF synthes...

The development of in-situ liquid stages for the (S)TEM presents many opportunities to study dynamic processes important for next generation energy storage, transport and conversion systems. However, to use the microscope to study these systems we must be aware of the effect of the electron beam in controlling/altering the experiment. Fortunately,...

In the last decades, radiolytic synthesis routes have exploited the chemical effects of the absorption of high-energy radiation on precursor solutions, to form nanostructures by reproducing a selective reducing/oxidizing environment. Radiation chemical synthesis provides a powerful means to form nuclei which are homogeneously distributed in the who...

This paper presents a regularized regression model with two-level structural sparsity penalties and applies it for locating individual atoms in a noisy electron microscope image. For crystalline materials, the locations of atoms have spatial symmetries, forming a few regular lattice groups. Therefore, by simply estimating the underlying lattice gro...

Understanding the Effect of Additives in Li-ion and Li-Sulfur Batteries by Operando ec- (S)TEM - Volume 22 Issue S5 - B. Layla Mehdi, Andrew Stevens, Jiangfeng Qian, Chiwoo Park, Wu Xu, Wesley A. Henderson, Ji-Guang Zhang, Karl T. Mueller, Nigel D. Browning

We introduce a new approach to a linear-circular regression problem that relates multiple linear predictors to a circular response, bringing a new modeling perspective on a circular variable. Some previous works model a circular variable as projection of a bivariate Gaussian random vector on the unit square, and the statistical inference of the res...

One of the most promising means to increase the energy density of state-of-the-art lithium Li-ion batteries is to replace the graphite anode with a Li metal anode. While the direct use of Li metal may be highly advantageous, at present its practical application is limited by issues related to dendrite growth and low Coulombic efficiency, CE. Here o...

This paper develops an efficient computational method for solving a Gaussian process (GP) regression for large spatial data sets using a collection of suitably defined local GP regressions. The conventional local GP approach first partitions a domain into multiple non-overlapping local regions, and then fits an independent GP regression for each lo...

This paper presents a robust matrix decomposition approach that automatically segments a binary image to foreground regions and background regions under high observation noise levels and uneven background intensities. The work is motivated by the need of identifying foreground objects in a noisy electron microscopic image, but the method can be app...

Tomographic reconstruction is a method of reconstructing a high dimensional image with a series of its low dimensional projections, and the filtered backprojection is one of very popular analytical techniques for the reconstruction due to its computational efficiency and easy of implementation. The accuracy of the filtered backprojection method det...

Nanoscientists have long conjectured that adjacent nanoparticles aggregate with one another in certain preferential directions during chemical syntheses of nanoparticles, which is so called the oriented attachment. For the study of the oriented attachment phenomenon, the microscopy and nanoscience community have used dynamic electron microscopy for...

Nanoscientists have long conjectured that adjacent nanoparticles aggregate with one another in certain preferential directions during a chemical synthesis of nanoparticles, which is referred to the oriented attachment. For the study of the oriented attachment, the microscopy and nanoscience communities have used dynamic electron microscopy for dire...

div class="title"> Understanding the Effect of Additives in Li-Sulfur Batteries by Operando ec- (S)TEM - Volume 22 Issue S3 - B. L. Mehdi, R. Cao, C. Park, W. A. Henderson, W. Xu, J. Liu, J. -G. Zhang, K. T. Mueller, N. D. Browning

div class="title">The Mechanisms for Preferential Attachment of Nanoparticles in Liquid Determined Using Liquid Cell Electron Microscopy, Machine Learning, and Molecular Dynamics - Volume 22 Issue S3 - Taylor Woehl, David Welch, Chiwoo Park, Roland Faller, James Evans, Nigel Browning

This paper presents a simulation-guided regression approach for estimating the size distribution of nanoparticles with dynamic light scattering (DLS) measurements. The properties and functionalities exhibited by nanoparticles often depend on their sizes, so the precise quantification of the sizes is important for characterizing and monitoring the q...

Org. block copolymer micelle nanoparticles (NPs) have shown tremendous potential for active drug delivery in vivo. The synthesis of micelle NPs is typically controlled via methods involving cosolvent mixts., with the assumption that the structures produced are stable following transfer to aq. soln. Recent studies suggest that ongoing dynamic intera...

Synthesizing nanomaterials of uniform shape and size is of critical importance to access and manipulate the novel structure-property relationships arising at the nanoscale, such as catalytic activity. In this work, we synthesize Pd nanoparticles with well-controlled size in the sub-3 nm range using scanning transmission electron microscopy (STEM) i...

Optimization of colloidal nanoparticle synthesis techniques requires an understanding of underlying particle growth mechanisms. Non-classical growth mechanisms are particularly important as they affect nanoparticle size and shape distributions which in turn influence functional properties. For example, preferential attachment of nanoparticles is kn...

Here we report a significant advancement in materials science made possible by the use of liquid cell transmission electron microscopy. Namely, the ability to observe self-assembly of Metal-Organic Frameworks (MOFs) in liquids with nanometer resolution. MOFs were studied by LCTEM in order to understand and demonstrate control over the dynamics a...

Studying liquid samples in the (scanning) transmission electron microscope ((S) TEM) represents specific challenges as compared to the study of crystalline/amorphous solid specimens. Solutions decompose upon e--beam irradiation through radiolytic processes and chemical species are generated in the liquid phase. These species interact with the s...

div class="title">Quantification of Electrochemical Nanoscale Processes in Lithium Batteries by Operando ec -(S)TEM - Volume 21 Issue S3 - B. L. Mehdi, J. Qian, E. Nasybulin, C. Park, D. A. Welch, R. Faller, H. Mehta, W. A. Henderson, W. Xu, C. M. Wang, J. E. Evans, J. Liu, J. -G. Zhang, K. T. Mueller, N. D. Browning

This paper proposes a new damage monitoring method based on a multivariate cumulative sum test statistic applied to Lambwave sensing data for health monitoring in composites. The CUSUM monitoring method applied to the features extracted with Principal Components Analysis was studied to improve robustness of detection and sensitivity to small damage...

Lithium (Li)-ion batteries are currently used for a wide variety of portable electronic devices, electric vehicles and renewable energy applications [1,2]. In addition, extensive worldwide research efforts are now being devoted to more advanced “beyond Li-ion” battery chemistries - such as lithium-sulfur (Li-S) [3] and lithium-air (Li-O 2 ) [4] - i...

Many processes in materials science, chemistry and biology take place in a liquid environment – such as the synthesis of nanoparticles, biological cellular functions and the operation of Li-ion/next generation batteries. In these cases, the overall process/function of the system is a result of a series of complicated transients, where a change in t...

Liquid cell transmission electron microscopy (LCTEM) can provide direct observations of solution-phase nanoscale materials, and holds great promise as a tool for monitoring dynamic self-assembled nanomaterials. Control over particle behavior within the liquid cell, and under electron beam irradiation, is of paramount importance for this technique t...

The high demand for new energy storage materials has created a need for experimental techniques that can provide real-time information on the dynamic structural changes/processes that occur locally at the electrode/electrolyte interface during battery operation. In this regard, in-sit u electrochemical stages for (scanning) transmission electron mi...