This seminar inaugurates a series of short talks about research within ACMD.
Tuesday, August 11, 2020, 3:00 PM EDT (1:00 PM MDT)
A video of these talks is available to NIST staff in the Math channel on NISTube, which is accessible from the NIST internal home page.
Challenges in the application of data-driven methods in optical metrology
There are several applications of optics-based metrology in semiconductor manufacturing, including detection of patterning defects and the measurement of critical dimensions of photolithographic masks used to print well-defined geometrical patterns on wafers. While the advantages of optical methods in both cases lie in the high speed and the non-destructiveness, decreasing feature dimensions make it increasingly harder to detect defects or measure the quantities of interest directly with currently available light sources.
In its most straightforward implementation, the defect detection problem can be solved by employing intensity thresholding, mean difference intensity, signal-to-noise ratio (SNR) or linear classification algorithms for differential images or even differential volumes. Critical dimension optical metrology on the other hand is usually formulated as an inverse problem, that necessitates an underlying physical model, e.g. a FEM based electromagnetic simulator. Each of these methods has their own problems, such as robustness of the employed SNRs and increasing time- and memory demands for simulations.
This talk presents how data-driven methods such as convolutional neural networks for the defect detection, and Gaussian process regression for critical dimension metrology can be used to overcome these challenges; the difficulties practitioners might face in reporting an uncertainty budget for the investigated problems will also be addressed.
A Study of the RF Propagation Channel for Wireless Capsule Endoscopy
Comprehensive study of wireless communication for ingestible electronics is a very challenging task. Focusing on wireless capsule endoscopy, we have developed an innovative immersive platform including an enhanced 3D computational human body model. This platform allows for flexible placement of a capsule inside the gastrointestinal (GI) tract and multiple receivers around the abdomen area. The wireless channel study is being performed within the unlicensed Ultra-Wide Band (UWB) frequency range. UWB spectrum is considered to be an attractive candidate for the next generation of wireless capsule endoscopy. In this talk, an overview of the platform, along with some of our recent RF propagation modeling results will be presented.
Mark-Alexander Henn (ACMD/ITL) was born in Mainz, Germany. He studied mathematics at the Technical University (TU) in Berlin, Germny, and got his Diplom (German equivalent to a master's degree) in 2008, with a Diplom thesis on "Hyponormal and strongly hyponormal matrices in inner product spaces." After that he worked as a PhD student in the Mathematical Modelling and Data Analysis Group at PTB in Berlin in collaboration with the Imaging and Wave Optics group of PTB in Braunschweig, Germany and the Institute of Theoretical Physics of TU Berlin. He finished his thesis "A maximum likelihood approach to the inverse problem of scatterometry" in 2013 and in early 2014 started working as a postdoc in the NIST Semiconductor and Dimensional Metrology Division (as it was called back then). In October 2019 he joined NIST's Applied and Computational Mathematics Division to work on uncertainty quantification for the Thermal MagIC project.
Kamran Sayrafian (ACMD/ITL) is leading several projects related to the application of the Internet of Things (IoT) in Healthcare. He is the co-chair of the IoT-Health subgroup at the COST CA15104 “Inclusive Radio Communication Networks for 5G and Beyond”. He was a major contributor in the development of the IEEE802.15.6 international standard on Body Area Networks, and the recipient of the 2015 U.S. Department of Commerce Bronze Medal for his contribution to this emerging field. He is the co-inventor/inventor of four U.S. patents, and holds Ph.D. (1999) and M.S. (1993) degrees in Electrical & Computer Engineering from the University of Maryland and Villanova University, respectively.
This talk will be recorded to provide access to NIST staff and associates who could not be present to the time of the seminar. The recording will be made available in the Math channel on NISTube, which is accessible only on the NIST internal network. This recording could be released to the public through a Freedom of Information Act (FOIA) request. Do not discuss or visually present any sensitive (CUI/PII/BII) material. Ensure that no inappropriate material or any minors are contained within the background of any recording. (To facilitate this, we request that cameras of attendees are muted except when asking questions.)