The IEEE Transactions On Nuclear Science Best Paper Award is an annual award recognizing the most significant paper published in the Transactions in a given year. The award is sponsored by the IEEE Nuclear and Plasma Sciences Society and the winning paper is selected according to its quantifiable usefulness to the community. The authors of papers published in the Transactions in the third year prior to the year of the award are eligible for consideration. Thus, the 2024 award is awarded to the paper published in calendar year 2021 judged to be the most useful to our community based on metrics calculated for the years 2021, 2022, and 2023.

This year the award is presented to Matthew Marinella for his paper “Radiation Effects in Advanced and Emerging Nonvolatile Memories.” (IEEE TNS Vol. 68, No. 5, May 2021, pp. 546 – 572, DOI 10.1109/TNS.2021.3074139)

The paper reviews the physics, fabrication, operational principles, and commercial status of scaled 2- and 3-D flash memory, new types of nonvolatile memory, and the effects of ionizing radiation on them. Dr. Marinella discusses the physics of and errors caused by total ionizing dose, displacement damage, and single-event upsets, and how these might impact the future of emerging technologies in radiation environments. It has been viewed or cited over 6200 times since publication.

Prof. Matthew J. Marinella is an electrical engineer and researcher focused on emerging microelectronic devices and circuits for computing. He is currently an associate professor in the School of Electrical, Computer and Energy Engineering at Arizona State University since 2022, where he leads a research group focused on emerging technologies for low-energy and radiation-hard computing. From 2010 to 2021, he was with Sandia National Laboratories’ Microsystems S&T Center, where he was a Distinguished Member of the Technical Staff. At Sandia, Dr. Marinella led projects that sought to develop new methods of efficient computing for government applications and extreme environments. He served as PI of numerous large efforts, including the Secure, Efficient, Extreme Environment Computing (SEEEC) Grand Challenge, the Nonvolatile Memory Technology Development Program, and as the Learning Hardware Task Lead for the Hardware Acceleration of Adaptive Neural Algorithms (HAANA) Project. During HAANA, Dr. Marinella led a team that pioneered the use of emerging electrochemical and oxide-based memory devices for neural network training and created multiscale modeling frameworks to understand and improve accuracy of analog in-memory computing accelerators. He served as Lead Scientist for Sandia’s Beyond Moore Computing Lab and DOE-Level Initiatives. Prof. Marinella has published extensively on emerging devices for energy efficient, analog in-memory, neuromorphic, and radiation-hard computing (6500 citations, h-index=36), given numerous invited and contributed talks, and presented several short courses on these topics. He has served in technical advising and leadership roles in various Lab- and DOE-level initiatives on next-generation computing for government applications and is a member of the SRC Decadal Plan Executive Committee, a member of the Microelectronics and Advanced Packaging Technologies (MAPT) Roadmap, chairs the Emerging Memory Devices Section for the IRDS Roadmap Beyond CMOS Chapter. He serves on various conference committees including NSREC and is a Senior Member of the IEEE. Prior to starting at Sandia in 2010, he was a Device Engineer in Microchip’s Technology Development Group. He received his Ph.D. in Electrical Engineering from Arizona State University under advisor Dieter K. Schroder in 2008.

Zane W. Bell, Editor-in-Chief, IEEE Transactions on Nuclear Science can be reached by E-mail at [email protected].