This Tetris-inspired detector can be a game-changer for radiation safety

Accurate beam angle reconstruction relies on AI-guided analysis of sensor signals, considering relative intensities and detection times in simulated systems.

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Jijo Malayil

MIT and LBNL develop a computational approach for creating basic, efficient sensor setups to locate radiation sources accurately.

Ella Maru Studio

Researchers have devised an improved radiation detector, drawing inspiration from the popular game Tetris.

The technology leverages a computational foundation to create simplified, optimized versions of sensor configurations that can identify the location of a dispersed radiation source.

The demonstration also showed how they might locate the source’s precise location by moving the sensor around to obtain several readings.

According to MIT and the Lawrence Berkeley National Laboratory (LBNL) researchers, their technology may make it possible to monitor nuclear sites with low-cost, precise radiation detectors.

The details of the team’s research were published in the journal Nature.

Practical radiation detection advances

Recent events like Fukushima and the potential threat at Zaporizhzhia underscore the urgent need for reliable methods to identify and track radioactive isotopes. Researchers emphasize that monitoring radioisotope emissions is crucial for nuclear reactor maintenance, uranium processing, and spent fuel disposal.

Semiconductor materials, like cadmium zinc telluride, are commonly used in radiation detection because they generate an electrical reaction when exposed to high-energy radiation, like gamma rays.

However, because radiation passes through materials so easily, it is challenging to use simple counting to determine which direction the signal originated from. For example, Geiger counters only register radiation as a click sound; they do not identify the type or energy of radiation.

Consequently, locating a source involves searching for the highest sound, much like handheld metal detectors. Moving closer to the radiation source is a need of the process, which increases danger.

Large, costly detector arrays with at least 100 pixels in a 10 by 10 array are commonly used to determine the direction of radiation sources.

However, the team discovered they could nearly equal the precision of the massive, costly systems by utilizing as few as four pixels grouped in the tetromino forms of the “Tetris” figurines.

AI-enhanced detector enhances radiation tracking

The secret lies in the accurate computer reconstruction of the beams’ arrival angles, which depends on the relative intensities and times at which each sensor detects the signal. This reconstruction is done using an AI-guided analysis of simulated systems.

According to researchers, inserting an insulating material like a lead sheet between pixels is crucial to ensure the system functions properly. This enhances the contrast of radiation readings coming from different directions into the detector.

In these reduced arrays, the lead between the pixels fulfills the same purpose as the more complex shadow masks in the bigger array systems. The team discovered that less symmetrical layouts yield more meaningful information from a tiny array.

“The merit of using a small detector is in terms of engineering costs. Not only are the individual detector elements expensive, typically made of cadmium-zinc-telluride, or CZT, but all of the interconnections carrying information from those pixels also become much more complex,” said Ryotaro Okabe, a research student at MIT and the project lead, in a statement.

In a single-blind field test conducted by Vavrek at Berkeley Lab using a real cesium radiation source, a test device was used to determine the direction and distance to the source.

“Radiation mapping is of utmost importance to the nuclear industry, as it can help rapidly locate sources of radiation and keep everyone safe,” said Benoit Forget, an MIT professor and co-author of the study, in a statement.

Researchers assert their computational tools, initially tailored for gamma-ray sources, possess broad applicability. They claim to extract directional information from limited pixels across various wavelengths, including neutrons and ultraviolet light.

“This work is critical to the U.S. response community and the ever-increasing threat of a radiological incident or accident,” said Nick Mann, a scientist with the Defense Systems branch at the Idaho National Laboratory.

Abstract

Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, the researchers present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding to enhance contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. The research’s framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

Jijo Malayil Jijo is an automotive and business journalist based in India. Armed with a BA in History (Honors) from St. Stephen's College, Delhi University, and a PG diploma in Journalism from the Indian Institute of Mass Communication, Delhi, he has worked for news agencies, national newspapers, and automotive magazines. In his spare time, he likes to go off-roading, engage in political discourse, travel, and teach languages.

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