Publications

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In this work we present a novel method for improving the high-temperature performance of silicon photomultipliers (SiPMs) via focused ion beam (FIB) modification of individual microcells. The literature suggests that most of the dark count rate (DCR) in a SiPM is contributed by a small percentage (<5%) of microcells. By using a FIB to electrically deactivate this relatively small number of microcells, we believe we can greatly reduce the overall DCR of the SiPM at the expense of a small reduction in overall photodetection efficiency, thereby improving its high temperature performance. In this report we describe our methods for characterizing the SiPM to determine which individual microcells contribute the most to the DCR, preparing the SiPM for FIB, and modifying the SiPM using the FIB to deactivate the identified microcells.

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This paper reports the experimental comparison of two silicon photomultipliers (SiPMs): the MicroFJ-30035 by ONSemi and the ASD-NUV3S-P by AdvanSiD, in terms of gain, dark count rate, and crosstalk probability. SiPMs are solid state photon detectors that enable high sensitivity light readout. They have low-voltage power requirements, small form factor, and are durable. For these reasons, they are being considered as replacements for vacuum photomultiplier tubes in some applications. However, their performance relies on several parameters, which need to be carefully characterized to enable their high-fidelity simulation and SiPM-based design of devices capable to operate in harsh environments. The parameters tend to vary between manufacturers and processing technologies. In this work, we have compared the MicroFJ and ASD SiPMs in terms of gain, dark count rate, and crosstalk probability. We found that the dark count rate of the MicroFJ was 16% higher than the ASD. Also, the gain of the MicroFJ is 3.5 times higher than the ASD. Finally, the crosstalk probability of the ASD 1.96 times higher than the MicroFJ. Our findings are in good agreement with manufacturer reported values.

The Open Radiation Monitoring (ORM) Project seeks to develop and demonstrate a modular radiation detection architecture designed specifically for use in arms control treaty verification (ACTV) applications that will facilitate rapid development of trusted systems to meet the needs of potential future treaties. Development of trusted systems to support potential future treaties is a complex and costly endeavor that typically results in a purpose-built system designed to perform one specific task. The majority of prior trusted system development efforts have relied on the use of commercial embedded computers or microprocessors to control the system and process the acquired data. These processors are complex, making authentication and certification of measurement systems and collected data challenging and time consuming. We believe that a modular architecture can be used to reduce more complex systems to a series of single-purpose building blocks that could be used to implement a variety of detection modalities with shared functionalities. With proper design, the functionality of individual modules can be confirmed through simple input/output testing, thereby facilitating equipment inspection and in turn building trust in the equipment by all treaty parties. Furthermore, a modular architecture can be used to control data flow within the measurement system, reducing the risk of "hidden switches" and constraining the amount of sensitive information that could potentially be inadvertently leaked. This report documents a conceptual modular system architecture that is designed to facilitate inspection in an effort to reduce overall authentication and certification burden. As of publication, this architecture remains in a conceptual phase and additional funding is required to prove out the utility of a modular architecture and test the assumptions used to rationalize the design.

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A dual-particle imager (DPI) has been designed that is capable of detecting gamma-ray and neutron signatures from shielded SNM. The system combines liquid organic and NaI(Tl) scintillators to form a combined Compton and neutron scatter camera. Effective image reconstruction of detected particles is a crucial component for maximizing the performance of the system; however, a key deficiency exists in the widely used iterative list-mode maximum-likelihood estimation-maximization (MLEM) image reconstruction technique. For MLEM a stopping condition is required to achieve a good quality solution but these conditions fail to achieve maximum image quality. Stochastic origin ensembles (SOE) imaging is a good candidate to address this problem as it uses Markov chain Monte Carlo to reach a stochastic steady-state solution. The application of SOE to the DPI is presented in this work.

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Our work in radiographic image matching has centered on the use of SURF (Speeded Up Robust Features) for feature detection, and FLANN (Fast Learning Artificial Neural Network) for feature matching. We discovered that while the SURF process does return information on location, scale, and rotation for each detected feature, they are not essential for image matching. The nature of the remaining feature detection data does not appear to contain any useful information in terms of reconstructing a useful portion of an image, and therefore is not amenable to reconstructing the original image. This led us to wonder if, in fact, we had discovered an irreversible process; the original image could not be constructed from the remaining feature data. Additional detail on the derivation of the image processing and matching algorithms and the irreversibility hypothesis are available in the final SAND Report documenting our previous LDRD work (SAND2015-9665 “Processing Radiation Images Behind an Information Barrier for Automatic Warhead Authentication” Little, Wilson, Weber and Novick, 2015).

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