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Jonathan Mulvey

Publications and source records attributed to Jonathan Mulvey.

2 recordsLinked to original sources

Soft X-Ray Detection Down to the Nitrogen K-Edge Using a Pixelated iLGAD Sensor

Hybrid pixel detectors represent the state-of-the-art technology for hard X-ray experiments at synchrotron light sources and free-electron lasers, owing to their high frame rates, extended dynamic range, and scalable detection areas. However, their application in the soft X-ray regime remains bottlenecked by the challenge of developing a sensor that can achieve high quantum efficiency and an sufficient signal-to-noise ratio at low photon energies. Here, we present inverse low-gain avalanche diode (iLGAD) sensors integrated with a thin entrance window, demonstrating single-photon resolution down to 390 eV (below the Nitrogen K-edge) with a signal-to-noise ratio of 5. Two gain layer designs, standard gain layer and shallow gain layer, were systematically investigated to evaluate their spectral response as a function of photon energy and operating temperature. A double-peak feature is observed in the energy spectrum, arising from the dependence of charge multiplication on photon absorption depth. Furthermore, a phenomenological spectral fitting model was established, enabling the quantitative extraction of the effective $\mathrm{n}^+$ layer thickness and gain layer depth. Beyond providing a fundamental understanding of iLGAD charge multiplication mechanisms and characterization results in the soft X-ray regime, these findings lay the foundation for developing large-area, high-frame-rate hybrid pixel detectors for soft X-ray. This advancement directly benefits soft X-ray photon science applications, including high-resolution ptychography, spectroscopy, and resonant scattering at synchrotron and FEL beamlines.

physics.ins-det↗

Non-destructive 3D doping imaging of silicon sensors

Silicon sensors are the foundational detection medium for X-rays and charged particles. While their bulk dopant distribution determines device performance, it is conventionally assumed homogeneous because traditional profiling is destructive, spatially restricted, and insensitive at the relevant concentrations. Here we introduce a non-destructive 3D doping imaging technique that turns the readout electronics of a charge-integrating hybrid pixel detector into a massively parallelized capacitance-voltage profiler. With a few tens of micrometres of 3D resolution over wafer-scale areas at concentrations on the order of $10^{11}$ cm$^{-3}$, we image the bulk doping concentration of operational sensors. Macroscopically, we resolve depth-evolving concentric doping rings; microscopically, we uncover scattered doping anomalies that distort local electric fields. The rings modulate the depletion voltage, while the anomalies disrupt local charge collection, a previously overlooked cause of pixel yield and performance degradation. By bridging manufacturing signatures with microscopic defects, this approach provides a non-destructive framework for sensor characterization and yield optimization.

physics.ins-det↗