Diode-based programmable network array (DiProNA) for high-impact reconfigurable instrumentation

The increasing complexity and integration density of modern mixed-signal and high-frequency systems demand reconfigurable, precise, and fault-tolerant signal-routing architectures. Conventional switching matrices based on multiplexers or crossbar networks suffer from crosstalk, leakage, limited scalability, and weak fault tolerance, making them unsuitable for emerging precision analog platforms. Addressing these limitations, this work introduces the Diode-Based Programmable Network Array (DiProNA), a novel hybrid switching architecture that differs fundamentally from existing structures by combining MOSFET-based programmability with unidirectional diode-assisted conduction paths to achieve intrinsic fault isolation, current sharing, and enhanced thermal robustness. A comprehensive analytical model—developed using Thevenin equivalents, nodal analysis, and explicit inclusion of diode and MOSFET parasitics—is presented and validated through extensive circuit-level simulations. Clear modeling assumptions (such as quasi-static device behavior and linearized small-signal parasitics) are stated to ensure transparency and reproducibility. Quantitative comparisons with traditional multiplexer and crossbar matrices demonstrate that DiProNA achieves higher voltage accuracy, lower effective resistance, and significantly reduced short-circuit current. Series ballast resistors effectively constrain fault currents and mitigate thermal stress, enabling reliable operation under open-circuit, short-circuit, and partial-failure scenarios. Multi-source configurations further enhance efficiency and distribute power-thermal load, while dynamic evaluations confirm microsecond-level response times with minimal overshoot, supporting high-speed instrumentation front-ends. Collectively, the results position DiProNA as a scalable, efficient, and fault-tolerant routing solution suitable for adaptive data converters, SoC subsystems, wireless front-ends, and biomedical instrumentation. This work establishes DiProNA as a robust and versatile platform advancing next-generation programmable mixed-signal systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026.