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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Design and flight performance evaluation of the Mariners 6, 7, and 9 short-circuit current, open-circuit voltage transducers

The purpose of the short-circuit voltage transducer is to provide engineering data to aid the evaluation of array performance during flight. The design, fabrication, calibration, and in-flight performance of the transducers onboard the Mariner 6, 7 and 9 spacecrafts are described. No significant differences were observed in the in-flight electrical performance of the three transducers. The transducers did experience significant losses due to coverslides or adhesive darkening, increased surface reflection, or spectral shifts within coverslide assembly. Mariner 6, 7 and 9 transducers showed non-cell current degradations of 3-1/2%, 3%, and 4%, respectively at Mars encounter and 6%, 3%, and 4-12%, respectively at end of mission. Mariner 9 solar Array Test 2 showed 3-12% current degradation while the transducer showed 4-12% degradation.

Patterson, R. E.↗
NASA NTRS1973

Practical applications of digital integrated circuits. Part 3: Practical sequential theory and synchronous circuits

Here, the 7400 line of transistor to transistor logic (TTL) devices is emphasized almost exclusively where hardware is concerned. However, it should be noted that the logic theory contained herein applies to all hardware. Discussed here are synchronous binary UP counters, synchronous DOWN and UP/DOWN counters, integrated circuit counters, shift registers, sequential techniques, and designing sequential counting machines.

Source record↗
NASA NTRS1995

Method for characterizing the upset response of CMOS circuits using alpha-particle sensitive test circuits

A method for predicting the SEU susceptibility of a standard-cell D-latch using an alpha-particle sensitive SRAM, SPICE critical charge simulation results, and alpha-particle interaction physics. A technique utilizing test structures to quickly and inexpensively characterize the SEU sensitivity of standard cell latches intended for use in a space environment. This bench-level approach utilizes alpha particles to induce upsets in a low LET sensitive 4-k bit test SRAM. This SRAM consists of cells that employ an offset voltage to adjust their upset sensitivity and an enlarged sensitive drain junction to enhance the cell's upset rate.

Buehler, Martin G.↗
DOE OSTI2026

Towards Generalizable and Efficient Circuit Topology Design: A Graph-Transformer-based Surrogate Model with Curriculum Learning

Unlike circuit parameter and sizing optimizations, the automated design of analog circuit topologies poses significant challenges for learning-based approaches. One challenge arises from the combinatorial growth of the topology space with circuit size, which limits the topology optimization efficiency. Moreover, traditional circuit evaluation methods are time-consuming, while the presence of data discontinuity in the topology space makes the accurate prediction of circuit performance exceptionally difficult for unseen topologies. To tackle these challenges, we design a novel Graph-Transformer-based Network (GTN) as the surrogate model for circuit evaluation, offering a substantial acceleration in the speed of circuit topology optimization without sacrificing performance. Our GTN model architecture is designed to embed voltage changes in circuit loops and current flows in connected devices, enabling accurate performance predictions for circuits with unseen topologies. To address the cold start problem when scaling GTN to large-scale circuits, we further introduce a curriculum learning strategy that progressively trains GTN from small-scale to large-scale circuits. This approach enables the model to first learn fundamental physical principles from simpler topologies and gradually adapt to complex configurations, effectively bridging the circuit complexity gap and improving prediction accuracy. Taking the power converter circuit design as an experimental task, our GTN model significantly outperforms an analytical approach and baseline methods directly utilizing graph neural networks. Furthermore, GTN achieves less than 5% relative error and 196× speed-up compared with high-fidelity simulation. Notably, our GTN surrogate model empowers an automatic circuit design framework to discover circuits of comparable quality to those identified through high-fidelity simulation while reducing the time required by up to 98.2%. With curriculum learning, the enhanced GTN achieves a 51% improvement for performance prediction of large-scale circuits compared to the GTN model without this strategy. These advancements establish GTN as a scalable framework for automated analog circuit design across varying circuit complexity levels.

Lu, Haoshu [New Jersey Institute of Technology (NJ↗
DOE OSTI2026

A Unidirectional Two-Compartment Neuron Circuit with On-chip STDP learning

Most neuromorphic chips implement the single-compartment point neuron model where synapse circuits connect directly to a leaky integrate and fire (LIF) soma circuit. However, when using a biologically plausible soma circuit (e.g., Hodgkin-Huxley neuron model), an interface circuitry, such as a current conveyor circuit, is needed to transmit synaptic current to the soma circuit. This is especially true for ultra-low power neuron circuits, where membrane capacitance is on the order of 20 fF. This need for an interface circuit arises because the parasitic capacitance and leakage current caused by fabrication mismatch and second-order effects of the output transistors in the synapse circuits can disturb the spiking dynamics of the soma circuit if connected without an interface. Using an interface circuit to isolate the soma’s membrane capacitor from synapses resolves this issue. We propose to use a unidirectional resistor (a transconductance circuit) to connect the synapse and soma circuits instead of conventional current conveyor circuits. Using a biologically plausible spike pattern detection model, we show that the on-chip spike-timing-dependent plasticity (STDP) learning performance of the proposed unidirectional two-compartment neuron circuit is similar to a single-compartment circuit (with a current conveyor as an interface) and additionally, it is more power-efficient and biologically plausible. The chip is fabricated in the Taiwan Semiconductor Manufacturing Company (TSMC) 250 nm technology node and comprises a single neuron circuit.

Gautam, Ashish [ORNL]↗