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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Skyrmion-Based Programmable Logic Device with Complete Boolean Logic Functions

A skyrmionic programmable logic device (SkrPLD) with complete Boolean logic functions is proposed and analyzed by micromagnetic simulations. The SkrPLD is based on an antiferromagnet/ferromagnet bilayer structure, in which the antiferromagnetic layer supports the interfacial Dzyaloshinskii–Moriya interaction and the out-of-plane exchange bias field for stabilizing a zero-field skyrmion. By varying the local exchange bias field, artificial pinning sites are introduced for trapping the skyrmions. Depending on the input currents and the initial position of skyrmions at different pinning sites, different logic functions can be realized. Micromagnetic simulations show that the proposed SkrPLD has robust performance even under thermal fluctuations and inhomogeneity effects. Our work can provide insights for the design of programmable spin logic devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2013

Nonvolatile “AND,” “OR,” and “NOT” Boolean logic gates based on phase-change memory

Electronic devices or circuits that can implement both logic and memory functions are regarded as the building blocks for future massive parallel computing beyond von Neumann architecture. Here we proposed phase-change memory (PCM)-based nonvolatile logic gates capable of AND, OR, and NOT Boolean logic operations verified in SPICE simulations and circuit experiments. The logic operations are parallel computing and results can be stored directly in the states of the logic gates, facilitating the combination of computing and memory in the same circuit. These results are encouraging for ultralow-power and high-speed nonvolatile logic circuit design based on novel memory devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

UltraLiM: In-Memory Boolean Logic Architecture Using UltraRAM

Conventional computing architectures encounter ‘von Neumann’ and ‘memory wall’ bottlenecks which arise due to the back-and-forth data movement between the physically separate memory and processing units and the speed mismatch between them, respectively. These bottlenecks hurt both energy efficiency and the throughput of computing systems. To address these challenges, in-memory computing architectures have emerged as a promising alternative. They reduce the need for frequent data movement by executing different computing tasks inside the memory system. Here, we present UltraLiM, a logic-in-memory architecture using the UltraRAM-based memory system. UltraRAM holds the promise of developing a ‘universal memory’, overcoming the limitations of charge-based memories thanks to their non-volatile behavior with lower operating voltage. This work presents an in-memory computing architecture that integrates an UltraRAM-based memory array with a custom-designed peripheral circuitry. With this architecture, we can perform various in-memory Boolean logic operations (such as NOT, NAND, NOR, and XOR) in a single cycle. Leveraging the separate read-write paths in the UltraRAM-based memory array, we optimize read operations without encountering design conflicts. This optimization enhances the sense margin, enabling the use of simpler peripheral circuitry for in-memory logic operations.

Alam, Shamiul [University of Tennessee, Knoxville ↗
DOE OSTI2024

Tunable stochastic memristors for energy-efficient encryption and computing

Information security and computing, two critical technological challenges for post-digital computation, pose opposing requirements – security (encryption) requires a source of unpredictability, while computing generally requires predictability. Each of these contrasting requirements presently necessitates distinct conventional Si-based hardware units with power-hungry overheads. This work demonstrates Cu 0.3 Te 0.7 /HfO 2 (‘CuTeHO’) ion-migration-driven memristors that satisfy the contrasting requirements. Under specific operating biases, CuTeHO memristors generate truly random and physically unclonable functions, while under other biases, they perform universal Boolean logic. Using these computing primitives, this work experimentally demonstrates a single system that performs cryptographic key generation, universal Boolean logic operations, and encryption/decryption. Circuit-based calculations reveal the energy and latency advantages of the CuTeHO memristors in these operations. This work illustrates the functional flexibility of memristors in implementing operations with varying component-level requirements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Acoustic logic gates and Boolean operation based on self-collimating acoustic beams

The reveal of self-collimation effect in two-dimensional (2D) photonic or acoustic crystals has opened up possibilities for signal manipulation. In this paper, we have proposed acoustic logic gates based on the linear interference of self-collimated beams in 2D sonic crystals (SCs) with line-defects. The line defects on the diagonal of the 2D square SCs are actually functioning as a 3 dB splitter. By adjusting the phase difference between two input signals, the basic Boolean logic functions such as XOR, OR, AND, and NOT are achieved both theoretically and experimentally. Due to the non-diffracting property of self-collimation beams, more complex Boolean logic and algorithms such as NAND, NOR, and XNOR can be realized by cascading the basic logic gates. The achievement of acoustic logic gates and Boolean operation provides a promising approach for acoustic signal computing and manipulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Magnon-based logic in a multi-terminal YIG/Pt nanostructure

Boolean logic is the foundation of modern digital information processing. Recently, there has been a growing interest in phenomena based on pure spin currents, which allows to move from charge to spin based logic gates. We study a proof-of-principle logic device based on the ferrimagnetic insulator Yttrium Iron Garnet, with Pt strips acting as injectors and detectors for non-equilibrium magnons. We experimentally observe incoherent superposition of magnons generated by different injectors. This allows to implement a fully functional majority gate, enabling multiple logic operations (AND and OR) in one and the same device. Clocking frequencies of the order of several GHz and straightforward down-scaling make our device promising for applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Logical Activation Functions v.1.1

SAND2024-01501O Logical Activation Functions software is a PyTorch implementation from the paper, "Logical Activation Functions for Training Arbitrary Probabilistic Boolean Logic." The activation functions approximate logit-space marginalization of probabilistic truth tables from probabilistic interpretations of inputs. They also provide a general methodology to approximate logical relationships between abstract antecedents and consequents for machine learning architectures. They do not target any specific application or use-case. By training probabilistic truth tables, these activation functions can capture more expressive relationships in a neural network than typical elementwise activation functions. This code is only designed for a single compute node with a GPU and is limited to machine learning architectures than can fit within the memory of a single GPU. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Duersch, Jed↗
DOE OSTI2023

Extending Parsimonious Bayesian Inference

Parsimonious Bayesian inference is a theoretical framework for efficient data assimilation that seeks to balance increased consistency between predictions and training data against corresponding increases in model complexity. Within this framework, over-training is understood as optimization that encodes excessive information within model parameters while only achieving small improvements between predictions and training data. This project aims to develop practical methods of limiting excess model information during optimization. One key observation is that practical heuristics for parsimonious learning in high-dimensions must balance expressivity, i.e. the ability of the model to capture diverse predictions with only a few non-zero parameters, against discoverability, i.e. the ability to train the model with gradient-based optimization and drive parameters to low information states. As such, we developed logical activation functions that are able to adaptively approximate arbitrary truth tables that define Boolean logic operations within a probabilistic framework. These functions have demonstrated the ability to learn exclusive disjunction (XOR) and conditioned disjunction (if [condition] then [result_if_true] else [result_if_false]) within a single layer of a neural network. To efficiently exploit these activation functions to drive parsimonious learning required several other advances within the domain of variational inference. The most efficient form of complexity suppression is structured sparsification, driving most model parameters to zero while achieving the structural coherence among nonzeros needed for bandwidth reduction. Such models are not only far more efficient at suppressing information-theoretic complexity, they also reduce the other forms of complexity (computations, communication, storage, and the number of dependencies needed to evaluate predictions). Aiming to support enhanced sparsification, this project examined new approaches to high-dimensional variational inference that allow us to calibrate and control parameter uncertainty during optimization. By identifying which parameters can sustain sparsifying perturbations with little impact on prediction quality, we can develop better pruning strategies by framing them as approximate Bayesian inference. These advances also open paths to mitigate concerns with deploying advanced learning methods in resource-constrained environments, such as running models on power-limited or communication-limited devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Quantum random flip-flop and its applications in random frequency synthesis and true random number generation

In this work, a new type of elementary logic circuit, named random flip-flop (RFF), is proposed, experimentally realized, and studied. Unlike conventional Boolean logic circuits whose action is deterministic and highly reproducible, the action of a RFF is intentionally made maximally unpredictable and, in the proposed realization, derived from a fundamentally random process of emission and detection of light quanta. We demonstrate novel applications of RFF in randomness preserving frequency division, random frequency synthesis, and random number generation. Possible usages of these applications in the information and communication technology, cryptographic hardware, and testing equipment are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A review of crosstalk polymorphic circuits and their scalability

Using a control variable, the functionality of Polymorphic circuits can be modified, making them adaptable and useful for reconfiguring circuit behavior — all the way from gate level to system level. State-of-the art polymorphic circuits are based on custom non-linear circuit design or emerging devices such as ambipolar FET, configurable magnetic devices etc. While some of these approaches are inefficient in performance, others involve exotic devices. The Crosstalk computing based polymorphic circuits offer a fresh perspective. In Crosstalk, the interconnect interference between nanoscale metal lines is intentionally engineered to exhibit the programmable Boolean logic behavior. This approach relies on the coupling between metal lines and not on the transistors for computing, resulting in better scalability, security by obscurity, and fault tolerance by reconfiguration. Our novel approach is backed by the mathematical formulation that conveys the rationale to generalize and achieve a wide variety of polymorphic circuits. Our experiments, including design, simulation, and Power Performance Area (PPA) characterization results indicate that crosstalk circuits provide significant improvement in transistor count (about 3x), switching energy (2x), and speed (1.5x) for polymorphic logic circuits. In the best-case scenario, the transistor count reduction is 5x. This paper presents Crosstalk computing’s fundamentals, polymorphism and the scalability aspects to compete/co-exist with CMOS for digital logic implementations below 10 nm. Our scalability study uses Open Source 7 nm PDK, considers all process variation aspects and accommodates worst-case scenarios. The study results for various benchmark circuits show that the Crosstalk technology is a viable alternative to CMOS for digital logic implementations below 10 nm, having 48% density, 57% power, and 10% performance gains over equivalent CMOS counterparts. Finally, we compare Crosstalk Polymorphic Circuit design technique with similar approaches described in related works and discuss its features and constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage

To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

On the Language of Reliability: A System Engineer Perspective

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences, and how likely is it to occur? While this definition makes sense in a regulatory-based framework where for the current fleet of operating light water reactors (LWRs), the risks associated with nuclear power plants typically are characterized in terms of core damage and large early release frequency (LERF), this approach does not provide a useful snapshot of the health of the plant from a broader perspective. This is due to the very narrow context in which the term “risk” typically is defined as nuclear safety aspects that have the potential to impact public health. In this paper, we take the viewpoint of nuclear safety that is reflective of the current fleet of operating LWRs for which core damage frequency and LERF are appropriate metrics. For other advanced reactor designs, other more applicable technology neutral metrics of reactor safety metrics would be specified. A possible alternate path would start by redefining the word risk with a broader meaning that better reflects the needs of a system health and asset management decision-making process. Rather than asking how likely an event could occur (in probabilistic terms), we can ask how far this event is from occurring. Our approach starts by defining and quantifying component and system health in terms of a “distance” between its actual and limiting conditions, i.e., determination of the margin that exists between the current state/condition and the state where the component/system is no longer capable of achieving its intended function. A margin is a measure that is more reflective of the current state or performance of a component, and therefore more closely tied to decisions that are made on an ongoing basis. Further, we will show how, given the data available from plant equipment reliability and monitoring (e.g., pump vibration data) and prognostic (e.g., component remaining useful life estimation) data, a margin can be described and determined for all types of maintenance approaches (e.g., corrective or predictive maintenance). We show how classical reliability models (e.g., fault trees) can be used to quantify the system margin provided component margin values. In the approach described in this paper, the propagation of margin values through classical reliability models are not performed using classical probabilistic calculations applied to sets (as performed in a typical plant probabilistic risk assessment). Instead, we show how it is possible to propagate margin values through Boolean logic gates (i.e., AND and OR operators) through distance-based operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

DNA-mediated excitonic upconversion FRET switching

Excitonics is a rapidly expanding field of nanophotonics in which the harvesting of photons, ensuing creation and transport of excitons via Förster resonant energy transfer (FRET), and subsequent charge separation or photon emission has led to the demonstration of excitonic wires, switches, Boolean logic and light harvesting antennas for many applications. FRET funnels excitons down an energy gradient resulting in energy loss with each step along the pathway. Conversely, excitonic energy up conversion via up conversion nanoparticles (UCNPs), although currently inefficient, serves as an energy ratchet to boost the exciton energy. Although FRET-based up conversion has been demonstrated, it suffers from low FRET efficiency and lacks the ability to modulate the FRET. We have engineered an up conversion FRET-based switch by combining lanthanide-doped UCNPs and fluorophores that demonstrates excitonic energy up conversion by nearly a factor of 2, an excited state donor to acceptor FRET efficiency of nearly 25%, and an acceptor fluorophore quantum efficiency that is close to unity. These findings offer a promising path for energy up conversion in nanophotonic applications including artificial light harvesting, excitonic circuits, photovoltaics, nanomedicine, and optoelectronics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Objective past of a quantum universe: Redundant records of consistent histories

Motivated by the advances of quantum Darwinism and recognizing the role played by redundancy in identifying the small subset of quantum states with resilience characteristic of objective classical reality, we explore the implications of redundant records for consistent histories. The consistent histories formalism is a tool for describing sequences of events taking place in an evolving closed quantum system. A set of histories is consistent when one can reason about them using Boolean logic, i.e., when probabilities of sequences of events that define histories are additive. However, the vast majority of the sets of histories that are merely consistent are flagrantly nonclassical in other respects. This embarras de richesses (known as the set selection problem) suggests that one must go beyond consistency to identify how the classical past arises in our quantum universe. The key intuition we follow is that the records of events that define the familiar objective past are inscribed in many distinct systems, e.g., subsystems of the environment, and are accessible locally in space and time to observers. We identify histories that are not just consistent but redundantly consistent using the partial-trace condition introduced by Finkelstein as a bridge between histories and decoherence. The existence of redundant records is a sufficient condition for redundant consistency. It selects, from the multitude of the alternative sets of consistent histories, a small subset endowed with redundant records characteristic of the objective classical past. Furthermore, the information about an objective history of the past is then simultaneously within reach of many, who can independently reconstruct it and arrive at compatible conclusions in the present.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Energy and Performance Benchmarking of a Domain Wall-Magnetic Tunnel Junction Multibit Adder

The domain wall (DW)-magnetic tunnel junction (MTJ) device implements universal Boolean logic in a manner that is naturally compact and cascadable. However, an evaluation of the energy efficiency of this emerging technology for standard logic applications is still lacking. In this work, we use a previously developed compact model to construct and benchmark a 32-bit adder entirely from DW-MTJ devices that communicates with DW-MTJ registers. The results of this large-scale design and simulation indicate that, while the energy cost of systems driven by spin-transfer torque (STT) domain wall motion is significantly higher than previously predicted, the same concept using spin-orbit torque (SOT) switching benefits from an improvement in the energy per operation by multiple orders of magnitude, attaining competitive energy values relative to a comparable CMOS sub-processor component. This result clarifies the path towards practical implementations of an all-magnetic processor system.

42 ENGINEERING↗
DOE OSTI2022

Synthetic genetic circuits as a means of reprogramming plant roots

We report the shape of a plant’s root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Safety Risk Reliability Model Library

SR2ML is a software package which contains a set of safety and reliability models designed to be interfaced with the INL developed RAVEN code. These models can be employed to perform both static and dynamic system risk analysis and determine risk importance of specific elements of the considered system. Two classes of reliability models have been developed; the first class includes all classical reliability models (Fault-Trees, Event-Trees, Markov models and Reliability Block Diagrams) which have been extended to deal not only with Boolean logic values but also time dependent values. The second class includes several components aging models. Models of these two classes are designed to be included in a RAVEN ensemble model to perform time dependent system reliability analysis (dynamic analysis). Similarly, these models can be interfaced with system analysis codes to determine failure time of systems and evaluate accident progression (static analysis).

Wang, Congjian↗
DOE OSTI2023

Particulate mass migration and mixing in cylindrically contained explosions

Abstract To explore particulate movement near the plasma of chemical explosions, rugged tracer particles were placed within and on the exterior of metal charges and electrically detonated. The particles were collected on/in the porous walls of plastic cylinders at diameters that correlated to the plasma width during different phases of the explosion. The particles’ positions were determined by Boolean logic analysis of their luminescent intensity. The cylinders which caught particles from the initial phases of the explosion retained placement information, while wider cylinders showed uniform mixing. These results/analysis methodology can help improve the understanding of particulate mixing in harsh environments. Graphical abstract

36 MATERIALS SCIENCE↗