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At least 289 records · Page 16

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DOE OSTI2019

Heterogeneous Activation, Local Structure, and Softness in Supercooled Colloidal Liquids

We experimentally characterize heterogeneous nonexponential relaxation in bidisperse supercooled colloidal liquids utilizing a recent concept called “softness”. Particle trajectory and structure data enable classification of particles into subgroups with different local environments and propensities to hop. We determine residence times t R between particle hops and show that t R derived from particles in the same softness subgroup are exponentially distributed. Using the mean residence time t¯ R for each softness subgroup, and a Kramers’ reaction rate model, we estimate the activation energy barriers E b for particle hops, and show that both t¯ R and E b are monotonic functions of softness. Lastly, we derive information about the combinations of large and small particle neighbors that determine particle softness, and we explicitly show that multiple exponential relaxation channels in the supercooled liquid give rise to its nonexponential behavior.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Designing and Evaluating Redundancy-Based Soft-Error Masking on a Continuum of Energy versus Robustness

Near-threshold computing is an effective strategy to reduce the power dissipation of deeply-scaled CMOS logic circuits. However, near-threshold strategies exacerbate the impact of delay variations on device performance and increase the susceptibility to soft errors due to narrow voltage margins. The objective of this work is to develop and assess design approaches that leverage tradeoffs between performance and the resilience of fault masking coverage for various soft-error mitigation techniques. The primary insight from this work is identification of redundancy-based hardening techniques that can deliver increased benefits in terms of the fault coverage energy ratio (FCER) for the leveraged tradeoffs within iso-energy constraints at near-threshold voltage (NTV). Simulation results demonstrate that temporal redundancy approaches offer favorable tradeoffs in terms of FCER. They exhibit reduced impact on performance variations and achieve extensive soft fault masking, therefore improving the system robustness within acceptable delay constraints. Meanwhile, it is shown that a hybrid redundancy approach can be used to protect a low-power system to maintain throughput while tolerating soft errors. We demonstrate how the FCER metric can be used as an optimization parameter to guide circuit synthesis to meet performance and robustness goals. Lastly, the impact of design diversity on spatial and hybrid redundancy at NTV is assessed in terms of FCER and delay variation to form overall recommendations regarding soft-error mitigation at NTV.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Integration of Soft Data Into Geostatistical Simulation of Categorical Variables

Uncertain or indirect “soft” data, such as geologic interpretation, driller’s logs, geophysical logs or imaging, offer potential constraints or “soft conditioning” to stochastic models of discrete categorical subsurface variables in hydrogeology such as hydrofacies. Previous bivariate geostatistical simulation algorithms have not fully addressed the impact of data uncertainty in formulation of the (co) kriging equations and the objective function in simulated annealing (or quenching). This paper introduces the geostatistical simulation code tsim-s, which accounts for categorical data uncertainty through a data “hardness” parameter. In generating geostatistical realizations with tsim-s, the uncertainty inherent to soft conditioning is factored into both 1) the data declustering and spatial correlation functions in cokriging and 2) the acceptance probability for change of category in simulated quenching. The degree or sensitivity to which soft data conditions a realization as a function of hardness can be quantified by mapping category probabilities derived from multiple realizations. In addition to point or borehole data, arrays of data (e.g., as derived from a depth-dependency function, probability map, or “prior realization”) can be used as soft conditioning. The tsim-s algorithm provides a theoretically sound and general framework for integrating datasets of variable location, resolution, and uncertainty into geostatistical simulation of categorical variables. A practical example shows how tsim-s is capable of generating a large-scale three-dimensional simulation including curvilinear features.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Embedded Fluidic Sensing and Control with Soft Open‐Cell Foams

Abstract The synthesis of soft matter intelligence with circuit‐driven logic has enabled a new class of robots that perform complex tasks or conform to specialized form factors in unique ways that cannot be realized through conventional designs. Translating this hybrid approach to fluidic systems, the present work addresses the need for sheet‐based circuit materials by leveraging the innate porosity of foam—a soft material—to develop pneumatic components that support digital logic, mixed‐signal control, and analog force sensing in wearables and soft robots. Analytical tools and experimental techniques developed in this work serve to elucidate compressible gas flow through porous sheets, and to inform the design of centimeter‐sized foam resistors with fluidic resistances on the order of 10 9 Pa s m −3 . When embedded inside soft robots and wearables, these resistors facilitate diverse functionalities spanning both sensing and control domains, including digital logic using textile logic gates, digital‐to‐analog signal conversion using ladder networks, and analog sensing of forces up to 40 N via compression‐induced changes in resistance. By combining features of both circuit‐based and materials‐based approaches, foam‐enabled fluidic circuits serve as a useful paradigm for future hybrid robotic architectures that fully embody the sensing and computing capabilities of soft fluidic materials.

Rajappan, Anoop↗

DOE OSTI2019

Conformally soft photons and gravitons

The four-dimensional S-matrix is reconsidered as a correlator on the celestial sphere at null infinity. Asymptotic particle states can be characterized by the point at which they enter or exit the celestial sphere as well as their SL(2, C) Lorentz quantum numbers: namely their conformal scaling dimension and spin h±h¯ instead of the energy and momentum. This characterization precludes the notion of a soft particle whose energy is taken to zero. We propose it should be replaced by the notion of a conformally soft particle with h = 0 or h¯ = 0. For photons we explicitly construct conformally soft SL(2, C) try on the celestial sphere. For gravity the generator of celestial conformal symmetry is constructed from a (2, 0) SL(2, C) primary wavefunction. Interestingly, BMS supertranslations are generated by a spin-one weight (3/2, 1/2) operator, which nevertheless shares holomorphic characteristics of a conformally soft operator. This is because the right hand side of its OPE with a weight (h, h¯) operator Oh,h¯ involves the shifted operator Oh+1/2,h¯+1/2. This OPE relation looks quite unusual from the celestial CFT 2 perspective but is equivalent to the leading soft graviton theorem and may usefully constrain celestial correlators in quantum gravity.