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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Stability Transition From Stable to Unstable Frictional Slip With Finite Pore Pressure

Pore fluids are ubiquitous throughout the lithosphere and are commonly invoked as the cause of induced seismicity and slow earthquakes. We perform lab experiments to address these questions for drained fault conditions and low pore pressure. We shear simulated faults at effective normal stress (σ' n ) of 20 MPa and pore pressures Pp from 1 to 4 MPa. We document the full range of lab earthquake behaviors from slow slip to elasto-dynamic rupture and show that slow slip can be explained by the slip rate dependence of the critical rheologic stiffness without dilatancy hardening or other fluid effects. Our fault permeabilities ranges from 10 –18 to 10 –17 m 2 with an initial porosity of 0.1 and estimated fluid diffusion time ≈1 s. Slow slip and quasi-dynamic fault motion may arise from high P p at higher pressures but dilatancy strengthening is not a general requirement.

58 GEOSCIENCES↗
DOE OSTI2024

The Effect of Normal Stress Oscillations on Fault Slip Behavior Near the Stability Transition From Stable to Unstable Motion

Tectonic fault zones are subject to normal stress variations with a wide range of spatio-temporal scales. Stress perturbations cover a wide range of frequencies and amplitudes from high frequency seismic waves generated by earthquakes to low frequency transients associated with solid Earth tides. These perturbations can reactivate critically stressed faults and trigger earthquakes. Here, we describe lab experiments to illuminate the physics of such changes in friction and the mechanics of earthquake triggering and fault reactivation. Friction tests were done in a double direct shear configuration for conditions near the stability transition from stable to unstable motion. We studied simulated fault gouge composed of quartz powder and conducted experiments at reference normal stress from 10 to 13.5 MPa. After shearing to steady state sliding, we applied sinusoidal normal stress oscillations of amplitude 0.5–2 MPa, and period of 0.5–50 s. We performed numerical simulations using measured values of rate and state friction (RSF) parameters to assess our data. Our results show that low frequency stress oscillations cause a Coulomb-like response of shear strength that transitions from stable slip to slow lab earthquakes as frequency increases. At the critical frequency predicted by RSF we observe periodic stick-slip behavior. Perturbations of high amplitude and short period weaken the fault, while lower amplitudes strengthen the fault. We find that a modified RSF formulation is able to accurately match our laboratory data. Our findings highlight the complex effects of stress perturbations on fault strength and the mode of fault slip.

58 GEOSCIENCES↗
DOE OSTI2015

Liquid-based gating mechanism with tunable multiphase selectivity and antifouling behaviour

Living organisms make extensive use of micro- and nanometre-sized pores as gatekeepers for controlling the movement of fluids, vapours and solids between complex environments. The ability of such pores to coordinate multiphase transport, in a highly selective and subtly triggered fashion and without clogging, has inspired interest in synthetic gated pores for applications ranging from fluid processing to 3D printing and lab-on-chip systems(1-10). But although specific gating and transport behaviours have been realized by precisely tailoring pore surface chemistries and pore geometries(6,11-17), a single system capable of controlling complex, selective multiphase transport has remained a distant prospect, and fouling is nearly inevitable(11,12). Here we introduce a gating mechanism that uses a capillary-stabilized liquid as a reversible, reconfigurable gate that fills and seals pores in the closed state, and creates a non-fouling, liquid-lined pore in the open state. Theoretical modelling and experiments demonstrate that for each transport substance, the gating threshold-the pressure needed to open the pores-can be rationally tuned over a wide pressure range. This enables us to realize in one system differential response profiles for a variety of liquids and gases, even letting liquids flow through the pore while preventing gas from escaping. These capabilities allow us to dynamically modulate gas-liquid sorting in a microfluidic flow and to separate a three-phase air-water-oil mixture, with the liquid lining ensuring sustained antifouling behaviour. Because the liquid gating strategy enables efficient long-term operation and can be applied to a variety of pore structures and membrane materials, and to micro- as well as macroscale fluid systems, we expect it to prove useful in a wide range of applications.

Hou, X↗
DOE OSTI2016

Imaging electric field dynamics with graphene optoelectronics

The use of electric fields for signalling and control in liquids is widespread, spanning bioelectric activity in cells to electrical manipulation of microstructures in lab-on-a-chip devices. However, an appropriate tool to resolve the spatio-temporal distribution of electric fields over a large dynamic range has yet to be developed. Here we present a label-free method to image local electric fields in real time and under ambient conditions. Our technique combines the unique gate-variable optical transitions of graphene with a critically coupled planar waveguide platform that enables highly sensitive detection of local electric fields with a voltage sensitivity of a few microvolts, a spatial resolution of tens of micrometres and a frequency response over tens of kilohertz. Our imaging platform enables parallel detection of electric fields over a large field of view and can be tailored to broad applications spanning lab-on-a-chip device engineering to analysis of bioelectric phenomena.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Aerosol jet printing of surface acoustic wave microfluidic devices

Abstract The addition of surface acoustic wave (SAW) technologies to microfluidics has greatly advanced lab-on-a-chip applications due to their unique and powerful attributes, including high-precision manipulation, versatility, integrability, biocompatibility, contactless nature, and rapid actuation. However, the development of SAW microfluidic devices is limited by complex and time-consuming micro/nanofabrication techniques and access to cleanroom facilities for multistep photolithography and vacuum-based processing. To simplify the fabrication of SAW microfluidic devices with customizable dimensions and functions, we utilized the additive manufacturing technique of aerosol jet printing. We successfully fabricated customized SAW microfluidic devices of varying materials, including silver nanowires, graphene, and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). To characterize and compare the acoustic actuation performance of these aerosol jet printed SAW microfluidic devices with their cleanroom-fabricated counterparts, the wave displacements and resonant frequencies of the different fabricated devices were directly measured through scanning laser Doppler vibrometry. Finally, to exhibit the capability of the aerosol jet printed devices for lab-on-a-chip applications, we successfully conducted acoustic streaming and particle concentration experiments. Overall, we demonstrated a novel solution-based, direct-write, single-step, cleanroom-free additive manufacturing technique to rapidly develop SAW microfluidic devices that shows viability for applications in the fields of biology, chemistry, engineering, and medicine.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

A browser-based tool for visualization and analysis of diffusion MRI data

Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is important, it is not always clear how to share data in a manner that allows other labs to understand and reproduce published findings. Here we report a new open source tool, AFQ-Browser, that builds an interactive website as a companion to a diffusion MRI study. Because AFQ-Browser is portable—it runs in any web-browser—it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of the dataset (anatomy, diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, aggregating data across labs, and publishing data alongside manuscripts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Contrasting geochemical and fungal controls on decomposition of lignin and soil carbon at continental scale

Lignin is an abundant and complex plant polymer that may limit litter decomposition, yet lignin is sometimes a minor constituent of soil organic carbon (SOC). Accounting for diversity in soil characteristics might reconcile this apparent contradiction. Tracking decomposition of a lignin/litter mixture and SOC across different North American mineral soils using lab and field incubations, here we show that cumulative lignin decomposition varies 18-fold among soils and is strongly correlated with bulk litter decomposition, but not SOC decomposition. Climate legacy predicts decomposition in the lab, and impacts of nitrogen availability are minor compared with geochemical and microbial properties. Lignin decomposition increases with some metals and fungal taxa, whereas SOC decomposition decreases with metals and is weakly related with fungi. Decoupling of lignin and SOC decomposition and their contrasting biogeochemical drivers indicate that lignin is not necessarily a bottleneck for SOC decomposition and can explain variable contributions of lignin to SOC among ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Autonomous phase mapping of gold nanoparticles synthesis with differentiable models of spectral shape

Autonomous experimentation–or self-driving labs–offers a systematic approach to accelerate materials discovery by integrating automated synthesis, characterization, and data-driven decision-making. We present a closed-loop workflow for the on-demand synthesis and structural characterization of colloidal gold nanoparticles, enabling direct mapping from composition to nanoscale structure. Our framework leverages differentiable models of spectral shape to address two central tasks in self-driving labs: (a) phase mapping, or identifying compositional regions with distinct structural behavior; and (b) material retrosynthesis, or optimizing compositions for target structure. Using functional data analysis, we develop a data-driven model with generative pre-training, active learning, and high-throughput experiments to predict spectral responses across composition space. We demonstrate the approach on seed-mediated growth of gold nanoparticles, showcasing its ability to extract design rules, reveal secondary interactions, and efficiently navigate morphology space. Gradient-based optimization of the models enables inverse design, making this a unified platform.

36 MATERIALS SCIENCE↗
DOE OSTI2017

WastePD, an innovative center on materials degradation

The US Department of Energy recently awarded funds to create the Center for Performance and Design of Nuclear Waste Forms and Containers (WastePD) as part of the Energy Frontier Research Center (EFRC) program. EFRCs are multi-investigator collaborations of universities, national labs and companies that “conduct fundamental research focusing on one or more “grand challenges” and use-inspired “basic research needs” identified in major strategic planning efforts by the scientific community.” The major performance parameter of nuclear waste forms is their ability to isolate the radionuclides by withstanding degradation in a repository environment over very long periods of time. So WastePD is at heart a center focused on materials degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

High temperature oxidation of corrosion resistant alloys from machine learning

Parabolic rate constants, k p , were collected from published reports and calculated from corrosion product data (sample mass gain or corrosion product thickness) and tabulated for 75 alloys exposed to temperatures between ~800 and 2000 K (~500–1700 °C; 900–3000°F). Data were collected for environments including lab air, ambient and supercritical carbon dioxide, supercritical water, and steam. Materials studied include low- and high-Cr ferritic and austenitic steels, nickel superalloys, and aluminide materials. A combination of Arrhenius analysis, simple linear regression, supervised and unsupervised machine learning methods were used to investigate the relations between composition and oxidation kinetics. The supervised machine learning techniques produced the lowest mean standard errors. The most significant elements controlling oxidation kinetics were Ni, Cr, Al, and Fe, with Mo and Co composition also found to be significant features. The activation energies produced from the machine learning analysis were in the correct distributions for the diffusion constants for the oxide scales expected to dominate in each class.

Materials Science↗
DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prediction of chronic kidney disease progression using recurrent neural network and electronic health records

Chronic kidney disease (CKD) is a progressive loss in kidney function. Early detection of patients who will progress to late-stage CKD is of paramount importance for patient care. To address this, we develop a pipeline to process longitudinal electronic heath records (EHRs) and construct recurrent neural network (RNN) models to predict CKD progression from stages II/III to stages IV/V. The RNN model generates predictions based on time-series records of patients, including repeated lab tests and other clinical variables. Our investigation reveals that using a single variable, the recorded estimated glomerular filtration rate (eGFR) over time, the RNN model achieves an average area under the receiver operating characteristic curve (AUROC) of 0.957 for predicting future CKD progression. When additional clinical variables, such as demographics, vital information, lab test results, and health behaviors, are incorporated, the average AUROC increases to 0.967. In both scenarios, the standard deviation of the AUROC across cross-validation trials is less than 0.01, indicating a stable and high prediction accuracy. Our analysis results demonstrate the proposed RNN model outperforms existing standard approaches, including static and dynamic Cox proportional hazards models, random forest, and LightGBM. The utilization of the RNN model and the time-series data of previous eGFR measurements underscores its potential as a straightforward and effective tool for assessing the clinical risk of CKD patients concerning their disease progression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Learning from existing photovoltaic technologies to identify alternative perovskite module designs

Perovskite solar cells have now become the most efficient of all multicrystalline thin film photovoltaic technologies, reaching 25.2% in 2019. This outstanding figure of merit has only been achieved on small lab-scale devices, with significantly lower performance when processed on larger more industrially relevant substrate sizes. Perovskite modules, connecting several smaller area cells together, are commonly demonstrated with a superstrate monolithic interconnection method. However, several other module designs exist and remain largely unexplored by the perovskite community. In this work, we review and highlight those alternatives and discuss their advantages and limitations. We propose that a singulated substrate-oriented module design, using metallic substrates, could provide a quicker path to seeing highly efficient, lightweight, and flexible perovskite modules on the market, while mitigating near-term technical risks. Finally, as an experimental starting-point towards this design, we demonstrate a substrate-oriented all-perovskite 2-terminal tandem with 18% efficiency.

14 SOLAR ENERGY↗
DOE OSTI2017

Trans-oceanic Remote Power Hardware-in-the-Loop: Multi-site Hardware, Integrated Controller, and Electric Network Co-simulation

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources (DERs) including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This paper describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab-lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. We demonstrate its utility by studying real-time PHIL co-simulation of coordinated solar PV firming control of two inverters connected in multiple electric distribution network models, prototypical of U.S. and Australian systems. Here, the novel trans-pacific closed-loop system simulation was conducted in real-time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Exotic Hybrid Meson Spectroscopy with the GlueX detector at Jlab

The GlueX experiment is scheduled to begin taking data in 2015. The goal is to discover evidence for the existence of exotic hybrid mesons and to map out their spectrum in the light quark sector. Recent theoretical developments using Lattice QCD predict exotic hybrid states in a mass range accessible using the newly upgraded 12GeV electron accelerator at Jefferson Lab. Hybrid mesons, and in particular exotic hybrid mesons, provide the ideal laboratory for testing QCD in the confinement regime since these mesons explicitly manifest the gluonic degrees of freedom. The experiment will use 9 GeV linearly polarized photons produced via coherent bremsstrahlung to produce the exotic hybrids. The decay products will be detected in the solenoid-based GlueX detector currently under construction at Jefferson Lab. The status of the GlueX experiment including detector parameters will be presented along with theoretical motivation for the experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Recent results on the nucleon resonance spectrum and structure from the CLAS detector

The CLAS detector at Jefferson Lab has provided the dominant part of all available worldwide data on exclusive meson electroproduction off protons in the resonance region. New results on the $\gamma_{v}pN^*$ transition amplitudes (electrocouplings) are available from analyses of the CLAS data and will be presented. Their impact on understanding of hadron structure will be discussed emphasizing the credible access to the dressed quark mass function that has been achieved for the first time by a combined analysis of the experimental results on the electromagnetic nucleon elastic and $N \rightarrow N^*$ transition form factors. We will also discuss further convincing evidences for a new baryon state $N^{\, '}(1720)3/2^+$ found in a combined analysis of charged double pion photo- and electroproduction cross sections off the protons.

Mokeev, Viktor I.↗
DOE OSTI2016

The 3H-3He Charge Radii Difference

The upcoming E12-14-009 [1] experiment at Jefferson Lab will determine the ratio of the electric form factors for the A=3 mirror nuclei 3He and 3H. The measurement will use a 1.1 GeV electron beam, a special collimator plate to allow for simultaneous optics measurements, and the low-activity tritium target being prepared for Jefferson Lab. By observing the dependence of the form factor ratio as a function of Q2 over 0.05–0.09 GeV2, the dependence of the radii extraction on the shape of the form factors is minimized. As a result, we anticipate the uncertainty of the extracted charge radii difference to be 0.03 fm, a reduction of 70% from the current measurement. Using precise measurements of the 3He charge radius from isotopic shift or μHe measurements [2–4], we can deduce the absolute 3H charge radius. The results will provide a direct comparison to recent calculations of the charge radii.

Myers, Luke S.↗
DOE OSTI2016

K-Long Facility for JLab and its Scientific Potential

Our main interest in creating a secondary high-quality KL-beam is to investigate hyperon spectroscopy through both formation and production processes. We propose to study two-body reactions induced by the KL-beam on the proton target. The experiment should measure both differential cross sections and self-analyzed polarizations of the produced Λ-, Σ-, and Ξ-hyperons using the GlueX detector at the Jefferson Lab Hall D. New data will greatly constrain partial-wave analysis and reduce modeldependent uncertainties in the extraction of strange resonance properties, providing a new benchmark for comparisons with QCD-inspired models and LQCD calculations. The measurements will span c.m. cos θ from -0.95 to 0.95 in c.m. range above W = 1490 MeV and up to 4000 MeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗