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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

PyOECP: A flexible open-source software for the measurement and modeling of the dielectric spectrum from the reflection coefficient

We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to complex permittivity is performed based on two different models, including the capacitance model and the antenna model. The software library contains dielectric spectra of common reference liquids, which can be used to transform the reflection coefficient into the dielectric spectra. Several Python routines that are commonly employed (e.g., SciPy and NumPy) are only required so that the users can alter the software structure depending on their needs. The modeling algorithm exploits the Markov chain Monte Carlo method for the data regression. The discrete relaxation models can be built by a proper combination of well-known relaxation models. In addition to these models, the electrode polarization, which is a common measurement artifact for interpreting the dielectric spectra, can be incorporated in the modeling algorithm. A continuous relaxation model, which solves the Fredholm integral equation of the first kind (a mathematically ill-posed problem) is also included.

Yoon, Tae-Jun↗
DOE OSTI2022

Neural Networks for Supercapacitor Modeling

This software implements a one-dimensional model of a supercapacitor and calibrates it to experimental data. A system of coupled partial differential equation models the salt concentration and the ionic and electronic potentials. The term in the equation modeling the capacitance contains a neural network, whose parameters are optimized to fit the provided experimental data. The software is written in python using the open-source library JAX to calculate the gradients needed for the optimization.

Salazar de Troya, Miquel↗
DOE OSTI2026

Supervisory Control and Data Acquisition for Electrochemical Separation Experimentation

The Python-based program is a laboratory automation tool designed to control and monitor electrochemical systems. The tool was developed for capacitive deionization (CDI) experiments, but it can be used for any system that requires controlled voltage or current segments and multi-parameter monitoring. The program integrates hardware components to run user-defined experimental parameters, providing operational control of a programmable power supply, peristaltic pump, and data acquisition devices. Currently, the program is structured with a workflow that includes an initialization (or pre-run) phase, a main loop, and a post-experiment stabilization (or post-run) phase. The initialization phase prepares and stabilizes the cell, ensuring that the electrodes and solution reach a baseline state before the experiment begins. The main loop consists of multiple voltage segments that repeat, controlling the experiment while recording key parameters such as time, voltage, current, pH, and conductivity. Finally, the post-experiment stabilization phase allows the system to stabilize after the experiment, returning the cell and solution to equilibrium conditions before ending the sequence. The program is designed with four variations, each tailored to different experimental needs. All variations include both the initialization and post-experiment stabilization stages, which run for a set amount of time, voltage, current, and flow rate before and after the main experiment block. The main loop runs for a set number of cycles, as defined by the user input, and each cycle is composed of 2 or 4 segments. The 4 program variations are described as follows: Program 1: The main program includes 2 segments. Each segment is defined to have a set duration, flow rate, voltage, and current. This program measures conductivity, flow rate, voltage, and current. Program 2: The main program expands Program 1 to include 4 segments. Each segment has a specified duration, flow rate, voltage, and current. Like Program 1, it measures conductivity, flow rate, voltage, and current. Program 3: The main program consists of 2 segments, each defined by time, flow rate, voltage, and current. In addition to conductivity, flow rate, voltage, and current, Program 3 collects pH and temperature data through a 4-channel data acquisition device. Program 4: This program independently controls two channels of a multi-channel power supply simultaneously. While conductivity can only be measured for one cell at a time, the dual-channel control makes it possible to operate two cells simultaneously under different voltage/current conditions. The main program includes 2 segments.For each program, all measurements are automatically logged and integrated into a single Excel output file. Data are displayed in numerical format and plotted, both in real time, to track system performance. A key feature of the program is its ability to synchronize all outputs so that every measurement shares a single timestamp, ensuring accurate alignment of voltage, current, pH, conductivity, and pH data.By combining hardware control, real-time monitoring, and unified data collection, this program significantly reduces manual workload and minimizes errors, making it a reliable platform for researchers, engineers, and laboratory technicians conducting CDI experiments, among other electrochemical tests.

Valentino, Lauren [Argonne National Laboratory (AN↗
DOE OSTI2020

Benders Cut Classification via Support Vector Machines for Solving Two-Stage Stochastic Programs

In this work, we consider Benders decomposition for solving two-stage stochastic programs with complete recourse based on finite samples of the uncertain parameters. We define the Benders cuts binding at the final optimal solution or the ones significantly improving bounds over iterations as valuable cuts. We propose a learning-enhanced Benders decomposition (LearnBD) algorithm, which adds a cut classification step in each iteration to selectively generate cuts that are more likely to be valuable cuts. The LearnBD algorithm includes two phases: (i) sampling cuts and collecting information from training problems and (ii) solving testing problems with a support vector machine (SVM) cut classifier. We run the LearnBD algorithm on instances of capacitated facility location and multicommodity network design under uncertain demand. Our results show that SVM cut classifier works effectively for identifying valuable cuts, and the LearnBD algorithm reduces the total solving time of all instances for different problems with various sizes and complexities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Quantitative defect analysis in MOCVD GaN-on-GaN using cathodoluminescence

Cathodoluminescence (CL) is used as a quantitative characterization technique to probe impurities at the metal-organic chemical vapor deposition (MOCVD) grown GaN-on-GaN homoepitaxial interfaces. CL intensity contrast shows a strong correlation with the interfacial impurity concentrations. Based on the analysis of recombination mechanisms of electron beam induced non-equilibrium carriers, an analytical model is proposed to quantitatively determine the impurity concentrations from CL intensity. The extracted interfacial impurity concentrations from the analytical model show a good agreement with the compensation levels obtained from capacitance-voltage measurement, signifying the potential of CL for probing the quantitative impurity levels in GaN-on-GaN structures. This approach can also be extended to be applied in other material systems.

Chen, Zhaoying↗
DOE OSTI2020

High Dynamic Voltage Range Studies of Piezoelectric Multilayer Actuators at Low Temperatures

Piezo actuators are used for resonance control in superconducting linacs. In high accelerating gradients linacs, such as those operated in a pulsed mode, the piezos require a large operating voltage. This is due to the Lorentz forced detuning which causes a large frequency shift and is compensated with an active piezo-tuning system. In this high dynamic voltage range the piezo is expected to warm up drastically due to it being in an insulated vacuum. This study characterizes the dielectric properties (capacitance, dielectric losses), the piezo stroke (from geophone), and thermal properties such as heating. Results obtained in the temperature range of 20K to 300K will be presented and discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Vidyut3d: A Gpu Accelerated Fluid Solver for Non-Equilibrium Plasmas on Adaptive Grids

We present the numerical methods, programming methodology, verification, and performance assessment of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures, in this work. Our plasma fluid model solves the coupled conservation equations for species transport, electrostatic Poisson and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive-grid/particle management library, AMReX, and is portable over widely available vendor specific GPU architectures. We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth-order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on capacitive discharges and atmospheric pressure streamer propagation. We demonstrate the use of our solver on two 3D simulation cases: an atmospheric streamer propagation in Ar-H2 mixtures and a low pressure twin electrode radio frequency reactor. Our performance studies on three different CPU+GPU architectures indicate approximately 150-400X speed-up using AMD and NVIDIA GPUs per time step compared to a single CPU core for a 4 million cell simulation with 15 species.

Sitaraman, Hariswaran↗
DOE OSTI2017

Adsorption Equilibrium and Kinetics at Goethite-Water and Related Interfaces

This research study is an important component of a broader comprehensive project, “Geochemistry of Interfaces: From Surfaces to Interlayers to Clusters,” which sought to identify and evaluate the critical molecular phenomena at metal-oxide interfaces that control many geochemical and environmental processes. The primary goal of this research study was to better understand and predict adsorption of metal ions at mineral/water surfaces. Macroscopic data in traditional batch experiments was used to develop predictive models that characterize sorption in complex systems containing a wide range of background solution compositions. Our studies focused on systems involving alkaline earth metal (Mg 2+ , Ca 2+ , Sr 2+ , Ba 2+ ) and heavy metal (Hg 2+ , Co 2+ , Cd 2+ , Cu 2+ , Zn 2+ , Pb 2+ ) cations. The anions we selected for study included Cl - , NO 3 - , ClO 4 - , SO 4 2- , CO 3 2- and SeO 3 2- and the background electrolyte cations we examined included (Na + , K + , Rb + and Cs + ) because these represent a range of ion sizes and have varying potentials for forming ion-pairs or ternary complexes with the metal ions studied. The research led to the development of a modified titration congruency approach for estimating site densities for mineral oxides such as goethite. The CD-MUSIC version of the surface complexation modeling approach was applied to potentiometric titration data and macroscopic adsorption data for single-solute heavy metals, oxyanions, alkaline earth metals and background electrolytes over a range of pH and ionic strength. The model was capable of predicting sorption in bi-solute systems containing multiple cations, cations and oxyanions, and transition metal cations and alkaline earth metal ions. Incorporation of ternary complexes was required for modeling Pb(II)-Se(IV) and Cd(II)-Se(IV) systems. -Both crystal face contributions and capacitance values were shown to be sensitive to varying specific surface area but were successfully accounted for in the modeling strategy. The insights gained from the macroscopic, spectroscopic and CD-MUSIC modeling developed in this study can be used to guide the implementation of less complex models which may be more applicable to field conditions. The findings of this research suggest that surface complexation models can be used as a predictive tool for fate and transport modeling of metal ions and oxyanions in fresh and saline systems typical of energy production waters and wastewaters.

42 ENGINEERING↗
DOE OSTI2017

Tunable Impedance Spectroscopy Sensors via Selective Nanoporous Materials.

Impedance spectroscopy was leveraged to directly detect the sorption of I 2 by selective adsorption into nanoporous metal organic frameworks (MOF). Films of three different types of MOF frameworks, respectively, were drop cast onto platinum interdigitated electrodes, dried, and exposed to gaseous I 2 at 25, 40, or 70 C. The MOF frameworks varied in topology from small pores (equivalent to I 2 diameter) to large pore frameworks. The combination of the chemistry of the framework and pore size dictated quantity and kinetics of I 2 adsorption. Air, argon, methanol, and water were found to produce minimal changes in ZIF-8 impedance. Independent of MOF framework characteristics, all resultant sensors showed high response to I 2 in air. As an example of sensor output, I 2 was readily detected at 25 C in air within 720 s of exposure, using an un-optimized sensor geometry with a small pored MOF. Further optimization of sensor geometry, decreasing MOF film thicknesses and maximizing sensor capacitance, will enable faster detection of trace I 2 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Daylighting Digital Dimmer SBIR Phase 2 Final Report

The primary focus of the Phase II Development is the implementation of two key technologies, Task To Wall (TTW) Control, and Wand Gesture light dimming control into an easy to use remote for SSL light control, the MoJo Remote. The MoJo Remote product family includes a battery powered wireless remote, a WiFi gateway as well as Mobile Applications for iOS and Android. Specific accomplishments during the second reporting period include: 1. Finalization and implementation of MoJo Remote Accelerometer and capacitive-touch based UI/UX, referred to as the Wand Gesture UI. 2. Issuance of Patent for Wand Gesture UI. 3. Industrial and Mechanical Design for MoJo Remote and MoJo Gateway. 4. Task To Wall implementation and testing in MoJo Remote. 5. Zooming User Interface (ZUI) for the Mobile App implemented on both iOS and Andriod. 6. iOS Mobile app developed to beta level functionality. 7. Initial Development of the Android Mobile Application. 8. Closed loop color control at task (demonstrated at 2016 SSL R&D Workshop). 9. Task To Wall extended to Color Control, working in simulation. 10. Beta testing begun in Late 2017/Early 2018. The MoJo Remote integrates the Patented TTW Control and the Wand Gesture innovative User Interface, and is currently in Beta testing and on the path to commercialization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Advanced Models for Nondestructive Evaluation of Aging Nuclear Power Plant Cables

Background: Nuclear power plant (NPP) cables must function correctly for proper power supply and control of the nuclear reactor. This is especially important for public and environmental safety at critical times such as during reactor shut-down following loss of coolant. Over extended periods of service, the cable insulation and jacket polymer materials suffer from degradation due to exposure to environmental stressors such as heat and ionizing radiation. The focus of this project has been the development of detailed descriptions of the way in which insulation polymers degrade, from a materials science perspective, and the development of new electrical techniques to monitor cable polymer condition nondestructively. Objectives: The objectives of this project have been to i) perform detailed characterization experiments upon cable insulation polymers that have experienced thermal and radiation exposure mimicking that received during NPP operation, including the exploration of novel cable nondestructive evaluation methods; capacitive, THz and infrared methods; ii) identify the most sensitive indicators of aging in these materials, and iii) develop advanced, validated models describing microstructural and chemical changes that are observed in cable insulation polymers due to thermal and radiation exposure. Methods: Accelerated aging was performed on the two most common United States NPP cable insulation polymers (cross-linked polyethylene (XLPE) and ethylene propylene rubber (EPR)) under various conditions of elevated temperature and gamma radiation dose. Aging mechanisms were elucidated through extensive thermal, mechanical and microscopic characterization of the aged samples, and materials modeling. Dielectric and IR spectra were measured on pristine and aged samples. Data was analyzed statistically, via multiple linear regression, partial least squares and probabilistic neural network approaches. Impact: Extant cable monitoring techniques do not deal successfully with all polymer types. This research has laid a foundation upon which new electrical nondestructive test methods for cable polymer condition monitoring may be developed, hence launching the development of new test methods for cable insulation monitoring based on measuring electrical rather than mechanical parameters. Collaboration: This project has benefitted from collaboration between experts in materials science and engineering, materials modeling, electrical engineering, and nondestructive evaluation. The majority of the characterization measurements were carried out at Iowa State University. Materials modeling was carried out primarily at Washington State University. Irradiation of samples took place at Pacific Northwest National Laboratory (PNNL), where a student intern from Iowa State was hosted for one summer, setting up the aging experiments. A research student from the University of Bologna, Italy, joined the project for their thesis research at Iowa State University with samples provided by PNNL. The project benefitted from regular involvement of senior engineers in US-based industry partners. Project investigators presented findings at various national and international conferences and workshops.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

γ-Valerolactone-Extracted Lignin to Porous Carbon Materials

Synthesis of multiphase materials from lignin, a biorefinery coproduct, offers limited success due to the inherent difficulty in controlling dispersion of these renewable hyperbranched macromolecules in the product or its intermediates. Effective use of the chemically reactive functionalities in lignin, however, enables tuning morphologies of the materials. Here, we bind a lignin oligomer with a rubbery macromolecule followed by thermal crosslinking to form a carbon precursor with phase contrasted morphology at submicron scale. The solvent-free mixing is conducted in a high-shear melt-mixer. With this, the carbon precursor is further modified with potassium hydroxide for a single-step carbonization to yield activated carbon with tunable pore structure. A typical precursor with 90% lignin yields porous carbon with 2120 m 2 /g surface area and a supercapacitor with 215 F/g capacitance. The results show a simple route towards manufacturing carbon-based energy-storage materials, eliminating the need for conventional template-synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2018

MilliKelvin HEMT Amplifiers for Low Noise High Bandwidth Measurement of Quantum Devices

We demonstrate ultra-low power cryogenic high electron mobility transistor (HEMT) amplifiers for measurement of quantum devices. The low power consumption (few uWs) allows the amplifier to be located near the device, at the coldest cryostat stage (typically less than 100 mK). Such placement minimizes parasitic capacitance and reduces the impact of environmental noise (e.g. triboelectric noise in cabling), allowing for improvements in measurement gain, bandwidth and noise. We use custom high electron mobility transistors (HEMTs) in GaAs/A1GaAs heterostructures. These HEMTs are known to have excellent performance specifically at mK temperatures, with electron mobilities that can exceed 10 6 cm 2 /Vs, allowing for large gain with low power consumption. Low temperature measurements of custom HEMT amplifiers at T = 4 K show a current sensitivity of 50 pA at 1 MHz bandwidth for 5 mW power dissipation, which is an improvement upon performance of amplifiers using off-the-shelf HEMTs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Advanced Control Architecture and Sensor Information Development for Process Automation, Optimization, and Imaging of Chemical Looping Systems

The Syngas Chemical Looping (SCL) process developed at The Ohio State University (OSU) uses an iron-based oxygen carrier to convert syngas into high-purity hydrogen while simultaneously capturing carbon dioxide that is readily sequestrable. A 25 kWth sub-pilot unit was successfully demonstrated multiple times on the OSU Clean Coal Research Facility, and a 250 kWth – 3 MWth pilot demonstration unit has been designed and constructed at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The focus of this project is to develop multiple technologies to automate the startup and shutdown of chemical looping system. Success of this project will propel the advanced carbon capture method toward commercialization, hence be disruptive to the fossil fuel and power industries. Advanced process automation control architecture and imaging and optimization sensor software were developed for OSU chemical looping process. A high-level controller (HLC) consisting of decision-making and controller-selection logic integrated with sliding mode controllers (SMCs) were developed to perform chemical looping process startup and shutdown. Babcock & Wilcox Power Generation Group’s FocalPoint Optimization System was implemented to optimize the process operating conditions. The process automation controller and optimization information were realized and tested on OSU’s existing sub-pilot chemical looping test unit under atmospheric condition. The implemented control architecture was able to perform the complete process procedure from startup, steady-state reaction operation to shutdown with minimal operator intervention. The controller was also implemented on the pressurized syngas chemical looping (SCL) pilot test unit constructed at the National Carbon Capture Center (NCCC), demonstrating its pressure control capability with a designed transient state trajectory. An electrical capacitance volume tomography (ECVT) sensor device and its software were developed to image the packed moving bed and slugging fluidized bed of oxygen carriers in chemical looping systems at elevated temperatures. The ECVT device constructed was capable of tracking the subtle voidage variance along the moving bed axis as a feature for directly measuring the oxygen carrier particles’ linear velocity. Also, the high temperature ECVT device was used to study the fluidization characteristics of Geldart Group D particles.

08 HYDROGEN↗
DOE OSTI2018

Hole Spin Qubits in Germanium

Holes in germanium-rich heterostructures provide a compelling alternative for achieving spin based qubits compared to traditional approaches such as electrons in silicon. In this project, we addressed the question of whether holes in Ge/SiGe quantum wells can be confined into laterally defined quantum dots and made into qubits. Through this effort, we successfully fabricated and operated single-metal-layer quantum dot devices in Ge/SiGe in multiple devices. For single quantum dots, we measured the capacitances of the quantum dot to the surface electrodes and find that they reasonably compare to expected values based on the electrode dimensions, suggested that we have formed a lithographic quantum dot. We also compare the results to detailed self-consistent calculations of the expected potential. Finally, we demonstrate, for the first time, a double quantum dot in the Ge/SiGe material system.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Improving Land-Surface Modeling of Evapotranspiration Processes in Tropical Forests (Final Report)

Land surface models are used to represent terrestrial processes that shape global climate; examples of these processes include evaporation, plant water use, and photosynthesis. While much progress has been made to improve and refine these models, some hydrological processes are not well captured, which hinders our ability to understand land-atmosphere interactions and ultimately to predict impacts of climate change on water resources. The inadequate representation of evapotranspiration may partly explain why global climate models do not match observed precipitation patterns. Multiple factors contribute to this problem. In moist tropical regions, high humidity, leaf wetness, and cloud cover combine to suppress forest water use and possibly reduce forest growth in ways that are poorly understood. Mountainous areas pose additional difficulties, as standard modeling and measurement techniques are not readily applied in rough terrain. In this project, we aimed to improve our understanding and modeling of fluxes of water vapor and carbon dioxide to and from tropical forests. To do this, we collected a suite of data from the mountainous rainforest surrounding the Texas A&M Soltis Center in San Ramon, Costa Rica. From 2014 to 2018, a suite of variables were measured, including: in-canopy profiles of water vapor, carbon dioxide, temperature, light, and leaf wetness; transpiration, evapotranspiration, carbon flux, and soil respiration; and local weather conditions. Leaf-scale measurements were used to find photosynthesis rates and derive their parameters. Using this data set, we were able to better quantify the relationships between assimilation and transpiration and their main drivers in tropical forests. These variables were namely available light, vapor pressure deficit, and leaf wetness, but not soil moisture, which exerted no detectable control. We also showed the vertical variability in canopy microclimates and how neglecting forest layers in models may misrepresent overall fluxes. The data were then used to test and refine evapotranspiration and energy budget formulations in the Community Land Model. Fluxes and energy budget components were compared to simulated values from CLM4.5 and CLM.5. The biggest discrepancies arose from hillslope shading effects, particularly mismatches in afternoon carbon fluxes, with notable differences in transpiration rates and sap flux due to capacitance in large trees. Secondary, but still significant issues included unrealistic leaf wetness and leaf drying rates, as well as air and vegetation temperatures, both of which were likely linked to CLM’s formulations controlling wet leaf and sunlit/shaded leaf fractions. Modeling multiple layers in the canopy via the newly released CLM-ml and making adjustments to existing parameters both show promise in resolving these issues. In total, the project has produced 5 peer-reviewed articles, 24 presentations, 2 theses, 4 public outreach items, and 4 publically available datasets, to date. Additional products are expected pending the completion of an additional thesis. Data has also been shared with several collaborative networks, including PHENOCAM and SAPFLUXNET.

54 ENVIRONMENTAL SCIENCES↗