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DOE OSTI2015

Development of III-Sb Quantum Dot Systems for High Efficiency Intermediate Band Solar Cells

This project aimed to develop solar cells that can help reduce cost per watt. This work focused on developing solar cells that utilize quantum dot (QD) nanomaterials to provide multijunction solar cell efficiency at the cost of single junction solar cell. We focused on a novel concept known as intermediate band solar cells (IBSC) where an additional energy band is inserted in a single solar cell to accommodate sub-bandgap photons absorption which otherwise are lost through transmission. The additional energy band can be achieved by growing QDs within a solar cell p-n junction. Though numerous studies have been conducted to develop such QD systems, very small improvements in solar energy conversion efficiency have been reported. This is mainly due to non-optimal material parameters such as band gap, band offset etc. In this work, we identified and developed a novel QD material system that meets the requirements of IBSC more closely than the current state-of-the-art technology. To achieve these goals, we focused on three important areas of solar cell design: band structure calculations of new materials, efficient device design for high efficiency, and development of new semiconductor materials. In this project, we focused on III-Sb materials as they possess a wide range of energy bandgaps from 0.2 eV to 2eV. Despite the difficulty involved in realizing these materials, we were successfully developed these materials through a systematic approach. Materials studied in this work are AlAsSb (Aluminum Arsenide Antimonide), InAlAs (Indium Aluminum Arsenide) and InAs (Indium Arsenide). InAs was used to develop QD layers within AlAsSb and InAlAs p-n junctions. As the QDs have very small volume, up to 30 QD layers been inserted into the p-n junction to enhance light absorption. These QD multi-stack devices helped in understanding the challenges associated with the development of quantum dot solar cells. The results from this work show that the quantum dot solar cells indeed improve the efficiency via sub-bandgap photon absorption but much lower than the expected theoretical efficiencies. Yet, these devices serve as a proof of concept and the results provide vital information for future IBSC work. With further understanding of the operation of intermediate band solar cells and the identification of less expensive materials can substantially improve the solar cell efficiency and drastically cut the cell cost thereby reducing the dollar/watt cost.

14 SOLAR ENERGY↗

DOE OSTI2017

Integrated Predictive Tools for Customizing Microstructure and Material Properties of Additively Manufactured Aerospace Components

Additive Manufacturing (AM) refers to a process by which digital three-dimensional (3-D) design data is converted to build up a component by depositing material layer-by-layer. United Technologies Corporation (UTC) is currently involved in fabrication and certification of several AM aerospace structural components made from aerospace materials. This is accomplished by using optimized process parameters determined through numerous design-of-experiments (DOE)-based studies. Certification of these components is broadly recognized as a significant challenge, with long lead times, very expensive new product development cycles and very high energy consumption. Because of these challenges, United Technologies Research Center (UTRC), together with UTC business units have been developing and validating an advanced physics-based process model. The specific goal is to develop a physics-based framework of an AM process and reliably predict fatigue properties of built-up structures as based on detailed solidification microstructures. Microstructures are predicted using process control parameters including energy source power, scan velocity, deposition pattern, and powder properties. The multi-scale multi-physics model requires solution and coupling of governing physics that will allow prediction of the thermal field and enable solution at the microstructural scale. The state-of-the-art approach to solve these problems requires a huge computational framework and this kind of resource is only available within academia and national laboratories. The project utilized the parallel phase-fields codes at Oak Ridge National Laboratory (ORNL) and Lawrence Livermore National Laboratory (LLNL), along with the high-performance computing (HPC) capabilities existing at the two labs to demonstrate the simulation of multiple dendrite growth in threedimensions (3-D). The LLNL code AMPE was used to implement the UTRC phase field model that was previously developed for a model binary alloy, and the simulation results were compared against the UTRC simulation results, followed by extension of the UTRC model to simulate multiple dendrite growth in 3-D. The ORNL MEUMAPPS code was used to simulate dendritic growth in a model ternary alloy with the same equilibrium solidification range as the Ni-base alloy 718 using realistic model parameters, including thermodynamic integration with a Calphad based model for the ternary alloy. Implementation of the UTRC model in AMPE met with several numerical and parametric issues that were resolved and good comparison between the simulation results obtained by the two codes was demonstrated for two dimensional (2-D) dendrites. 3-D dendrite growth was then demonstrated with the AMPE code using nondimensional parameters obtained in 2-D simulations. Multiple dendrite growth in 2-D and 3-D were demonstrated using ORNL’s MEUMAPPS code using simple thermal boundary conditions. MEUMAPPS was then modified to incorporate the complex, time-dependent thermal boundary conditions obtained by UTRC’s thermal modeling of single track AM experiments to drive the phase field simulations. The results were in good agreement with UTRC’s experimental measurements.

36 MATERIALS SCIENCE↗

DOE OSTI2018

GoldSim® Aquifer Model Calibration and Plume Interaction

The E-Area Low-Level Waste Facility (ELLWF) Probabilistic Aquifer Model (PAM) utilizes GoldSim ® Monte Carlo simulation software (GTG, 2017) to evaluate the transport of a tracer species as it travels from the water table below the disposal unit footprint, through the aquifer, to the Point of Assessment (POA) at the 100-meter boundary. This report documents the development and calibration of PAM as well as the implementation of plume interaction. PAM is a key component of the effort to include uncertainty quantification and sensitivity analysis (UQSA) in the next revision of the E-Area Performance Assessment (PA), considering recommendations from the 2015 PA strategic planning team outlined by Butcher and Phifer (2016). The Aquifer Model and associated optimized geometric parameters will be implemented in the future GoldSim® (GS) system model that will simulate subsurface flow and radionuclide transport from the ground surface to the 100-meter POA.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

Lattice Element Error Solver for Modeling of Accelerators, Storage Ring, Transport Systems, and Insertion Devices

The goals of CRADA 350 were achieved in this Phase I SBIR work. Specifically, a software environment was developed which included a nonlinear solver, OASIS. During the Phase I work, we applied the algorithm to a number of nonlinear-solver benchmark problems, including SLAC accelerator problems. By searching over only two optimization-control parameters, this Phase I work has enabled the development of a systematic procedure to facilitate the finding of a “best-guessed” global minimum solution for various types of non-linear problems with different size and complexity. This set of rules was codified and led to a versatile nonlinear program, IMIGO.

43 PARTICLE ACCELERATORS↗

DOE OSTI2019

PRIMA-X - Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing

The PRIMA-X (Performance Retargeting of Instrumentation, Measurement, and Analysis Technologies for Exascale Computing) project is the successor of the DOE PRIMA (Performance Refactoring of Instrumentation, Measurement, and Analysis Technologies for Petascale Computing) project, which addressed the challenge of creating a core measurement infrastructure that would serve as a common platform for both integrating leading parallel performance systems (notably TAU and Scalasca) and developing next-generation scalable performance tools. The PRIMA-X project shifts the focus away from refactorization of robust performance tools towards a re-targeting of the parallel performance measurement and analysis architecture for extreme scales. The massive concurrency, asynchronous execution dynamics, hardware heterogeneity, and multi-objective prerequisites (performance, power, resilience) that identify exascale systems introduce fundamental constraints on the ability to carry forward existing performance methodologies. In particular, there must be a deemphasis of per-thread observation techniques to significantly reduce the otherwise unsustainable flood of redundant performance data. Instead, it will be necessary to assimilate multi-level resource observations into macroscopic performance views, from which resilient performance metrics can be attributed to the computational features of the application. This requires a scalable framework for node-level and system-wide monitoring and runtime analyses of dynamic performance information. Also, the interest in optimizing parallelism parameters with respect to performance and energy drives the integration of tool capabilities in the exascale environment further. Initially, PRIMA-X was a collaborative project between the University of Oregon (lead institution) and the German Research School for Simulation Sciences (GRS). Because Prof. Wolf, the PI at GRS, accepted a position as full professor at Technische Universitaet Darmstadt (TU Darmstadt) starting February 1st, 2015, the work of GRS was continued at TU Darmstadt. This report covers the work at TU Darmstadt after the transition. The first main accomplishment of TU Darmstadt is the development of different techniques to aggregate performance data on the level of threads. TU Darmstadt evaluated different schemes designed at GRS during the first phase of this project and integrated them into Score-P, a widely used performance measurement framework for HPC applications. The second main accomplishment is a substantial increase of Score-P’s scalability, achieved by improving its internal representation of the underlying system. Third, we extended our performance-modeling tool Extra-P to automatically create models with more than one input parameter (e.g., process count and input size), which was previously impossible. These models allow the performance behavior of an application to be extrapolated to larger machines. Specific applications of the new multi-parameter capability realized in this project include modeling the isoefficiency function of task-based applications and a novel co-design methodology. Further extensions of Extra-P comprise online modeling functionality, automatic refinement of the model search space, and segmented performance modeling. Further contributions include new locality metrics for both shared- and distributed-memory applications, a new way of measuring the impact of inter-application inference on the execution time of an application, and finally an automatic method that selects appropriate OpenMP constructs for the parallelization of sequential code and classifies the affected variables based on their sharing semantics.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Design and Development of a Custom Laser Powder Bed Fusion System

Additive manufacturing (AM) has gained great momentum both in industrial and research applications. Due to the ability to create custom and complex parts directly from a computer-aided design (CAD) file, AM is becoming a more reliable and efficient means to fabricate components. While being implemented throughout the aerospace, medical, automotive, and energy industries, the development of metal AM is still ongoing and presents many unique scientific challenges. For example, in laser powder bed fusion (PBF), intense localized heating of metal powder followed by rapid cooling leads to residual stresses and unique microstructures within a build. This may lead to cracking and a decrease in mechanical performance. In-situ diagnostics enable the laser-material interaction to be monitored as it occurs in order to optimize process parameters, and can be leveraged to develop tailored materials with specific microstructures that are more conducive for the complex thermal patterns encountered during laser PBF. Unfortunately, most commercial laser PBF machines are not suitable for research applications due to their large size, lack of diagnostics, and black box operation. A smaller system is better suited for using smaller quantities of powder to develop new tailored materials for AM, and a custom, modular design permits greater flexibility for incorporating in-situ diagnostics. Therefore, this project consisted of the design and construction of a custom, small scale, modular PBF system.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Effects of Pore Size on Na/Ca Ion Selectivity Using Flow Through Electrode Capacitive Deionization

In flow through electrode capacitive deionization (fte-CDI), low salinity brackish water flows through two porous carbon electrodes. When an electrical potential difference is applied over the electrodes, ions migrate towards micropores, cleaning the water. Ion selectivity can be controlled by taking advantage of charge and ionic radius differences as well as the applied potential and pore size of the electrodes. The research outlined in this paper consists primarily of running fte-CDI cells with electrodes of varying pore size distributions to experimentally determine the parameters for optimal total salt removal and sodium/calcium ion selectivity. Five fte-CDI cells of different activation were fabricated using microporous hierarchical carbon aerogel materials (HCAMs) as electrodes. For each cell, cyclic voltammetry using 20 mM NaCl solution and 10 mM CaCl2 solution was performed at a scan rate of 0.5, 0.75, and 1 mV/s with a potential window from -0.8 V to +0.8 V. The same pure salts were desalinated in hourly charge/discharge cycles at ±1 V. A mixture of 5 mM NaCl and 2.5 mM CaCl2 was desalinated at 0.6, 0.8, 1.0, and 1.2 V. The collected charge and discharge streams were analyzed with ion chromatography (IC). The IC data for the two least activated cells showed minimal calcium adsorption compared to sodium. All cells adsorbed sodium, regardless of activation, while only highly activated cells removed calcium. This data indicates a tradeoff between more total salt removed at high voltages and selectivity of sodium over calcium at low voltages. Future research with nitrogen porosimetry could provide a quantitative value for the optimal pore size distribution.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Spatial Atomic Layer Deposition to Scale Manufacturing of Robust Catalysts for Biomass Conversion Applications: Cooperative Research and Development Final Report, CRADA Number CRD-17-715

This CRADA will facilitate technology maturation for NREL-developed ALD-coated catalyst materials that are tailored for durability during harsh biomass conversion chemistries. This project will address optimizing process parameters for scale-up of Al2O3 ALD-coated catalysts, demonstrating ALD-coated catalyst performance for muconic acid hydrogenation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

DOE OSTI2020

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

Phase 1 research identified a two-step refining train, acid leaching of AMD precipitate feed followed by solvent extraction (SX), to produce a 2% TREE product. For the Phase 2 bench scale system, the objective was to get the acid leaching step to operate in batch-mode with sufficient storage capacity to feed an aqueous, enriched REE liquor to a pilot SX plant operating in continuous-mode at a feed rate capable of producing 3 g/hr 2% TREE. Important process variables included feed rate, extractant makeup, flowsheet configuration, and stripping conditions. Operating parameters were optimized through a feedback-capable SCADA system configured for the SX bench scale plant. These conditions were met and exceeded. TREE grades approaching 90% were produced while our Techno-Economic Assessment indicated highly favorable economic returns. The project led to the design of a pilot facility for producing roughly 500 kg/TREE/year. That plant is now in the procurement stage with constructed expected to begin in late 2020.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Recovery of Rare Earth Elements (REEs) from Coal Mine Drainage, Phase 2

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Advanced Data Preparation Module for Metals Additive Manufacturing

The Mission: Provide the LLNL metals additive manufacturing (AM) team with an advanced AM data preparation module that will analyze and optimize build parameters for metal AM parts fabricated in a laser powder bed fusion (LPBF) system in order increase the first pass success ratio.

42 ENGINEERING↗

DOE OSTI2021

Microfluidic Liquid-Liquid Extraction Chip with Integrated Raman Sensors (Phase I and Phase II Final Report)

As demand for electricity continues to increase worldwide, the world’s nuclear power generating capacity will continue to grow. Nuclear power is the most environmentally benign way of producing electricity on a large scale. The long-term successful use of nuclear power, however, is critically dependent upon adequate and safe processing and disposal of spent nuclear fuels. A very important feature of nuclear energy is that spent fuels can be reprocessed to recover fissile and fertile materials that can then be used as fresh fuel for nuclear power plants. The DOE-NE Fuel Cycle Research and Development (FCR&D) is currently developing nuclear material reprocessing technologies. In a typical nuclear fuel reprocessing system, centrifugal contactors are used as liquid-liquid extraction devices where two immiscible liquids are mixed at high speeds using a rotor, which creates a fine dispersion of droplets of organic phase in an aqueous phase that contains the analyte. Understanding the extraction efficiency at these contactors through modeling and simulation is important in the development of reprocessing technologies and the optimization of current technologies such as the PUREX process. The outcome of this program will be a liquid-liquid microfluidic flow cell chip with embedded spectroscopic sensors for the analysis of extracted analytes. This device will be useful in the optimization of new fuel reprocessing schemes as well as existing reprocessing processes by providing a microfluidic modeling platform to optimize extraction parameters. The Phase I and Phase II work developed a microfluidic chip design that allows integration of Raman and absorption fiber optic probes and successfully demonstrated the feasibility of using Raman and absorption probes to detect key analytes that partition into the aqueous and organic phases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Surface Roughness Calculations of Additively Manufactured Cylinders via X-Ray Computed Tomography

X-ray Computed Tomography (X-ray CT) is an analytical technique used in materials science to non–destructively characterize features in variety of materials like polymers, metals, composites, and explosives. It also has the capability of imaging additively manufactured, machined and assembled parts and processes. The non-destructive imaging allows for the analysis of features (voids and cracks), which give a fundamental understanding of material characteristics. Additionally, X-ray CT can obtain accurate measurements of dimensional and topographic variations as a result of different stimuli, and assess accuracy of material production. This study will focus on parts manufactured via metal additive manufacturing (AM). Although, AM produces parts faster and easier, the printing process can produce defects (pores and surface roughness) that undermine the part’s mechanical properties. The analysis of 3D printed objects has a strength in analysis in that the material has an STL file from which the item was printed, which is not available in many manufactured materials (i.e. foams) due to stochastic structures. For this study, the print accuracy of several 3D printed cylinders will be assessed via X-ray CT to determine optimal printing parameters for parts with less defects and stronger mechanical properties. This will be accomplished by having the original STL file serve as the baseline surface to compute difference in the CT rendering to calculate surface roughness for each cylinders.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Expedited Real Time Processing for the NETL HYPER Cyber-Physical System (Final Report)

The primary objective of the proposed project was to provide the National Energy Technology Laboratory’s Hybrid Performance (Hyper) Facility the needed numerical methods algorithm(s), software development and implementation support to enact real time cyber-physical systems (CPSs) that simulate process dynamics on the order of five milliseconds or smaller. The proposed paths forward comprised three distinct approaches to hasten transient simulations. They fell under the numerical methods categorical options of: 1) optimizing key parameters within the facility’s pre-existing real time processing scheme; 2) introducing an “informed” processing approach wherein a priori computations expedite real time attempts; and 3) implementing alternatives to the employed explicit-implicit blended finite difference (spatio-temporal) approach. Each of these three classes were proposed independently as options for improvement, yet in some cases one class of approach could have complemented another.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Modeling the cooldown of cryocooler conduction-cooled devices

Cryocooler conduction cooled devices can experience significant cooldown time due to lower available cooling capacity compares to convection cooled devices. Therefore, the cooldown time is an important design parameter for conduction cooled devices. This article introduces a framework developed in Python for calculating the cooldown profiles and cooldown time of cryocooler conduction-cooled devices such as superconducting magnets and accelerator cavities. The cooldown time estimation problem is essentially a system of ordinary first-order differential equations comprising the material properties (temperature dependent thermal conductivity and specific heat capacity) of the components intertwined with the prevailing heat transfer channels (conduction, radiation, and heat flow across pressed contacts) and the cryocooler capacity. The formulation of this ODE system is first presented. This ODE system is then solved using the in-built Python library odeint. A case study is presented comprising a small cryocooler conduction-cooled copper stabilized niobium-titanium magnet. The case study is supplemented with the Python script enabling the reader to simply tweak the device design parameters and optimize the design from the point of view of slow/fast cooldown.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Enhanced Catalyst Durability for the Oxidative Production of Biobased Chemicals (Cooperative Research and Development Final Report)

This CRADA will facilitate technology maturation for NREL-developed atomic layer deposition (ALD) coated catalyst materials that are tailored for durability during the oxidative production of biobased chemicals. This project will address optimizing process parameters for scaling aluminum oxide (Al 2 O 3 ) ALD coated catalysts, demonstrating ALD coated catalyst performance for biomass oxidation, and validating economic models that project significant cost benefits for ALD-enhanced catalytic processes. This work will strengthen private-public partnerships in the area of advanced catalyst manufacturing for energy-related technology. Critical information will be collected to elevate the Technology Readiness Level and increase our competitiveness for cooperative R&D agreements and licensing. Success of this work will be crosscutting as it can facilitate advanced catalyst development for both renewable and conventional processes.

09 BIOMASS FUELS↗

DOE OSTI2023

Large Area Picosecond PhotoDetector (LAPPD) definitive tests

The goal of the project was to determine the optimal functional parameters for a new LAPPD, determine the cloud charge radius and test for gain variation due to pore sharing. Also, cosmics tests with C4F8 heavy gas of the new LAPPD were planned.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Machine Learning Software for Cylindrical Battery Design and Performance Prediction

A software that delivers optimal design parameters and performance predictions for cylindrical cells, which can range in size from micro batteries to EV batteries, is developed. The Cylindrical battery design V1.0 is comprised of three types of cylindrical batteries, Micro battery (Primary), Micro battery (Secondary) and 18650/21700/xxxxx cylindrical battery. The software was developed in MATLAB. The software has the capability to output the cell design with the capacity ranges from several mAh to several million Ah. The software utilizes machine learning and includes a graphical user interface to enable rapid prototyping to accelerate energy storage research, development, and manufacturing.

25 ENERGY STORAGE↗