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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Recent advances in chemical recycling and upcycling of plastic waste into valuable materials, chemicals, and energy: a comprehensive review

The global plastic waste crisis has increased in severity in recent years: annual plastic production is projected to reach 500 million metric tons by 2025, and plastic waste accumulation is expected to surpass 12 billion metric tons. Despite these growing volumes, only ∼9% of plastic waste is currently recycled; the majority is either landfilled, incinerated, or mismanaged, contributing to escalating greenhouse gas emissions—from 1.7 Gt carbon dioxide equivalent (CO 2 -eq.) in 2015 to an estimated 6.5 Gt CO 2 -eq. by 2050—and physical environmental pollution. This review provides a comprehensive overview of advanced plastic upcycling strategies to address this issue and recover value from diverse plastic waste streams. Recent developments in solvent-based dissolution, chemical depolymerization, and thermochemical conversions are examined for major plastic types, including polyolefins, polycondensation polymers, and PVC. Underlying reaction pathways, catalyst designs, and processing parameters that govern product selectivity, efficiency, and conversion yields are discussed in depth. Emerging techniques such as microwave-assisted depolymerization, tandem catalysis, and co-processing approaches are highlighted for their potential to enhance efficiency under milder conditions. Emphasis is also placed on the production of high-value products such as monomers, naphtha-range hydrocarbons, and syngas, and discussion is provided on catalyst stability, contaminant removal, scalability, life cycle effects on the environment, and technoeconomic viability. Finally, the review outlines future research directions focused on catalyst innovation, integrated process design, supportive policy frameworks, and interdisciplinary collaboration. All recommendations are aimed at accelerating large-scale implementation of plastic upcycling technologies and advancing the global circular plastics economy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Magnetic resonance insights into the heterogeneous, fractal-like kinetics of chemically recyclable polymers

Moving toward a circular plastics economy is a vital aspect of global resource management. Chemical recycling of plastics ensures that high-value monomers can be recovered from depolymerized plastic waste, thus enabling circular manufacturing. However, to increase chemical recycling throughput in materials recovery facilities, the present understanding of polymer transport, diffusion, swelling, and heterogeneous deconstruction kinetics must be systematized to allow industrial-scale process design, spanning molecular to macroscopic regimes. To develop a framework for designing depolymerization processes, we examined acidolysis of circular polydiketoenamine elastomers. We used magnetic resonance to monitor spatially resolved observables in situ and then evaluated these data with a fractal method that treats nonlinear depolymerization kinetics. This approach delineated the roles played by network architecture and reaction medium on depolymerization outcomes, yielding parameters that facilitate comparisons between bulk processes. These streamlined methods to investigate polymer hydrolysis kinetics portend a general strategy for implementing chemical recycling on an industrial scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Detonator Design Guide and Knowledge Capture System [Slides]

Engineering design--good design--is a blend of engineering and science; this is especially true for of explosive detonator design. Detonators are complex components with interrelated mechanical, electrical, and chemical attributes, all of which must be balanced to achieve a robust and reliable, working whole. This design guide presents an integrated, lifecycle approach to the design process, bringing together engineering design with science, emphasizing elegance and subtlety in the design process.

42 ENGINEERING↗
DOE OSTI2023

Lighting for Health and Wellness Recommendations in Offices: A Circadian Lighting Pilot Project in Chicago, IL

In 2019 Cook County initiated a request for proposals for a pilot project aimed at designing and specifying an advanced tunable lighting system for government offices in Chicago, Illinois. The primary goal of the project was to replace the existing tubular LED (TLED) lighting system with a lighting system that supported the circadian rhythms and wellbeing their office employees. A secondary goal was to evaluate the potential impacts of the new lighting system, informing Cook County’s internal workplace design standards. Schuler Shook, a Chicago-based lighting design firm, was awarded the Circadian Lighting Pilot Project in October 2019 and invited Pacific Northwest National Laboratory (PNNL) to contribute as a research partner. Based on the initial project goals, Schuler Shook and PNNL established design objectives that would enable a human factors study in the office spaces, investigating the benefits and drawbacks of using a tunable LED lighting system to meet existing recommendations for lighting and health. The following report details the lighting design process through design development, with summaries of the relevant circadian lighting metrics, simulation tools, energy considerations, and research plan for the Circadian Lighting Pilot Project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Preliminary Chlorine Worth Study Benchmark Evaluation

The Chlorine Worth Studies (CWS) experiments with polyvinyl chloride (PVC with chemical formula (C 2 H 3 Cl) n ), chlorinated polyvinyl chloride (CPVC with chemical formula (C 9 H 11 Cl 7 ) n ), and high density polyethylene (HDPE with chemical formula (CH 2 ) n ) were a series of measurements performed at the National Criticality Experiments Research Center (NCERC). The purpose of the CWS experiments was to perform integral experiments that were highly sensitive to the thermal 35 Cl(n,γ) reaction and matched the sensitivities of aqueous chloride operations at the plutonium facility at Los Alamos National Laboratory (LANL). The CWS experiments were performed on the Planet critical assembly machine at NCERC and utilized weapons grade plutonium (WGPu) plates as fuel. The design process and design of the CWS experiment were discussed previously. This paper discusses the benchmark evaluation of the experiment, intended for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Criticality calculations were performed with MCNP version 6.3. Results presented here are preliminary, as the benchmark has not yet been submitted to the ICSBEP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Transforming the Process Industries through Electrification: Challenges and Opportunities

For the more than 70 years, the process industries have provided essential fuels and materials for global growth. Increased manufacturing production comes with substantial environmental impact. Reducing environmental impact through process electrification, carbon capture, and other emerging technologies would require large changes throughout the process industries. We review opportunities and challenges related to electrification, focusing on technical, operational, and economic considerations. Here, we conclude that electrification could completely eliminate scope 1 CO 2 emissions, increase product quality, and reduce the equipment size and cost. On the other hand, it calls for a significant expansion of power generation capacity, as well as new paradigms for process design and operations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗
DOE OSTI2022

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
DOE OSTI2021

Design and processing for high performance Li ion battery electrodes with double-layer structure

A two-layer LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathode has been designed and fabricated containing a “power layer” and “energy layer”, with corresponding porosity and particle size prescribed to each layer to achieve best utilization of electrode material (maximum integrated depth of discharge across the electrode thickness) at high applied current. The cathode showed a 17% improvement in capacity when tested in symmetric cells. When applying the design to a full cell, where both positive and negative electrodes contain power and energy layers, a 74% increase in discharge capacity at 2C was achieved compared to the cell with conventional electrodes. Furthermore, this demonstrates an avenue to increase energy and power density of lithium–ion batteries and enable fast charging capability.

25 ENERGY STORAGE↗
DOE OSTI2026

Large Scale Granulator Development Designed to Process Reclaimed Feedstock for Sustainable Additive Manufacturing Applications

This CRADA between UT-Battelle, LLC (Contractor) and re:3D Inc. (Participant) aims to develop an affordable large-scale granulator system designed to process reclaimed plastic feedstock suitable for additive manufacturing applications. The 24-month project will focus on testing, prototyping, and optimizing a shredder/granulator system. This project also focuses on the processing steps (e.g. washing and sorting) that can convert waste plastics, like discarded water bottles, into flake/granules which can be 3D printed using re:3D’s Fused Granular Fabrication (FGF) 3D printers. If successful, this could enable more localized 3D printing using recycled plastics, reducing waste and feedstock costs.

Wang, Peter [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2021

Synthesis and Processing by Design of High-Nickel Cathode Materials

The high demand of lightweight, high energy density batteries for energy storage promotes new materials discovery and development. Despite the large number of battery materials being discovered, very few of them have been commercially deployed, mostly bottlenecked by synthesis and processing – namely, making certain phases with the desired structure and properties to meet the multifaceted performance requirements. Alternative to the traditional trial and error, we present here an in situ study aided synthesis- and processing-by-design approach. With specific examples, we illustrate how to use the approach to identify reaction pathways in synthesis and processing of high-Nickel (Ni) cathode materials for next-generation lithium-ion batteries, thereby ensuring precise control of their structure, morphology, and surface properties. Furthermore, perspectives are provided on the wide applicability of the approach to solving critical issues inherent to high-Ni cathodes and the new directions and opportunities in the area.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers (Final Technical Report)

This report summarizes the carbon capture research and development conducted by The State University of New York at Buffalo (UB) and GTI Energy (GTI) for award “DE-FE0031969: Direct Air Capture Using Trapped Small Amines in Hierarchical Nanoporous Capsules on Porous Electrospun Fibers” sponsored by the U.S. Department of Energy (DOE). The objective of this project is to develop an innovative sorbent structure of trapped small amines in HNC embedded in PEF for DAC. This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An innovative sorbent structure of trapped small amines in hierarchical nanoporous capsules (HNC) embedded in porous electrospun fibers (PEF) was developed for direct air capture (DAC). This involves tailoring both sorbent and PEF materials to achieve a compact system for DAC with high capacity for CO 2 at concentrations typically available in air and at near ambient conditions. An interfacial polymerization process was developed, which utilized loaded amines inside mesoporous silica and trimesoyl chloride (TMC) dissolved in organic solvents as the precursors, to generate a polyamide (PA) coating layer on mesoporous silica and thus trap amines. Reaction conditions, including TMC concentration, organic solvents, reaction time, etc., for interfacial polymerization were optimized to effectively trap loaded amines, and cyclic heating-cooling operation was conducted to evaluate the coating quality. Larger pore volume mesoporous silica was also synthesized to increase amine loading and thus increase CO 2 capacity. The optimized sorbent material exhibited CO 2 capacity as high as 4.88 mmol/g under humid DAC conditions and negligible loss (<1%) during 10 cyclic heating-cooling operations. The optimized PA-coated sorbent also showed fast adsorption and desorption kinetics, with <20% t1/2 increase compared to uncoated sorbent. PEF fabrication conditions, including organic solvents for dissolving core and shell polymers, voltage, distance from the nozzle to the collection panel, etc. were adjusted to better incorporate HNC. After incorporating the optimized sorbent material into PEF, the structured sorbent had a CO 2 capacity of approximately 4.0 mmol/g under humid DAC conditions, with capacity loss of 0.17% per cycle and t1/2 increase less than 10%. A techno-economic analysis (TEA) for the process design for a DAC system based on our developed sorbent structure of trapped small amines in HNC embedded in PEF was conducted. The process design included process description and major equipment sizing and energy and mass balances in addition to scale-up research results and estimated capture cost. Aspen Adsorption Simulator was used to fit the experimentally measured breakthrough curves and extract equilibrium and kinetic data of the optimized sorbent. Our results indicated that for a DAC plant with CO 2 productivity of 3,000 tonne/year, the levelized cost of CO 2 capture was $\$$612/tonne, with the largest contribution of 44.33% from the fixed operation cost. Increasing CO 2 productivity, while maintaining similar fixed operation cost, is expected to significantly reduce the CO 2 capture cost. A sensitivity study was also conducted to understand the influence of total plant cost, sorbent cost, CO 2 concentration in the feed, sorbent mat lifetime, sorbent regeneration electricity, and adsorption blower pressure drop on the levelized cost of CO 2 capture, revealing a capture cost range of $\$$520-870/tonne.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mind the Gap: Building Simulation in the Architectural Design Studio

Building modelling and simulation approaches are increasingly being utilized in architectural design studios to guide and inform the design process and offer evidence-based feedback on proposed building performance. The development of intuitive and simplified simulation interfaces has greatly contributed to achieving this integration. One aspect that is often overlooked is the workflow that governs and regulates integrated design, which can have significant impacts on final design outcomes. Currently there are numerous software packages available for building performance simulations. This makes it challenging to select an appropriate tool that provides accurate results yet allows a designer to make informed architectural decisions with a designer-friendly interface. Furthermore, workflows to incorporate simulations into the design process proved to highly impact student’s project design integration. Yet, it is not clear what type of workflows are successful to achieve this goal, under what conditions, and/or for which building and site typologies. This paper addresses these issues by first reviewing three different workflows for integrating building performance simulation processes and highlighting their strengths and weaknesses. Second, a comparative case study approach was employed to test three of the most common workflows in three different integrated design architectural studios at the senior and vertical studio levels as well as in two courses that run parallel and complementary to the design studios. The workflows, processes, and the resultant student projects were further analyzed based on criteria for better integrated design and architectural excellence as outlined in the American Institute of Architects Committee on the Environment (AIA COTE) Top 10 Student’s Competition. Third, to situate the pedagogical case studies’ results within a larger context, a survey of the AIA COTE Top 10 student competition award recipients over the last five years was conducted. The results are summarized in a pedagogical framework that outlines best strategies of the type of workflows, software, design process used, methods to achieve desired interaction between design process and analytical feedback, and metrics for educators to evaluate the success of this integration and their learning outcomes in the design studio. The goal is to help bridge the gap between the building design and simulation within the design studio’s creative process for more integrated design outcomes.

Elzeyadi, Ihab↗
DOE OSTI2020

Counterweight for Long Reach Robotic Arm

Maintenance for vital systems proves challenging due to their location: tucked up and behind components. Pinpointing the precise location of errors presents difficulty when relying solely on the human eye. The solution to this issue arises in the form of a Long Reach Robotic Arm. An adequately balanced robot with several individually controlled links contains the capability to maneuver around obstructing components to locate the points of failure with accuracy. The design process for such a robot begins with the writing of a program. The program intends to visualize how the Long Reach Robotic Arm will move in 2D space by printing a select number of lines representing each arm link to the screen and controlling each link through the keyboard. This code substantially simplifies the design process for the multi-linked arm. The next step in the Long Reach Robotic Arm design process is the development of the arm and its counterweight system. The clear division of this work allows two interns to work on this project: one assumes responsibility for the arm, and the other for the counterweight. I undertook the design for the counterbalance. My half of the project is essential for maintaining safety as an extended multi-linked robot arm presents the challenge of preserving stability. The best method to supply a balance to the robot, even in extension, is a mobile counterweight with a compact design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Shaping Symmetry and Molding Morphology of Triply-Periodic Network Assemblies via Molecular Design and Processing of Block Copolymers

This project aimed to uncover molecular design rules for block copolymer (BCP) assemblies of triply-periodic network (TPN) phases, which are highly sought after, yet elusive, nanostructures for many functional material applications that rely on their combination of symmetry and polycontinuous domain connectivity [R1, R2], such as topological-photonics, supercapacitors and ultrafiltration media. While they have been a target of “bottom up” approaches to nanostructured, hybrid materials, the ability to manipulate the tubular network morphology of TPN assemblies beyond the cubic double-gyroid (DG) phase has advanced relatively little.

36 MATERIALS SCIENCE↗