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Clancy, Paulette

Publications and source records attributed to Clancy, Paulette.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Integrating Chemical Catalysis and Biological Conversion of Carbon Intermediates for Deriving Value-Added Products from Carbon Dioxide

Carbon dioxide valorization represents an appealing approach to reducing greenhouse gases in the atmosphere. While electrocatalysis is an effective tool to reduce CO 2 into small carbon compounds, it becomes increasingly challenging to efficiently produce compounds with more carbon atoms. In contrast, while biological systems struggle to utilize CO 2 , they can readily upcycle other small carbon compounds. This project explores the use of a two-stage process that electrocatalytically converts CO 2 into methanol, formate, or acetate which is subsequently utilized by Methylotuvimicrobium alcaliphilum 20Z to produce medium chain length polyhydroxyalkanoate. A techno-economic analysis and life cycle assessment evaluates the commercial viability of the process as well as its carbon emissions. We show here an enhanced CO 2 -to-methanol electroconversion step coupled with the use of a microbial culture adapted to the process conditions to be the optimal configuration for economic potential.

09 BIOMASS FUELS↗
DOE OSTI2024

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Smaller Is Better: The Case for Lower-Order Iodoplumbate Species Dominating MAPbI 3 /Dimethylformamide Solutions

Here, using complementary experimental measurements and computational predictions of spectroscopic measurements (EXAFS, XANES, and UV–vis), we have determined the identity of the most stable iodoplumbate species in dilute lead halide perovskite precursor solutions. We have determined which species are most likely to be thermodynamically stable compared to others that are unstable or metastable. Condensed phase ab initio models were constructed, and the resulting ensembles were used to directly compare the computed signals to the experimental results of the EXAFS, XANES, and UV–vis spectra of PbI 2 :MAI in DMF. The results of this study suggest that only Pb 2+ , PbI + , and PbI 2 are dominant in the dilute lead perovskite precursor solutions as thermodynamically stable entities. Our interpretation of the relative stability of iodoplumbate species in solution, based on an analysis of EXAFS and XANES spectra, provides critically important new insight into the species most likely to be responsible for crystal nucleation and growth in these materials. This insight will have a significant consequence on the broad scientific community and will necessitate the reinterpretation of peaks in the UV–vis spectra of lead halide perovskite precursor solutions.

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

Solution–Doped Donor–Acceptor Copolymers Based on Diketopyrrolopyrrole and 3, 3'–Bis (2–(2–(2–Methoxyethoxy) Ethoxy) ethoxy)–2, 2'–Bithiophene Exhibiting Outstanding Thermoelectric Power Factors with p –Dopants

The design of polymeric semiconductors exhibiting high electrical conductivity (σ) and thermoelectric power factor (PF) will be vital for flexible large-area electronics. In this work, four polymers based on diketopyrrolopyrrole (DPP), 2,3-dihydrothieno[3,4-b][1,4]dioxine (EDOT), thieno[3,2-b]thiophene (TT), and 3, 3'-bis (2-(2-(2-methoxyethoxy) ethoxy) ethoxy)-2, 2'-bithiophene (MEET) are investigated as side-chains, with the MEET polymers newly synthesized for this study. These polymers are systematically doped with tetrafluorotetracyanoquinodimethane ( F 4 TCNQ), CF3SO3H, and the synthesized dopant Cp(CN) 3 -(COOMe) 3 , differing in geometry and electron affinity. The DPP-EDOT-based polymer containing MEET as side-chains exhibits the highest conductivity (σ) ≈700 S cm–1 in this series with the acidic dopant (CF 3 SO 3 H). This polymer also shows the lowest oxidation potential by cyclic voltammetry (CV), the strongest intermolecular interactions evidenced by differential scanning calorimetry (DSC), and has the most oxygen-based functionality for possible hydrogen bonding and ionic screening. Other polymers exhibit high σ ≈300–500 S cm–1 and power factor up to 300 µW m –1 K –2 . The mechanism of conductivity is predominantly electronic, as validated by time-dependent conductance studies and transient thermo voltage monitoring over time, including for those doped with the acid. Furthermore, these materials maintain significant thermal stability and air stability over ≈6 weeks. Density functional theory calculations reveal molecular geometries and inform about frontier energy levels. Raman spectroscopy, in conjunction with scanning electron microscopy (SEM-EDS) and x-ray diffraction, provides insight into the solid-state microstructure and degree of phase separation of the doped polymer films. Infrared spectroscopy enables this study to further quantify the degree of charge transfer from polymer to dopant.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fabricating Single Crystal Quantum Dot Solids

The central goal of this research program was to establish fundamental synthesis and processing principles to enable the fabrication of single crystal quantum dot solids (QDS) with programmable structure (i.e., hexagonal and square) and composition. Our approach towards that goal leveraged access to and experience with unique in-situ, multi-probe characterization techniques to understand and ultimately control the fundamental relationship between processing conditions and nucleation and growth of QDS. The program integrated synthesis and fabrication (Hanrath) with in-situ TEM analysis (Kourkoutis) and computational modeling (Clancy) to gain atomic-level insights into the underlying physical phenomena governing assembly and attachment and to guide the development of optimized processing methods. We have established a foundational understanding of physicochemical interactions of self-assembly at a fluid interface, superlattice structure transformation pathways, the critical role of disorder during the initial dimerization of colloidal quantum dot monomers, and the residual strain distribution within the inter-dot epitaxial bridge which hampers the formation of novel electronics states of the quantum dot solids. Collectively, these insights have contributed towards advancing the mechanistic understanding of the complex choreography of assembly and attachment as well as understanding what currently limits further advances in high-fidelity quantum dot solids and tiles.

36 MATERIALS SCIENCE↗