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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Impact of Precipitation Parameters on the Specific Surface Area of PuO 2

Controlling the properties of PuO 2 through processing is of vital importance to environmental transport and fate, production of nuclear fuels, nuclear forensic analyses, stockpile stewardship, and storage of nuclear wastes applications. A number of processing conditions have been identified to control final product properties, including specific surface area (SSA), residual carbon content, adsorption of volatile species, morphology, and particle size. In this paper, a novel approach is developed for the prediction of PuO 2 SSA via the synthetic route of Pu(IV) oxalate precipitation followed by calcination. The proposed model utilizes multivariate regression methodology and leave one out formalism to link Savannah River Site (SRS) precipitation and calcination production data to the SSA of the final product. A comparison among the models provides insight into the accuracy and ability to identify variations amongst the processing data. Additionally, the models may also be used to fit new data outside of the parameters explored in a production facility. Finally, the trained model was compared to a similarly trained conventional model form to illustrate the influence of precipitation parameters on the prediction of the final SSA. The models presented here attempt to provide new methods for more accurate prediction of the PuO 2 product properties in a production scale environment for key environmental and nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Molecular structures reveal the origin of spectral variation in cryptophyte light harvesting antenna proteins

In addition to their membrane-bound chlorophyll a/c light-harvesting antenna, the cryptophyte algae have evolved a unique phycobiliprotein antenna system located in the thylakoid lumen. The basic unit of this antenna consists of two copies of an αβ protomer where the α and β subunits scaffold different combinations of a limited number of linear tetrapyrrole chromophores. While the β subunit is highly conserved, encoded by a single plastid gene, the nuclear-encoded α subunits have evolved diversified multigene families. It is still unclear how this sequence diversity results in the spectral diversity of the mature proteins. By careful examination of three newly determined crystal structures in comparison with three previously obtained, we show how the α subunit amino acid sequences control chromophore conformations and hence spectral properties even when the chromophores are identical. Previously we have shown that α subunits control the quaternary structure of the mature αβ.αβ complex (either open or closed), however, each species appeared to only harbor a single quaternary form. Here we show that species of the Hemiselmis genus contain expressed α subunit genes that encode both distinct quaternary structures. Finally, we have discovered a common single-copy gene (expressed into protein) consisting of tandem copies of a small α subunit that could potentially scaffold pairs of light harvesting units. Together, our results show how the diversity of the multigene α subunit family produces a range of mature cryptophyte antenna proteins with differing spectral properties, and the potential for minor forms that could contribute to acclimation to varying light regimes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evaluating performance of different generative adversarial networks for large-scale building power demand prediction

We report as an unsupervised-learning data-driven model, Generative Adversarial Networks (GANs) have recently attracted a lot of attention for various applications. There is potential to apply GANs for large-scale building power demand prediction, which is needed for power grid operation. However, there are many GAN variations and it is unclear which GAN is suitable for this application. To answer this question, this paper identifies five promising GANs (Original GAN, cGAN, SGAN, InfoGAN, and ACGAN) and evaluates their performance for predicting building power demand at a large scale. Physics-based building energy models are developed to generate training and reference data. A new evaluation indicator that combines accuracy and reproducibility is proposed to evaluate the performance of different GANs in predicting building power demand. The results show that SGAN and InfoGAN are not suitable because they cannot control the number of generated building samples for different building types. The prediction performance among the Original GAN, cGAN, and ACGAN can vary depending on training sample sizes and number of building types. If the training sample size is sufficiently large, Original GAN and cGAN can predict building power demand more accurately than ACGAN with the same number of samples. If training samples are limited, Original GAN provides better accuracy than cGAN and ACGAN. When the number of building types increase, the prediction accuracy increases for cGAN, decreases for ACGAN, and remains the same for Original GAN. As a result, cGAN and Original GAN are recommended for large-scale building power demand prediction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Phase field dislocation dynamics (PFDD) modeling of non-Schmid behavior in BCC metals informed by atomistic simulations

Body-Centered Cubic (BCC) metals exhibit anomalous mechanical properties such as twinning/anti-twinning and tension/compression asymmetry, which are attributed to asymmetric behavior of screw dislocations. Unlike Face-Centered Cubic (FCC) metals, the Critical Resolved Shear Stress (CRSS) of BCC metals deviates from the Schmid law. Here, we use a mesoscale modeling approach called Phase Field Dislocation Dynamics (PFDD) to understand the critical factors that control this non-Schmid behavior and reproduce atomistic predictions of the CRSS (Peierls stress). All inputs to the PFDD model are obtained from Molecular Statics (MS) simulations. Multiple pathways for modeling the non-Schmid behavior are investigated by incorporating the representative dislocation properties into different energy terms in the PFDD model. One way to understand non-Schmid behavior is to incorporate stress components projected on inclined planes into the external energy term within PFDD. Alternatively, we propose that non-Schmid behavior can also be accounted for by considering the variation of the {110} unstable stacking fault energy and the dislocation core width as a function of the applied tensorial stress field. The CRSS predicted using PFDD modeling is in excellent agreement with MS predictions.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Realization of fermionic Laughlin state on a quantum processor

Strongly correlated topological phases of matter are central to modern condensed matter physics and quantum information technology but often challenging to probe and control in material systems. The experimental difficulty of accessing these phases has motivated the use of engineered quantum platforms for simulation and manipulation of exotic topological states. Among these, the Laughlin state stands as a cornerstone for topological matter, embodying fractionalization, anyonic excitations, and incompressibility. Although its bosonic analogs have been realized on programmable quantum simulators, a genuine fermionic Laughlin state has yet to be demonstrated on a quantum processor. Here, we realize the ν = 1/3 fermionic Laughlin state on IonQ’s trapped-ion quantum computer using an efficient and scalable Hamiltonian variational ansatz with 369 two-qubit gates on a 16-qubit circuit. Employing symmetry-verification error mitigation, we extract key observables that characterize the Laughlin state, including correlation hole, bulk-edge correspondence, and topological entanglement entropy, with strong agreement to exact diagonalization benchmarks. This work demonstrates an end-to-end workflow to simulate material-intrinsic topological orders and provides a starting point to explore its dynamics and excitations on digital quantum processors.

Shen, Lingnan [Univ. of Washington, Seattle, WA (U↗
DOE OSTI2024

Challenges of COVID-19 Case Forecasting in the US, 2020–2021

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and government entities led by the Centers for Disease Control and Prevention and the US COVID-19 Forecast Hub ( https://covid19forecasthub.org ). We evaluated approximately 9.7 million forecasts of weekly state-level COVID-19 cases for predictions 1–4 weeks into the future submitted by 24 teams from August 2020 to December 2021. We assessed coverage of central prediction intervals and weighted interval scores (WIS), adjusting for missing forecasts relative to a baseline forecast, and used a Gaussian generalized estimating equation (GEE) model to evaluate differences in skill across epidemic phases that were defined by the effective reproduction number. Overall, we found high variation in skill across individual models, with ensemble-based forecasts outperforming other approaches. Forecast skill relative to the baseline was generally higher for larger jurisdictions (e.g., states compared to counties). Over time, forecasts generally performed worst in periods of rapid changes in reported cases (either in increasing or decreasing epidemic phases) with 95% prediction interval coverage dropping below 50% during the growth phases of the winter 2020, Delta, and Omicron waves. Ideally, case forecasts could serve as a leading indicator of changes in transmission dynamics. However, while most COVID-19 case forecasts outperformed a naïve baseline model, even the most accurate case forecasts were unreliable in key phases. Further research could improve forecasts of leading indicators, like COVID-19 cases, by leveraging additional real-time data, addressing performance across phases, improving the characterization of forecast confidence, and ensuring that forecasts were coherent across spatial scales. In the meantime, it is critical for forecast users to appreciate current limitations and use a broad set of indicators to inform pandemic-related decision making.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improvement of Atmospheric Objective Analysis Over Sloping Terrain and Its Impact on Shallow-Cumulus Clouds in Large-Eddy Simulations

Surface topography strongly impacts the regional atmospheric circulation dynamically and thermodynamically. Over the Great Plains in the United States, the gently tilted slope is an important factor that impacts clouds, convection and regional circulations. This study enhances an atmospheric constrained variational analysis by using a terrain-following sigma vertical coordinate and applies to the data collected at the Southern Great Plain (SGP) site of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program. Sensitivity studies are performed to examine the impact of the terrain effects on the derived large-scale atmospheric forcing fields and the simulated shallow-cumulus clouds in large-eddy simulation (LES) driven by the forcing. We found that the terrain impacts on the large-scale forcing fields are mainly at lower levels and are strongly controlled by up/downslope winds. The response of the derived forcing to the slope of the terrain is monotonic, but the response of the simulated shallow-cumulus clouds is more complex and depends on several factors. Overall, the terrain impact is small over SGP due to the small slope angle. However, the flat-surface assumption may cause larger biases in the large-scale forcing fields at locations with steeper terrain. The new sigma-coordinate algorithm, with its consideration of surface slope, should be more suitable to derive large-scale objective analysis over regions with steep terrain for application to force single-column models, cloud resolving models and LES models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Suppression of edge localized modes with real-time boron injection using the tungsten divertor in EAST

We report an observation of robust suppression of edge-localized modes (ELMs) in the Experimental Advanced Superconducting Tokamak (EAST), enabled by continuous boron (B) powder injection. Edge harmonic oscillations appear during B powder injection, providing sufficient particle transport to maintain constant density and avoid impurity accumulation in ELM-stable plasmas. Here, quasi-steady ELM suppression discharges are demonstrated with modest energy confinement improvement and over a wide range of conditions: heating power and technique variation, electron density range over a factor ~3.5, deuterium or helium ion species, and with either direction of the toroidal magnetic field. ELM suppression is observed above a threshold edge B intensity and ceases within 0.5 s of termination of the B injection. In contrast to ELM suppression accompanied by recycling reduction during Li powder injection in NSTX and EAST (Maingi et al 2018 Nucl. Fusion 58 024003), reduced recycling due to hydrogenic species retention is unnecessary for the ELM suppression with B powder injection, paving the way for its consideration as an ELM control tool for future fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

A systems genetic analysis identifies putative mechanisms and candidate genes regulating vessel traits in poplar wood

Wood is the water conducting tissue of tree stems. Like most angiosperm trees, poplar wood contains water-conducting vessel elements whose functional properties affect water transport and growth rates, as well as susceptibility to embolism and hydraulic failure during water stress and drought. Here we used a unique hybrid poplar pedigree carrying genomically characterized chromosomal insertions and deletions to undertake a systems genomics analysis of vessel traits. We assayed gene expression in wood forming tissues from clonal replicates of genotypes covering dosage quantitative trait loci with insertions and deletions, genotypes with extreme vessel trait phenotypes, and control genotypes. A gene co-expression analysis was used to assign genes to modules, which were then used in integrative analyses to identify modules associated with traits, to identify putative molecular and cellular processes associated with each module, and finally to identify candidate genes using multiple criteria including dosage responsiveness. These analyses identified known processes associated with vessel traits including stress response, abscisic acid and cell wall biosynthesis, and in addition identified previously unexplored processes including cell cycle and protein ubiquitination. We discuss our findings relative to component processes contributing to vessel trait variation including signaling, cell cycle, cell expansion, and cell differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Vaccine Efficacy of a Replication-Competent Interferon-Expressing Porcine Reproductive and Respiratory Syndrome (PRRS) Virus Against NADC-34 Challenge

Background/Objectives: Porcine reproductive and respiratory syndrome virus (PRRSV) significantly impedes swine production due to rapid genetic variation and suppression of antiviral interferon (IFN) responses, leading to ineffective immunity. To address this, we developed IFNmix, a replication-competent PRRSV modified live vaccine (MLV) candidate co-expressing three Type I IFN subclasses (IFNα, IFNβ, IFNδ) to enhance antiviral immunity. Methods: In two independent in vivo experiments, we compared the protection of IFNmix and a commercial PRRSV MLV vaccine during challenge with a virulent PRRSV strain. Clinical signs, antibody and cytokine production, viral replication, and lung pathology in IFNmix-vaccinated pigs were compared to those of commercial PRRSV vaccines and controls. Results: Pigs vaccinated with IFNmix exhibited similar anti-PRRSV antibody development, serum viral loads, lung lesions, and cytokine responses post-challenge with the virulent NADC34 strain, with comparable or lower body temperatures and weight gain, to pigs vaccinated with the commercial vaccines. While IFNmix showed early viral load reduction compared to the commercial vaccine (Days 7–14 post-challenge), it demonstrated similar efficacy in controlling PRRSV replication and lung pathology. Conclusions: These findings suggest that IFNmix, by expressing multiple IFNs, can potentially enhance innate and adaptive immune responses, offering a promising approach to improving PRRSV vaccine efficacy. Further studies are needed to evaluate IFNmix against a broader range of PRRSV strains and to optimize its attenuation and immunogenicity.

Miller, Laura C. (ORCID:0000000289469416)↗
DOE OSTI2022

High nitrate variability on an Alaskan permafrost hillslope dominated by alder shrubs

Abstract. In Arctic ecosystems, increasing temperatures are driving the expansion of nitrogen (N) fixing shrubs across tundra landscapes. The implications of this expansion to the biogeochemistry of Arctic ecosystems are of critical importance and more work is needed to better understand the form, availability, and transportation potential of N from these shrubs across a variety of Arctic landscapes. To gain insights into the processes controlling N within a permafrost hillslope system, the spatiotemporal variability of nitrate (NO3-) and its environmental controls were investigated at an alder (Alnus viridis spp. fruticosa) dominated permafrost tundra landscape in the Seward Peninsula, Alaska, USA. Soil pore water was collected from locations within alder shrubland growing along a well-drained hillslope and was compared to soil pore water collected from locations outside (upslope, downslope, and between) the alder shrubland. Soil pore water collected within alder shrubland had an average NO3-N (nitrogen from nitrate) concentration of 4.27±8.02 mg L−1 and differed significantly from locations outside alder shrubland (0.23±0.83 mg L−1; p<0.05). Temporal variation in NO3-N within and downslope of alder shrubland co-occurred with precipitation events where NO3- that accumulated in the soil was likely flushed downslope during rainfall. These findings have important implications for nutrient availability and mobility in N-limited permafrost systems that are experiencing shrub expansion in response to a warming Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Instability of Nagaoka State and Quantum Phase Transition via Kinetic Frustration Control

We investigate the Nagaoka-Thouless (NT) ferromagnetic instability in the strongly interacting t-t' Hubbard model by continuously breaking particle-hole symmetry on a tunable square-triangular lattice geometry. We use an analytic approach to show that the fully spin-polarized state becomes unstable to a metastable spin-polaron when the kinetic frustration t'/t exceeds a critical, dimension-dependent value. Large-scale density matrix renormalization group (DMRG) simulations reveal a quantum phase transition from the NT ferromagnet to a spiral spin-density wave, which evolves continuously into the Haerter-Shastry antiferromagnet in the large-frustration limit. Remarkably, this transition remains robust at low but finite hole density, making it accessible in cold-atom and moiré Hubbard platforms under strong interactions. A variational analysis further captures the instability mechanism at finite density via frustration-induced magnon band deformation.

FOS: Physical sciences↗
DOE OSTI2021

Investigation of Nucleation and Growth at a Liquid–Liquid Interface by Solvent Exchange and Synchrotron Small-Angle X-Ray Scattering

Hybrid nanomaterials possess complex architectures that are driven by a self-assembly process between an inorganic element and an organic ligand. The properties of these materials can often be tuned by organic ligand variation, or by swapping the inorganic element. This enables the flexible fabrication of tailored hybrid materials with a rich variety of properties for technological applications. Liquid-liquid interfaces are useful for synthesizing these compounds as precursors can be segregated and allowed to interact only at the interface. Although procedurally straightforward, this is a complex reaction in an environment that is not easy to probe. Here, we explore the interfacial crystallization of mithrene, a supramolecular multi-quantum well. This material sandwiches a well-defined silver-chalcogenide layer between layers of organic ligands. Controlling mithrene crystal size and morphology to be useful for applications requires understanding details of its crystal growth, but the specific mechanism for this reaction remain only lightly investigated. We performed a study of mithrene crystallization at an oil-water interfaces to elucidate how the interfacial free energy affects nucleation and growth. We exchanged the oil solvent on the basis of solvent viscosity and surface tension, modifying the dynamic contact angle and interfacial free energy. We isolated and characterized the reaction byproducts via scanning electron microscopy (SEM). We also developed a high-throughput small angle X-ray scattering (SAXS) technique to measure crystallization at short reaction timescales (minutes). Our results showed that modifying interfacial surface energy affects both the reaction kinetics and product size homogeneity and yield. Our SAXS measurements reveal the onset of crystallinity after only 15 min. These results provide a template for exploring directed synthesis of complex materials via experimental methods.

Schriber, Elyse A.↗
DOE OSTI2024

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope C1 Feed (LAWC22) Glass in Support of the LAW Pilot Melter (Final Report)

The Vitreous State Laboratory at The Catholic University of America (VSL) is developing and testing glass formulations for RPP-WTP waste envelopes to provide data to meet the RPP-WTP contract requirements and to support system design activities. That work is based upon small-scale batch melts (“crucible melts”) using waste envelope simulants. Selected formulations have also been tested in small-scale continuously-fed joule-heated melters (DM10 and DM100 systems) and, ultimately, in the LAW Pilot Melter. Such melter tests provide information on key process factors such as feed processing behavior, dynamic effects during processing, sulfate incorporation, processing rates, off-gas amounts and compositions, foaming control, etc., that cannot be reliably obtained from crucible melts. This sequential scale-up approach in the vitrification testing program ensures that maximum benefit is obtained from the more costly pilot-scale tests and that the most effective use is made of that resource. The principal objective of the work described in this report was to collect the necessary small-scale melter test data with a LAW Sub-Envelope C1 waste simulant in order to support the next series of tests with the same melter feed on the LAW Pilot Melter. This work was conducted under a corresponding Test Specification and Test Plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Controlling the Morphology of PEDOT:PSS Blend Films with Pre-Deposition Solution Composition and Deposition Technique

Understanding the relationships between morphology, fabrication processes, and thermoelectric performance in conducting polymers is essential to the development of high- efficiency organic thermoelectrics as an alternative to commonly used rare metals. Altering the film fabrication process of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) with the addition of high boiling solvents to the precast solution improves the electrical conductivity and significantly increases its Seebeck value. Neutron scattering monitors the changes in the atomic, nanoscale, and mesoscale morphologies of PEDOT:PSS thin films with the addition of dimethyl sulfoxide (DMSO) to the aqueous solution prior to film formation and with varying fabrication procedures. The neutron scattering results show a decrease in the deuterated PSS domain size along with systematic variations in PEDOT fibril assemblies in the final blend film with the addition of DMSO to the pre-deposition solution. These structural modifications indicate that the increase in conductivity of PEDOT:PSS blends with addition of DMSO reported in the literature can be ascribed to the disruption of solvated PEDOT assemblies by the DMSO, forming smaller PSS domains in the pre-deposition solution and allowing smoother film formation. These improvements are observed significantly with the addition of just 1% DMSO but continue to modestly improve with the addition of up to 5% DMSO to the PEDOT:PSS blend pre-deposition solution. The fact that the variations in the measured morphology are independent of whether the films were deposited by spin or ultrasonic spray casting methods emphasizes the crucial importance of the structure of the blend in the pre-deposition solution in determining the final thin film blend morphology.

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

Multi‐Material Gradient Printing Using Meniscus‐enabled Projection Stereolithography (MAPS)

Light‐based additive manufacturing methods are widely used to print high‐resolution 3D structures for applications in tissue engineering, soft robotics, photonics, and microfluidics, among others. Despite this progress, multi‐material printing with these methods remains challenging due to constraints associated with hardware modifications, control systems, cross‐contamination, waste, and resin properties. Here, a new printing platform coined Meniscus‐enabled Projection Stereolithography (MAPS) is reported, a vat‐free method that relies on generating and maintaining a resin meniscus between a crosslinked structure and bottom window to print lateral, vertical, discrete, or gradient multi‐material 3D structures with no waste and user‐defined mixing between layers. MAPS is compatible with a wide range of resins shown and can print complex multi‐material 3D structures without requiring specialized hardware, software, or complex washing protocols. MAPS's ability to print structures with microscale variations in mechanical stiffness, opacity, surface energy, cell densities, and magnetic properties provides a generic method to make advanced materials for a broad range of applications.

bioprinting↗
DOE OSTI2025

Imaging Photonic Resonances within an All‐Dielectric Metasurface via Photoelectron Emission Microscopy

Dielectric metasurfaces, through volume‐type photonic resonances, enable precise control of light‐matter interactions for applications including imaging, holography, and sensing. The application space of dielectric metasurfaces has extended from infrared to visible wavelengths by incorporating high refractive index materials, such as titanium dioxide (TiO 2 ). Understanding the fundamental and fabrication limits for these applications requires metrology with nanoscale resolution, sensitivity to electromagnetic fields within the meta‐atom volume, and far‐field excitation. In this work, photoelectron emission microscopy (PEEM) is used to image field distributions of photonic resonances in a TiO 2 metasurface excited with far‐field, visible‐wavelength illumination. The local volumetric field variations within the meta‐atoms are analyzed as a function of illumination angle and polarization by comparing photoelectron images to finite‐difference time‐domain simulations. This study determines the inelastic mean free path of very low‐energy (<1 eV) photoelectrons to be 35 ± 10 nm, which is comparable to the meta‐atom height thereby highlighting PEEM sensitivity to resonances within the volume. Additionally, the simulations reveal high sensitivity of PEEM images to an in‐plane component of the illumination k ‐vector. These results demonstrate that photoelectron imaging with subwavelength resolution offers unique advantages for examining light‐matter interactions in volume‐type (as opposed to surface) photonic modes within dielectric nanophotonic structures.

electron inelastic mean free path↗
DOE OSTI2021

Design principles of tandem cascade photoelectrochemical devices

Cascade photoelectrocatalysis (PEC) is a possible method to improve the selectivity of solar-driven CO 2 reduction (CO 2 R). This concept can be realized by coupling different CO 2 R catalysts to different subcells in a multijunction photovoltaic (PV) stack. Efficient implementation will require careful tuning of the photocurrents and design of the photovoltages provided by the subcells to the CO 2 R catalysts in such a way as to facilitate the target reaction. Here, we outline the design principles of the tandem PEC approach using two-step conversion of CO 2 to ethylene in aqueous electrolyte, via a CO intermediate, as a model system. To perform this reaction, the first coupled PV-catalyst component should provide 4 electrons to reduce 2 molecules of CO 2 to CO; the second component should provide 8 electrons to reduce 2 CO molecules to C 2 H 4 . Based on known CO 2 R catalysts, the overpotential required to produce CO can be less than that required to reduce it to ethylene, creating the opportunity for improved efficiency. Cascade PEC can be realized in a three-terminal tandem (3TT) configuration using III–V-semiconductor based subcells coupled to Au (produces CO intermediate) and Cu (converts CO to ethylene). The current to each catalyst can be controlled by the area of the subcell exposed to the electrolyte, and the photovoltage is determined by the materials selected and device configuration. Operating conditions are found by simulating the coupled system using the open-source circuit simulator SPICE (Simulation Program with Integrated Circuits Emphasis). We identify conditions under which a 3TT configuration can have a higher solar to chemical conversion efficiency compared to a two-terminal two-junction tandem (2T 2J) with the same absorbers and a Cu catalyst only. We also show that 3TT PEC devices can be less sensitive to variations in catalyst activity compared to 2T devices. Lastly, we discuss the applications of cascade PEC to CO 2 reduction, using different intermediates, and to other chemical networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗