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At least 1,459 records · Page 81

Recent advances of two-dimensional material additives in hybrid perovskite solar cells

Perovskite solar cells (PSCs) have become one of the state-of-the-art photovoltaic technologies due to their facile solution-based fabrication processes combined with extremely high photovoltaic performance originating from excellent optoelectronic properties such as strong light absorption, high charge mobility, long free charge carrier diffusion length, and tunable direct bandgap. However, the poor intrinsic stability of hybrid perovskites under environmental stresses including light, heat, and moisture, which is often associated with high defect density in the perovskite, has limited the large-scale commercialization and deployment of PSCs. The use of process additives, which can be included in various subcomponent layers in the PSC, has been identified as one of the effective approaches that can address these issues and improve the photovoltaic performance. Among various additives that have been explored, two-dimensional (2D) materials have emerged recently due to their unique structures and properties that can enhance the photovoltaic performance and device stability by improving perovskite crystallization, defect passivation, and charge transport. In this work, we provide a review of the recent progresses in 2D material additives for improving the PSC performance based on key representative 2D material systems, including graphene and its derivatives, transitional metal dichalcogenides, and black phosphorous, providing a useful guideline for further exploiting unique nanomaterial additives for more efficient and stable PSCs in the near future.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Data Science Meets Physical Organic Chemistry

At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interfacial Engineering Using Covalent Organic Frameworks in Polymer Composites for High‐Temperature Electrostatic Energy Storage

Abstract The use of inorganic nanofillers has been an effective method to improve high‐temperature capacitive performance of dielectric polymers, though there are unmet challenges such as undesirable organic–inorganic compatibility, and low efficiencies and energy densities. Herein, a surface functionalization strategy using covalent organic frameworks (COFs) is employed to address such challenges in realizing high‐performing polymer composites. Specifically, core–shell structured nanoparticles, where ZrO 2 nanoparticles act as the core and a COF material forms the shell, are constructed and composited with the polyetherimide (PEI) matrix. The design leverages the high electron affinity ( E A ) of the outer COF shell to create energy traps, thereby capturing free charges and limiting electrical conduction. Concurrently, the low E A and wide bandgap of the ZrO 2 core introduce energy barriers to impede charge injection and migration. This orchestrated “energy level cascade” results in a marked reduction of leakage current and energy loss. The resulting polymer composite showcases an impressive discharged energy density of 6.21 J cm −3 at an efficiency above 90%, with a maximum discharged energy density reaching 7.43 J cm −3 at 150 °C. These performance metrics position the PEI/ZrO 2 @COF polymer composite to surpass or be on par with state‐of‐the‐art high‐temperature PEI composites and other advanced polymer dielectrics.

Xie, Zongliang↗

Advanced strategies for the development of porous carbon as a Li host/current collector for lithium metal batteries

Lithium metal is considered a promising anode material for high-energy-density rechargeable batteries because of its high specific theoretical capacity (3860 mAh g -1 , low mass density (0.534 g cm -3 ), and low electrochemical redox potential (-3.04 V vs. the standard hydrogen electrode). However, the high reactivity of Li with the electrolyte leads to the formation of an unstable solid electrolyte interphase (SEI) and continuous side reactions. Also, the non-uniform lithium-ion flux and infinite volume expansion of Li metal cause the growth of Li dendrites. These pose significant safety challenges and cause rapid capacity fading of the lithium metal batteries (LiMBs). To resolve these issues, a low-cost, easily processed, lightweight, high-performance carbon-based porous matrix is considered promising to host Li metal deposition. The three-dimensional (3D) porous nano/microstructured carbon provides sufficient space for Li accommodation during Li plating, buffers the volume changes during Li plating/stripping, and lowers the effective current density contributing to dendrite-free Li deposition. Besides, the outstanding electrochemical and mechanical stability, flexibility and the high electronic conductivity enable the nano/microstructured carbon to serve as both Li host and current collector. The development of 3D carbon/Li composite by mechanical roll-press techniques not only eliminates the complex and risky procedure of making carbon/Li composite based on Li plating or molten Li infusion but also stabilizes the capacity at higher Li plating/stripping rates. Recently, there is an advancement in the lithiophilic decorations of 3D structure to introduce sufficient nucleation sites and the development of artificial SEI on top of the 3D matrix to suppress Li dendrite formation. Such 3D structural modifications create a uniform electric field, lower the Li nucleation overpotential, provide strong mechanical and chemical stability, and stabilize the interface thereby inhibiting the degradation of lithium and the electrolyte. Here we summarize the research progress on porous carbon/Li composites in terms of materials type, structure, fabrication technique, their electrochemical battery performance, and identify the critical challenges that need to be addressed for high-energy-density practical LiMBs.

25 ENERGY STORAGE↗

Concrete Structure Health Monitoring Using Vibro-acoustic Testing and Machine Learning

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of High-QE GaN Photodectors for Liquid Noble Particle Detectors

Detection of the handful of photons generated when a dark matter particle interacts in a liquid Xenon detector requires a new type of photodetector with very high detection efficiency at ultraviolet wavelengths, very low radioactive backgrounds, and essentially no measureable readout noise (achieved with devices with high intrisic gain). Such devices would find wide applicability to not only high energy physics experiments, but to a number of commercial applications including, e.g., biomedical imaging of fluorescent tags. We developed photodetectors based on amorphous GaN thin film structures (photocathodes) grown by molecular beam epitaxy on quartz windows. We also developed approaches to integrate these photocathode device structures with vacuum electron multipliers. All materials and fabrication techniques were developed to minimize radioactive backgrounds in materials, so these detectors could be used for very low count rate experiments, such as the future liquid-Xenon dark matter detectors, and future liquid-Argon neutrino detectors. We demonstrated growth of very high quantum efficiency amorphous GaN cathodes grown on a number of different substrates (Stainless steel, p-Silicon) reaching detection efficiencies of 80% at 220nm. The key to this growth was to use nitrogen plasma-assistend MBEs and very low growth temperatures. We also discovered that thinner structures (e.g.,40nm a-GaN thin films) had the best performance. We successfully demonstrated techniques for the vacuum transfer of these photocathode structures to a novel chamber that used hydraulics and bellow to form a cold indium bond needed to integrate these cathodes into sealed-tube devices. A complete, stand-along, device could not be completed during this proposal period due to difficulties in growing structures on the thick quartz window. Subsequent work is aimed at addressing this difficulty, by growing a buffer layer on the quartz substrate.

07 ISOTOPE AND RADIATION SOURCES↗

DENOVA: Deduplication Extended NOVA File System

This paper shows mathematically and experimentally that inline deduplication is not suitable for file systems on ultra-low latency Intel Optane DC PM devices in terms of performance, and proposes DeNova, an offline deduplication specially designed for log-structured NVM file systems such as NOVA. DeNova offers high-performance and low-latency I/O processing and executes deduplication in the background without interfering with foreground I/Os. DeNova employs DRAM-free persistent deduplication metadata, favoring CPU cache line, and ensures failure consistency on any system failure. We implement DeNova in the NOVA file system. Evaluation with DeNova confirms a negligible performance drop of baseline NOVA of less than 1%, while gaining high storage space savings. Extensive experiments show DeNova is failure consistent in all failure scenario cases.

Khan, Awais↗

Comparison of time-resolved photoluminescence and deep-level transient spectroscopy defect evaluations in an InAs nBn detector subjected to in situ and ex situ 63 MeV proton irradiation

Deep-level transient spectroscopy and temperature-dependent time-resolved photoluminescence experiments are performed on identical InAs nBn photodetector structures as a function of in situ and ex situ 63 MeV proton irradiation to assess their generation and recombination dynamics. Pre-irradiation, the n-type InAs absorbing region, exhibits a steadily increasing minority carrier lifetime with increasing temperature, providing evidence that excited minority carriers may be recombining via shallow defect levels. From deep-level transient spectroscopy, two features are found between 10 and 275 K: a low temperature broad “shoulder,” which suggests emission from multiple shallow electron defect levels with energies <29 meV and a high temperature minimum occurring at ∼230 K with an activation energy of 539 meV, which suggests a defect in the barrier layer in the device. Two similar nBn detectors are then subjected to 63 MeV proton irradiation in step doses and measured between steps. One experiment is performed in situ with an nBn held at ∼10 K during dosing, and the other experiment is performed ex situ with a similar nBn held at room temperature for dosing. The ex situ dosing results in an evaluation of the defect introduction rate that is three to four times lower than in situ due to partial annealing of the proton-induced displacement damage at room temperature. The results of these two experiments are then compared with the dose-dependent recombination rate analysis, resulting in an estimated recombination defect cross section of 1.6 × 10 −13 cm 2 for the shallow shoulder defect.

Carrasco, Rigo A. [Air Force Research Laboratory (↗

Optical properties of differing nanolayered structures of divalent europium doped barium fluoride thin films synthesized by pulsed laser deposition

Optically-active thin films are employed in a variety of applications, such as LEDs and photovoltaics, due to their ability to act as up- or down-photon energy converters. Their performance depends critically on their composition and structure; thus, the use of novel synthesis techniques that allow for their control at the nanoscale level can result in improved efficiency and practicality. Here, layered thin films consisting of Eu 2+ - doped BaF 2 nanocrystalline layers separated by amorphous Al 2 O 3 were synthesized via sequential pulsed laser deposition using three separate targets for the different components; this synthesis technique provides precise control of layer thickness at the nanoscale along with dopant distribution within the film. Cross-sectional transmission electron microscopy analysis verified the desired nano-layering. Post-deposition heat treatments in a nitrogen atmosphere resulted in samples exhibiting steady emission with a broad peak ranging from 400 to 600 nm and a shoulder at 410 nm. The CIE 1931 chromaticity coordinates are x = 0.26-0.29 and y = 0.32-0.35 and vary as a function of the sample configuration. Because the chromaticity coordinates are close to those of a pure white light (x = 0.33, y = 0.33), these films demonstrate advantageous properties for applications with UV-pumped white light LEDs.

36 MATERIALS SCIENCE↗

Direct Imaging of Asymmetric Interfaces and Electrostatic Potentials inside a Hafnia–Zirconia Ferroelectric Nanocapacitor

In hafnia-based thin-film ferroelectric devices, chemical phenomena during growth and processing, such as oxygen vacancy formation and interfacial reactions, appear to strongly affect device performance. However, the correlation between the structure, chemistry, and electrical potentials at the nanoscale in these devices is not fully known, making it difficult to understand their influence on device properties. Here, we directly image the composition and electrostatic potential with nanometer resolution in the cross section of a nanocrystalline W/Hf 0.5 Zr 0.5 O 2−δ (HZO)/W ferroelectric capacitor using multimodal electron microscopy. This reveals a 1.4 nm wide tungsten suboxide interfacial layer formed at the bottom interface during fabrication, which introduces a potential dip and leads to asymmetric switching fields. Additionally, we compare the measured potentials to DFT calculations and find it is nearly 3 V lower than expected in the HZO, which appears to be caused by oxygen vacancies and a resulting negative built-in potential. In conclusion, these chemical and electrostatic details are important to characterize and tune to achieve high-performance ferroelectric devices.

Defects in solids↗

Experimental and Kinetic Modeling Study of Laminar Burning Velocities of Cyclopentanone and Its Binary Mixtures with Ethanol and n-Propanol

Cyclopentanone is a promising biofuel that can enable more efficient engine operation and increase the fuel economy of the light duty fleet over current and planned technology developments. While the ignition of cyclopentanone has been investigated in detail, more studies on the laminar burning velocities of cyclopentanone are called for. In this work, the laminar burning velocities of cyclopentanone (C 5 H 8 O) have been measured using the heat flux and spherical flame methods at 1 atm, equivalence ratios from 0.7 to 1.6, and initial temperatures of 328, 353, and 428 K. To further investigate the relationship between the molecular structure and laminar burning velocity, identical experiments were also performed for binary mixtures of cyclopentanone with ethanol and n-propanol at 1:1 (mol). The consistency between the experimental data sets obtained in this work and literature data sets has been evaluated. Here, a recently published mechanism of cyclopentanone was used for simulation after adopting the submechanism of n-propanol. Good agreement has been seen between experimental and simulated results for all flames. To qualitatively explain the characteristics of the laminar burning velocity of cyclopentanone and the differences with those of ethanol and n-propanol, sensitivity analysis and reaction pathway analysis have been performed to compare the chemistry of the fuels under flame conditions, which revealed how the molecular structure of cyclopentanone could affect its laminar burning velocity. Compared to ethanol and n-propanol, cyclopentanone does not have primary carbon atoms in its molecule, leading to lower production of methyl radicals. Meanwhile, the carbonyl group in the cyclopentanone molecule is mostly released as CO in the decomposition of multiple intermediates accompanied by the production of unsaturated C 2 and C 4 species, especially C 2 H 4 and C 2 H 3 . Both features contribute to the high laminar burning velocity of cyclopentanone.

09 BIOMASS FUELS↗

Predicting Energetics Materials’ Crystalline Density from Chemical Structure by Machine Learning

To expedite new molecular compound development, a long-sought goal within the chemistry community has been to predict molecules’ bulk properties of interest a priori to synthesis from a chemical structure alone. In this work, we demonstrate that machine learning methods can indeed be used to directly learn the relationship between chemical structures and bulk crystalline properties of molecules, even in the absence of any crystal structure information or quantum mechanical calculations. We focus specifically on a class of organic compounds categorized as energetic materials called high explosives (HE) and predicting their crystalline density. An ongoing challenge within the chemistry machine learning community is deciding how best to featurize molecules as inputs into machine learning models—whether expert handcrafted features or learned molecular representations via graph-based neural network models—yield better results and why. We evaluate both types of representations in combination with a number of machine learning models to predict the crystalline densities of HE-like molecules curated from the Cambridge Structural Database, and we report the performance and pros and cons of our methods. Our message passing neural network (MPNN) based models with learned molecular representations generally perform best, outperforming current state-of-the-art methods at predicting crystalline density and performing well even when testing on a data set not representative of the training data. However, these models are traditionally considered black boxes and less easily interpretable. Here, to address this common challenge, we also provide a comparison analysis between our MPNN-based model and models with fixed feature representations that provides insights as to what features are learned by the MPNN to accurately predict density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Atomic-Scale Behavior of Radiation-Resistant ZnO under High-Energy Electron Bombardment

Understanding the atomic structure and defect characteristics of ZnO thin films is crucial for optimizing their electronic properties and performance in advanced applications. Here, we investigate the atomic structure and defect characteristics of atomic layer deposition (ALD)-grown ZnO thin films by using aberration-corrected scanning transmission electron microscopy (STEM). Atomic-resolution imaging identifies prevalent stacking faults, dipole disorder, and various grain boundary types, which are believed to influence the electronic properties of ZnO. Additionally, real-time electron beam exposure experiments demonstrate structural transformations, including crystal growth and surface rearrangements. These findings provide insights into the growth mechanisms of ALD ZnO under high-energy electron irradiation conditions, an important finding for the use of polycrystalline ZnO wide bandgap semiconductors in space-like conditions. In conclusion, our results underscore the capability of STEM in directly visualizing and quantifying atomic-scale defects and beam-induced transformations in radiation-resistant ZnO.

Defects↗

Reversible multicolor chromism in layered formamidinium metal halide perovskites

Abstract Metal halide perovskites feature crystalline-like electronic band structures and liquid-like physical properties. The crystal–liquid duality enables optoelectronic devices with unprecedented performance and a unique opportunity to chemically manipulate the structure with low energy input. In this work, we leverage the low formation energy of metal halide perovskites to demonstrate multicolor reversible chromism. We synthesized layered Ruddlesden-Popper FA n+1 Pb n X 3n+1 (FA = formamidinium, X = I, Br; n = number of layers = 1, 2, 3 … ∞) and reversibly tune the dimensionality ( n ) by modulating the strength and number of H-bonds in the system. H-bonding was controlled by exposure to solvent vapor (solvatochromism) or temperature change (thermochromism), which shuttles FAX salt pairs between the FA n+1 Pb n X 3n+1 domains and adjacent FAX “reservoir” domains. Unlike traditional chromic materials that only offer a single-color transition, FA n+1 Pb n X 3n+1 films reversibly switch between multiple colors including yellow, orange, red, brown, and white/colorless. Each colored phase exhibits distinct optoelectronic properties characteristic of 2D superlattice materials with tunable quantum well thickness.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New proposed ITER divertor design using carbon insert on tungsten to mitigate ELMs and secondary radiation effects on nearby components

Abstract Building a successful device for the magnetic fusion energy production is a great challenge. ITER is an international project of the tokamak based magnetic fusion design being developed for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. A key obstacle to a successful magnetic fusion energy production is however, the performance during abnormal events including plasma disruptions and edge-localized modes (ELMs). A credible reactor design must tolerate at least a few of these transient events without serious consequences such as melting of the structure. This paper investigates and compares the performance of the current ITER tokamak design during two types of transient events, i.e., ELMs occurring at normal operation and disruptions during abnormal operation. We simulated the divertor components response using our integrated 3D HEIGHTS package. The simulations include self-consistent modeling of the interaction of the released core plasma particles with the initial solid divertor material, energy deposition processes, vaporization of divertor material, secondary plasma formation and MHD evolution, incident core particles collisions and scattering from this dense secondary plasma, photon radiation of secondary plasma, and the resulting heat loads on nearby components. Our simulations showed that using a small carbon insert around the strike point can significantly reduce the overall expected damage on the tungsten dome structure, reflector plates, and prevent tungsten vaporization and its potential core plasma contamination.

47 OTHER INSTRUMENTATION↗

Correlated conformational dynamics of the human GluN1-GluN2A type N-methyl-D-aspartate (NMDA) receptor

N-Methyl-D-aspartate receptors (NMDARs) are glutamate-gated ion channels found in the nerve cell membranes. As a result of overexcitation of NMDARs, neuronal death occurs and may lead to diseases such as epilepsy, stroke, Alzheimer’s disease, and Parkinson’s disease. In this study, human GluN1- GluN2A type NMDAR structure is modeled based on the X-ray structure of the Xenopus laevis template and missing loops are added by ab-initio loop modeling. The final structure is chosen according to two different model assessment scores. To be able to observe the structural changes upon ligand binding, glycine and glutamate molecules are docked into the corresponding binding sites of the receptor. Subsequently, molecular dynamics simulations of 1.3 μs are performed for both apo and ligand-bound structures. Structural parameters, which have been considered to show functionally important changes in previous NMDAR studies, are monitored as conformational rulers to understand the dynamics of the conformational changes. Moreover, principal component analysis (PCA) is performed for the equilibrated part of the simulations. Additionally, from these analyses, the differences in between apo and ligand-bound simulations can be summarized as the following: The girdle right at the beginning of the pore loop, which connects M2 and M3 helices of the ion channel, partially opens. Ligands act like an adhesive for the ligand-binding domain (LBD) by keeping the bi-lobed structure together and consequently this is reflected to the overall dynamics of the protein as an increased correlation of the LBD with especially the amino-terminal domain (ATD) of the protein.

59 BASIC BIOLOGICAL SCIENCES↗

Porosity Development at Li-Rich Layered Cathodes in All-Solid-State Battery during In Situ Delithiation

Structural evolutions are crucial for determining the performance of high-voltage lithium, manganese-rich layered cathodes. Moreover, interface between electrode and electrolyte plays a critical role in governing ionic transfer in all-solid-state batteries. In this work, we unveil two different types of porous structure in Li 1.2 Ni 0.2 Mn 0.6 O 2 cathode with LiPON solid-state electrolyte. Na-nopores are found near the cathode/electrolyte interface at pristine state, where cation mixing, phase transformation, oxygen loss and Mn reduction are also found. In situ Li + extraction induces the evolution of nanovoids, initially formed near the inter-face then propagated into the bulk. Despite the development of nanovoids, layered structure is conserved, suggesting the nature of nanopores and nanovoids are different and their impact would be divergent. This work demonstrates the intrinsic interfacial layer, as well as the dynamic scenario of nanovoid formation inside high-capacity layered cathode, which help understanding the performance fading in cathodes and offer insights into the all-solid-state battery design.

25 ENERGY STORAGE↗

Reaction Diffusion Modelling of 3D Pillar Electrodes in Single-Catalyst CO 2 Reduction Cascades

Effective electrochemical CO 2 reduction to liquid fuels requires that the local catalytic environment facilitates the desired reactivity, yet a microscopic understanding of this environment is difficult to achieve from experiment alone. In this work, a 3D reaction-diffusion model was developed to explore the effects of electrode surface area and local geometry on the performance of a heterogeneous catalyst that performs a two-step CO 2 reduction cascade reaction to CO and then CH 3 OH under aqueous conditions. Kinetic parameters for the model were inspired by experimental results using a cobalt phthalocyanine (CoPc) catalyst. Three-dimensional architectures composed of arrays of square pillars with varying dimensions and either smooth or periodically modulated surfaces were tested, revealing the extent to which geometry modulates the performance of the cascade reactions. Although structural variations modulate local concentration gradients, we find that electrochemically active surface area predominantly governs the overall cascade reaction. Moreover, the results suggest that supersaturation of CO, with concentrations up to ten-fold higher than the equilibrium solubility limit, might be critical for more efficient conversion to CH 3 OH. For any given geometry, the spatially averaged ratio of [CO] to [CO 2 ] is dictated by the electrochemically active surface area and determines the yield of CH 3 OH. For a fixed surface area, geometries that spatially confine the electrolyte yield moderate local [CO] to [CO 2 ] ratios within small volumes. In contrast, less confining geometries result in a broader distribution of local ratios spread over larger volumes, with both configurations yielding the same spatially averaged [CO] to [CO 2 ] ratio. These insights provide valuable design principles—highlighting the critical importance of surface area and possibly CO supersaturation—for engineering advanced electrode architectures that leverage intermediate trapping and CO supersaturation to enhance overall performance in tandem CO 2 reduction systems.

COMSOL↗