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At least 433 records · Page 24

Tailoring electrode microstructure via ink content to enable improved rated power performance for platinum cobalt/high surface area carbon based polymer electrolyte fuel cells

Improvements in polymer electrolyte fuel cell (PEFC) electrode performance have primarily focused on catalyst and ionomer developments, marginalizing the importance of catalyst ink formulation. In this study, the effect of ink formulation is examined across a series of cathodes comprised of PtCo supported on high surface area carbon (PtCo/ HSC ) and Nafion ionomer using an array of in situ electrochemical and ex situ characterization techniques. In contrast to prior work on Pt/Vu systems, ink water content had little effect on the electrochemically determined ionomer coverage for the PtCo/HSC electrocatalyst examined here. Characterization using nano-scale resolution X-ray computed tomography (nano-CT) demonstrated that water-rich ink formulations lead to a reduction in aggregate size (ionomer + PtCo/HSC), improving local O 2 transport. This understanding, combined with the use of a commercially-available electrocatalyst was used to produced state-of-the-art membrane electrode assemblies with Pt loadings of 0.03/0.08 mg Pt /cm 2 on the anode and cathode respectively, having; i) > 1 A/mg Pt (0.9 V iR-free , 150 kPa, 80 °C, 100% RH, H 2 /O 2 ), ii) 320 mA/cm 2 at 0.8 V, 150 kPa, 80 ° C, 100% RH, H 2 /Air), and iii) > 1 W/cm 2 elec at rated power (0.67 V, 250 kPa, 94 °C, 65% RH, H 2 /Air) or < 0.11 g Pt /kW rated .

25 ENERGY STORAGE↗

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗

Water Imbibition and Oil Recovery in Shale: Dynamics and Mechanisms Using Integrated Centimeter-to-Nanometer-Scale Imaging

Water imbibition, and the associated oil displacement, is an important process in shale oil reservoirs after hydraulic fracturing and in water-based enhanced oil recovery (EOR). Current techniques for water imbibition measurement are mostly “black-box”-type methods. A more explicit understanding of the water imbibition/oil recovery dynamics and geological controls is in demand. In this paper, a multiscale imaging technique that covers centimeter to nanometer scale (i.e., core to pore scale), integrating neutron radiography, microcomputed tomography (micro-CT), and scanning electron microscope (SEM) is applied to investigate the water imbibition depth and rate and the cause of heterogeneity of imbibition in shale samples. The dynamic processes of water imbibition in the 1-in. (25.4-mm) core sample were explicitly demonstrated, and the imbibition along the matrix and imbibition through microfractures are distinguished through neutron radiography image analysis. The causes of observed imbibition heterogeneity were further investigated through micro-CT and SEM image analysis for 1.5-mm diameter miniplug samples from different laminas of the 1-in. core samples. Imbibition depth and rate were calculated on the basis of image analysis as well. Estimation of oil recovery through water imbibition in shale matrix was performed for an example shale field. Here this innovative and integrated multiscale imaging technique provides a “white/gray-box” method to understand water imbibition and water-oil displacement in shale. The wide span of the length scale (from centimeter to nanometer) of this technique enables a more comprehensive, accurate, and specific understanding of both the core-scale dynamics and pore-scale mechanisms of water imbibition, oil recovery, and matrix-fracture interaction.

04 OIL SHALES AND TAR SANDS↗

Experimental Observations of Damage States in Unnotched and Notched 3D Orthogonal Woven Coupons Loaded in Tension

This paper describes a series of unnotched and notched tensile tests on two 3D orthogonal woven architectures loaded in the warp direction. Dogbone specimens were used for the unnotched tests, and open-hole specimens were used for the notched tests. For each architecture and test type, two specimens were loaded under monotonic displacement control to failure, and two specimens were incrementally loaded to failure in five steps. X-ray computed tomography (CT) was used to characterize the woven architecture and defects on each specimen prior to testing. Digital image correlation (DIC) images were obtained from both sides of the specimen throughout the loading and unloading. For the incremental tests, X-ray CT was used to document the damage progression after each load increment. The results for both architectures and test specimens followed a similar pattern where matrix cracks formed perpendicular to the load direction and were primarily located between the stacks of warp tows. Two-piece failure path always occurred perpendicular to the loading direction, along the through-thickness segments of the Z-tows. The combination of stress concentrations due to the specimen geometry, weave geometry, and cut tows created stress concentrations that appear to initiate failure.

Woven materials↗

Multiscale Progressive Failure Analysis of 3D Woven Composites

Application of three-dimensional (3D) woven composites is growing as an alternative to the use of ply-based composite materials. However, the design, analysis, modeling, and optimization of these materials is more challenging due to their complex and inherently multiscale geometries. Herein, a multiscale modeling procedure, based on efficient, semi-analytical micromechanical theories rather than the traditional finite element approach, is presented and applied to a 3D woven carbon–epoxy composite. A crack-band progressive damage model was employed for the matrix constituent to capture the globally observed nonlinear response. Realistic microstructural dimensions and tow-fiber volume fractions were determined from detailed X-ray computed tomography (CT) and scanning electron microscopy data. Pre-existing binder-tow disbonds and weft-tow waviness, observed in X-ray CT scans of the composite, were also included in the model. The results were compared with experimental data for the in-plane tensile and shear behavior of the composite. The tensile predictions exhibited good correlations with the test data. While the model was able to capture the less brittle nature of the in-plane shear response, quantitative measures were underpredicted to some degree.

3D woven composites↗

Material Characterization and Modeling of Room Temperature Vulcanizing Silicone

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive that has successfully been used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also used to bond instrumentation plugs such as temperature and pressure sensors into the heatshields. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Heating RTV has also shown swelling, or intumescence, which can pose unique problems that lead to roughness induced boundary-layer transition, surface oxide formation and contamination of heat shield sensors. Therefore, it is crucial to understand and model the intumescence phenomenon of RTV. As data for RTV material properties is limited, the first step in modeling RTV is to collect material properties such as pyrolysis mass-loss, microstructure change, virgin and char porosity, etc. which was performed in our initial study. Additionally, thermomechanical properties such as Young’s modulus and Poisson ratio are required for modeling the intumescence of RTV, which were taken from literature and the coefficient of thermal expansion was collected using in-situ heating and Micro Computed Tomography (µ-CT) in previous studies. Finally, numerous other properties such as pyrolysis gas properties, virgin and char thermal conductivity and specific heat were compiled from previous experiments and literature into a material database that can be used for simulations. In Porous Material Analysis Toolbox based on OpenFOAM (PATO) [4], structural mechanics coupled with material response was used for simulating the intumescence of RTV as it is heated. However, since the permeability of the material is very low, the pyrolysis gas creates an internal pressure build-up as the material is being heated, significantly contributing to the deformation of the material. To correctly characterize this phenomenon, additional physics models were implemented into PATO's stress analysis solver, and results were compared with RTV dilatometry test data as a preliminary verification case. Future work will include experiments of RTV at the Plasmatron X facility and the in-situ heating cell with µ-CT, and improvement of simulation tools to more accurately model RTV intumescence.

TPS↗

Material Properties and Modeling of Room Temperature Vulcanizing Silicone

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive that has successfully been used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also used to bond instrumentation plugs such as temperature and pressure sensors into the heatshields. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Heating RTV has also shown swelling, or intumescence, which can pose unique problems that lead to roughness induced boundary-layer transition, surface oxide formation and contamination of heat shield sensors. Therefore, it is crucial to understand and model the intumescence phenomenon of RTV. As data for RTV material properties is limited, the first step in modeling RTV is to collect material properties such as pyrolysis mass-loss, microstructure change, virgin and char porosity, etc. which was performed in our initial study. Additionally, thermomechanical properties such as Young’s modulus and Poisson ratio are required for modeling the intumescence of RTV, which were taken from literature and the coefficient of thermal expansion was collected using in-situ heating and Micro Computed Tomography (µ-CT) in previous studies. Finally, numerous other properties such as pyrolysis gas properties, virgin and char thermal conductivity and specific heat were compiled from previous experiments and literature into a material database that can be used for simulations. In Porous Material Analysis Toolbox based on OpenFOAM (PATO) [4], structural mechanics coupled with material response was used for simulating the intumescence of RTV as it is heated. However, since the permeability of the material is very low, the pyrolysis gas creates an internal pressure build-up as the material is being heated, significantly contributing to the deformation of the material. To correctly characterize this phenomenon, additional physics models were implemented into PATO's stress analysis solver, and results were compared with RTV dilatometry test data as a preliminary verification case. Future work will include experiments of RTV at the Plasmatron X facility and the in-situ heating cell with µ-CT, and improvement of simulation tools to more accurately model RTV intumescence.

PATO↗

Endothermic Charge Separation Occurs Spontaneously in Non–Fullerene Acceptor/Polymer Bulk Heterojunction

Organic photovoltaics (OPVs) based on non-fullerene acceptors (NFAs) have achieved a power conversion efficiency close to 20%. These NFA OPVs can generate free carriers efficiently despite a very small energy level offset at the donor/acceptor interface. Why these NFAs can enable efficient charge separation (CS) with low energy losses remains an open question. Here, the CS process in the PM6:Y6 bulk heterojunction is probed by time-resolved two-photon photoemission spectroscopy. It is found that the CS, the conversion from bound charge transfer (CT) excitons to free carriers, is an endothermic process with an enthalpy barrier of 0.15 eV. The CS can occur spontaneously despite being an endothermic process, which implies that it is driven by entropy. It is further argued that the morphology of the PM6:Y6 film and the anisotropic electron delocalization restrict the electron and hole wavefunctions within the CT exciton such that they can primarily contact each other through point-like junctions. Furthermore, this configuration can maximize the entropic driving force.

36 MATERIALS SCIENCE↗

Peptide‐Induced Ferroelectricity in Charge‐Transfer Supramolecular Materials

Organic ferroelectrics are of great interest in sustainable energy conversion, information storage, flexible electronics, and potential biomedical applications as soft implants, among many other applications. Despite their broad potential, the development of organic ferroelectrics has remained limited, with only a few known examples in solid-state systems, primarily due to the lack of well-established design strategies compared to inorganic systems. Bio-inspired supramolecular chemistry offers a path to create functional nanostructures that are water-processable and biocompatible. We report here on supramolecular charge transfer (CT) systems in which peptides are covalently linked to dyads of electron-donating and electron-accepting moieties, creating amphiphiles that self-assemble into nanoscale ribbons in water. The peptide chirality-induced symmetry breaking in these crystalline nanostructures not only results in second harmonic activity but also generates ferroelectric behavior across multiple CT systems, demonstrating a versatile supramolecular approach to the design of new organic ferroelectrics. Furthermore, culturing primary neuron cells on coatings of the ferroelectric materials promoted axonal growth and enhanced action potentials, indicating improved neuronal maturity facilitated by the polar structure of the ferroelectric nanomaterials. The supramolecular strategy used here holds promise to create new water-processable ferroelectric biomaterials, opening avenues for innovative applications in cell charge transfer, neuronal axon growth, peptide symmetry breaking, self-assembling peptides, supramolecular ferroelectrics, proliferation, and bioelectronics.

charge transfer↗

Linking Phase Behavior to Performance Parameters in Non-Fullerene Acceptor Solar Cells

Performance of nonfullerene-based organic solar cells is largely dependent on the donor:acceptor blend morphology, which is initially tuned by composition. However, morphological design rules are difficult to identify due to the complex relationship between composition-dependent phase behavior and performance properties. In this study, the authors are able to establish a direct link between PM6:Y6 film morphology and device properties by combining grazing-incidence wide-angle X-ray scattering with highly sensitive Fourier transform photocurrent spectroscopy. By analyzing properties across the full composition range, interfacial microstructure and the corresponding charge transfer (CT) states are identified and direct structure–property relationships are established. Here the results indicate that open-circuit voltage is controlled by the CT state at amorphous-PM6:crystalline-Y6 interfaces. Crystalline Y6 is found to increase both transport and non-radiative recombination, suggesting that morphological tradeoffs may be necessary for overall device optimization.

14 SOLAR ENERGY↗

Dispersive Charge Transfer State Electroluminescence in Organic Solar Cells

Abstract The notion of quasi‐equilibrium is central to most solar cells; however, it has been questioned in organic photovoltaics (OPVs) owing to strong energetic disorder that frustrates efficient relaxation of electrons and holes within their respective density of states (DOS). Here, modulation electroluminescence (EL) spectroscopy is applied to OPVs and it is found that the frequency response of charge transfer (CT) state EL on the high energy side of the spectrum differs from that of the low energy side. This observation confirms that static disorder contributes substantially to the linewidth of the steady‐state EL spectrum and is unambiguous proof that the distribution of CT states formed by electrical injection in the dark is not in quasi‐equilibrium. These results emphasize the need for caution when analyzing OPV cells on the basis of reciprocity models that assume quasi‐equilibrium holds, and highlight a new method to study this unusual aspect of OPV operation.

14 SOLAR ENERGY↗

Enhancing Li + Transport in NMC811||Graphite Lithium–Ion Batteries at Low Temperatures by Using Low–Polarity–Solvent Electrolytes

LiNi x Co y MnzO 2 (x+y+z=1)||graphite lithium-ion battery (LIB) chemistry promises practical applications. However, its low-temperature (≤ –20°C) performance is poor because the increased resistance encountered by Li + transport in and across the bulk electrolytes and the electrolyte/electrode interphases induces capacity loss and battery failures. Though tremendous efforts have been made, there is still no effective way to reduce the charge transfer resistance (R ct ) which dominates low-temperature LIBs performance. In this work, we propose a strategy of using low-polarity-solvent electrolytes which have weak interactions between the solvents and the Li + to reduce R ct , achieving facile Li + transport at sub-zero temperatures. The exemplary electrolyte enables LiNi 0.8 Mn 0.1 Co 0.1 O 2 ||graphite cells to deliver a capacity of ≈113 mAh g –1 (98% full-cell capacity) at 25°C and to remain 82% of their room-temperature capacity at –20°C without lithium plating at 1/3C. They also retain 84% of their capacity at –30°C and 78% of their capacity at –40°C and show stable cycling at 50°C.

25 ENERGY STORAGE↗

Engineering Clostridium cellulovorans for highly selective n ‐butanol production from cellulose in consolidated bioprocessing

Abstract Cellulosic n ‐butanol from renewable lignocellulosic biomass has gained increased interest. Previously, we have engineered Clostridium cellulovorans , a cellulolytic acidogen, to overexpress the bifunctional butyraldehyde/butanol dehydrogenase gene adh E2 from C. acetobutylicum for n ‐butanol production from crystalline cellulose. However, butanol production by this engineered strain had a relatively low yield of approximately 0.22 g/g cellulose due to the coproduction of ethanol and acids. We hypothesized that strengthening the carbon flux through the central butyryl‐CoA biosynthesis pathway and increasing intracellular NADH availability in C. cellulovorans adh E2 would enhance n ‐butanol production. In this study, thiolase ( thl A CA ) from C. acetobutylicum and 3‐hydroxybutyryl‐CoA dehydrogenase ( hbd CT ) from C. tyrobutyricum were overexpressed in C. cellulovorans adh E2 to increase the flux from acetyl‐CoA to butyryl‐CoA. In addition, ferredoxin‐NAD(P) + oxidoreductase ( fnr ), which can regenerate the intracellular NAD(P)H and thus increase butanol biosynthesis, was also overexpressed. Metabolic flux analyses showed that mutants overexpressing these genes had a significantly increased carbon flux toward butyryl‐CoA, which resulted in increased production of butyrate and butanol. The addition of methyl viologen as an electron carrier in batch fermentation further directed more carbon flux towards n ‐butanol biosynthesis due to increased reducing equivalent or NADH. The engineered strain C. cellulovorans adh E2‐ fnr CA ‐ thl A CA ‐ hbd CT produced n ‐butanol from cellulose at a 50% higher yield (0.34 g/g), the highest ever obtained in batch fermentation by any known bacterial strain. The engineered C. cellulovorans is thus a promising host for n ‐butanol production from cellulosic biomass in consolidated bioprocessing.

Bao, Teng↗

Ability of x‐ray computed tomography to resolve critical flaw size in laser‐based, paste stereolithography ceramic printing of alumina

Abstract Complex alumina parts were printed using vat photopolymerization (VPP), which is a stereolithography‐based additive manufacturing (AM) technique used to shape ceramic preforms, or green parts. The critical flaw size was determined using classical fracture mechanics techniques. The strength and fracture toughness were measured and compared to flaws detected in x‐ray computed tomography (XCT or CT) distributions as well as the fracture surfaces. The strength was lower compared traditionally made alumina, and that is due to layering effects, slurry defects, and printing defects. The critical flaw size from fracture mechanics was 206 µm. XCT has high enough resolution to detect the critical flaw size and much smaller features, where the average flaw size observed in CT scans was around 80–100 µm. The fracture surfaces indicate that flaws causing failure are larger than that of the critical flaw size (∼300 µm), but fracture surfaces do not show definitive features compared to traditionally made ceramics. Since XCT can observe flaws smaller than the critical flaw size, this method can be used as a screening technique.

36 MATERIALS SCIENCE↗

Damage of prismatic lithium‐ion cells subject to bending: Test, model, and detection

Abstract The mechanically induced internal short circuit (ISC) is one of the major safety concerns of lithium‐ion batteries. Mechanical abuse tests are often performed to evaluate the integrity and safety of lithium‐ion batteries under mechanical loadings. Except for the widely explored compression‐dominated indentation tests, bending is another typical real‐world loading condition that is tension‐dominated. To investigate the mechanical damage and ISC behavior of batteries under bending, we carried out controlled three‐point bending tests in four progressive steps on prismatic battery cells with maximum deflections ranging from 38% to 76% of the cell thickness. None of the tested cells experienced an ISC. We then conducted 3D X‐ray computed tomography (CT) scanning on the bent cells after unloading. X‐ray CT images showed three out of the four tested cells have extensive cracking in the electrode layers at the bottom side (opposite to the loading head). This indicates that cracking does not necessarily lead to an ISC under bending. Electrochemical impedance spectroscopy was also measured on the bent cells and substantial changes were observed. Both the bulk resistance and charge‐transfer resistance increased significantly after bending, which could influence the battery performance and lifespan. We then developed a detailed finite (FE) element model to further investigate the mechanical deformation and failure mechanisms. The FE model successfully predicts the load–displacement response and reproduces the deformation patterns. The findings and the FE model developed in the present study provide useful insights and tools for the battery structure and crash safety design. image

25 ENERGY STORAGE↗

Modeling the impact of measured and projected climate and management systems on agricultural fields: Surface runoff, soil moisture, and soil erosion

Abstract As global climate change poses a challenge to crop production, it is imperative to prioritize effective adaptation of agricultural systems based on a scientific understanding of likely impacts. In this study, we applied an integrated watershed modeling framework to examine the impacts of projected climate on runoff, soil moisture, and soil erosion under different management systems in Central Oklahoma. The proposed model uses measured climate data and three downscaled ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) at the water resources and erosion watershed to understand the impact of climate change and various climate conditions under three management systems: (1) continuous winter wheat (Triticum aestivum) under conventional tillage (WW‐CT; baseline system), (2) continuous winter wheat under no‐till (WW‐NT), and (3) cool and warm season forage cover crop mixes under no‐till (CC‐NT). The study indicates that the occurrence of agricultural drought is projected to increase while erosion rates will remain unchanged under the WW‐CT. In contrast, climate simulations imposed on the WW‐NT and CC‐NT systems significantly reduce runoff and sediment while preserving soil moisture levels. Especially, implementing the CC‐NT system can bolster food security and foster sustainable farming practices in Central Oklahoma in the face of a changing climate.

Environmental Sciences & Ecology↗

Engineered selective biotoxin‐binding hydrogels for toxin sequestration

The development of synthetic selective membranes that separate materials of similar sizes, charges, and/or polarities remains a difficult challenge, and looking towards biology provides inspiration for new designs. In this work, a series of cholera toxin binding peptides (CTBPs) are identified, spanning a range of binding inhibitions, and integrated into chemically cross-linked cholera toxin binding gels (CTBGs) via thiol-Michael polycondensation reactions. All gels demonstrate rheological profiles consistent with elastic solids. The CTBGs are probed via small-angle neutron scattering and exhibit a correlation length, ξ, smaller than most proteins (1.3–2.5 nm). Thus, an effective entropic mesh is formed to block non-targeted proteins. However, the CTBGs have a dynamic mesh size, Ξ, that is larger than cholera toxin (CT) to allow the transport of target proteins. The CTBGs with the highest binding inhibitions both show high selectivity and permeation of CT, rejecting all other tested proteins. In total, two new highly selective CTBGs are synthesized and validated for use in cholera toxin remediation. Together, this platform demonstrates the wide applicability of selectively-diffusive materials for difficult separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development of limited-view tomography for measurement of Spray G plume direction and liquid volume fraction

Abstract The method for direct injection of fuel in the cylinder of an IC engines is important to high-efficiency and low-emission performance. Optical spray diagnostics plays an important role in understanding plume movement and interaction for multi-hole injectors, and providing baseline understanding used for computational optimization of fuel delivery. Traditional planar or line-of-sight diagnostics fail to capture the liquid distribution because of optical thickness concerns. This work proposes a high-speed (67 kHz) extinction imaging technique at various injector rotations coupled to computed tomography (CT) for time-resolved reconstruction of liquid volume fraction in three dimensions. The number of views selected and processing were based on synthetic (modeled) liquid volume fraction data where extinction and CT adequately reconstructed each plume. The exercise showed that for an 8-hole, symmetric-design injector (ECN Spray G), only three different views are enough to reproduce the direction of each plume, and particularly the mean plume direction. Therefore, the number of views was minimized for experiments to save expense. Measurements applying this limited-view technique confirm plume–plume variations also detected with mechanical patternation, while providing better spatial and temporal resolution than achieved previously. Uncertainties due to the limited view within pressurized spray chambers, the droplet size, and optically thick regions are discussed. Graphic abstract

42 ENGINEERING↗