Structural and Dynamical Properties of Potassium Dodecahydro-monocarba-closo-dodecaborate: KCB[subscript 11]H[subscript 12]
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Concentrated solutions of Li salts in acetonitrile are promising alternative electrolytes for the next generation of Li batteries as they may exhibit superior electrochemical properties. However, the reduced mobility of the chemical species is a barrier yet to be overcome, and for this, we explore the utilization of acetone as a cosolvent. Although acetone is a polar compound, we find that its addition to the LiTFSI/acetonitrile solution does not follow the trends expected for a simple dilution process. At a low concentration, acetone subtly shifts acetonitrile from the first to extended solvation sheaths of the ions. Still, most of the original structure of the solution is preserved, and mobile high-concentration clusters are formed in the solution. At higher concentrations, the cosolvation promotes cation–anion interactions but with a different nature from those in the original solution and still allows for a further increase in conductivity. Additionally, the non-coordinating fraction of acetonitrile acquires features resembling the pure solvent, which is a possible additional facilitating factor for ionic diffusion.
Atomic-precision advanced manufacturing enables unique silicon quantum electronics built on quantum dots fabricated from small numbers of phosphorus dopants. The number of dopant atoms comprising a dot plays a central role in determining the behavior of charge and spin confined to the dots and thus overall device performance. Here in this work, we use both theoretical and experimental techniques to explore the combined impact of lithographic variation and stochastic kinetics on the number of P incorporations in quantum dots made using these techniques and how this variation changes as a function of the size of the dot. Using a kinetic model of PH3 dissociation augmented with novel reaction barriers, we demonstrate that for a 2 × 3 silicon dimer window the probability that no donor incorporates goes to zero, allowing for certainty in the placement of at least one donor. However, this still comes with some uncertainty in the precise number of incorporated donors (either one or two), and this variability may still impact certain applications. We also examine the impact of the size of the initial lithographic window, finding that the incorporation fraction saturates to δ-layer-like coverage as the circumference-to-area ratio decreases. We predict that this incorporation fraction depends strongly on the dosage of the precursor and that the standard deviation of the number of incorporations scales as ~√n, as would be expected for a sequence of largely independent incorporation events. Finally, we characterize an array of 36 experimentally prepared multidonor 3 × 3 nm lithographic windows with scanning tunneling microscopy, measuring the fidelity of the lithography to the desired array and the final location of PH x fragments within these lithographic windows. We use our kinetic model to examine the expected variability due to the observed lithographic error, predicting a negligible impact on incorporation statistics. We find good agreement between our model and the inferred incorporation locations in these windows from scanning tunneling microscope measurements.
As thin-film cadmium telluride (CdTe) solar cells gain prominence, one particular challenge is optimizing contacts and their interfaces to transfer charge without losses in efficiency. Back contact recombination is still significant and will prevent CdTe solar technology from reaching its full potential in device efficiency, and transparent back contacts have not been developed for bifacial solar technology or multijunction solar cells. To address these challenges, here we investigate sputtered Cu x Zn 1– x S as a p-type semi-transparent back contact material to thin-film polycrystalline CdTe solar cells at Cu concentrations x = 0.30, 0.45, and 0.60. This material is selected for its high hole conductivity (160–2120 S cm –1 ), wide optical band gap (2.25–2.75 eV), and variable ionization potential (approximately 6–7 eV) that can be aligned to that of CdTe. We report that without device optimization, CdTe solar cells with these Cu x Zn 1– x S back contacts perform as well as control cells with standard ZnTe:Cu back contacts. We observe no reduction in external quantum efficiency, low contact barrier heights of approximately 0.3 eV, and carrier lifetimes on par with those of baseline CdTe. These cells are relatively stable over one year in air, with V OC and efficiency of the x = 0.30 cell decreasing by only 1 and 3%, respectively. Using scanning electron microscopy and scanning transmission electron microscopy to investigate the Cu x Zn 1– x S/CdTe interface, we demonstrate that the Cu x Zn 1– x S layer segregates into a bilayer of Cu-Te-S and Zn-Cd-S, and thermodynamic reaction calculations support these findings. Despite its bilayer formation, the back contact still functions well. This investigation explains some of the physical mechanisms governing the device stack, inspires future work to understand interfacial chemistry and charge transfer, and elicits optimization to achieve higher-efficiency CdTe cells.
Commercialization and scale-up of organic solar cells (OSCs) using industrial solution printing requires maintaining maximum performance at active-layer thicknesses >400 nm – a characteristic still not generally achieved in non-fullerene acceptor OSCs. NT812:PC71BM is a rare system whose performance increases up to these thicknesses due to highly suppressed charge recombination relative to the classic Langevin model. The suppression in this system, however, uniquely depends on device processing, pointing towards the role of nano-morphology. We investigate the morphological origins of this suppressed recombination by combining results from a suite of X-ray techniques. We are surprised to find that while all investigated devices are composed of pure, similarly aggregated nanodomains, Langevin reduction factors can still be tuned from ~2 to >1000. This indicates that pure aggregated phases are insufficient for non-Langevin (reduced) recombination. Instead, we find that large well-ordered conduits and, in particular, sharp interfaces between domains appear to help to keep opposite charges separated and percolation pathways clear for enhanced charge collection in thick active layers. To our knowledge, this is the first quantitative study to isolate donor/acceptor interfacial width correlated to non-Langevin charge recombination. Furthermore, this new structure-property relationship will be key to successful commercialization of printed OSCs at scale.
Catalytic oxidation of methane (CH 4 ) over nonprecious Ni/CeO 2 catalysts has received a lot of attention due to the large natural gas reserves found in North America and the prohibitive cost of palladium-based catalysts, commonly used for CH 4 oxidation. However, the catalytic mechanism of CH 4 oxidation over Ni/CeO 2 still remains unclear. Moreover, the parameters affecting the reaction rates, the interaction between nickel and CeO 2 , and the reaction intermediates are still not well understood. In this study, kinetic model fitting, CH 4 temperature-programmed reduction-mass spectroscopy (CH 4 TPR-MS), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and density functional theory (DFT) calculations were combined to elucidate the mechanism of complete oxidation of CH 4 over Ni/CeO 2 . CH 4 TPR-MS showed that the complete oxidation of CH 4 over Ni/CeO 2 requires 55–120 °C lower compared to bare CeO 2 or Ni/quartz sand; complete oxidation of CH 4 took place when the surface oxygen species were abundant, while partial oxidation products (CO, H 2 ) were formed when the oxygen species were depleted. In situ DRIFTS showed that CH 3 , CH 2 , CO, and CO 2 were formed after CH 4 activation over Ni/CeO 2 , while CH 3 O species were not observed. Combining those findings with kinetic model fitting, a redox Mars–van Krevelen (MvK) mechanism showed the best description of the experimental observations. The MvK mechanism involves the reaction of dissociated oxygen species with gas-phase CH 4 while water inhibits the reaction rate by adsorbing on the oxidized sites. Moreover, CH 4 activation leads to the reduction of the active sites and oxygen vacancy formation followed by reoxidation of the active sites by gas-phase O 2 . A CH 4 oxidation reaction pathway over Ni/CeO 2 is proposed by DFT calculations. In summary, the findings shown here suggest that CH 4 oxidation over Ni/CeO 2 follows a redox MvK mechanism and provides guidance for the rational design of non-precious-metal catalysts for CH 4 oxidation reactions.
Oxidative desulfurization (ODS) plays critical roles in the production of high-quality sulfur impurity-free fuels, especially procedures using molecular oxygen as the sole oxidant. However, the state-of-the-art systems still rely on noble metal nanocatalysts, with deactivation issues caused by coking and sintering still present. In this work, leveraging the merits of single-atom catalysts (SACs) with earth-abundant metal cores and robust nanoporous supports, a series of catalysts composed of homogeneously distributed single chromium atoms anchored on multiwalled carbon nanotubes were fabricated and deployed to catalyze the aerobic ODS transformation. Adopting aromatic sulfur compound (ASC)-containing alkanes as a model system with molecular oxygen as the oxidant, efficient oxygen-to-active O 2 •– transformation and subsequent ASCs-to-sulfone conversion have been achieved, with the former benefiting from the chromium-active sites and the latter arising from the robust, nanoporous, and π-conjugated architecture of the supports. The attractive catalytic performance and cycling stability of the chromium-based SACs make them promising candidates in practical sulfur species removal from liquid fuels, supplying an alternative guidance on the catalyst design toward cost-effective and energy-efficient ODS procedures.
Mixed tin–lead halide perovskite solar cells have promising power conversion efficiencies, but long-term stability is still a challenge. Here, we examine the stability of a 60:40 tin–lead perovskite to better understand diminished device performance upon thermal treatment, both in ambient and inert atmosphere. Operando X-ray diffraction shows a stable bulk structure of the perovskite absorber, leading to the hypothesis that surface chemistry dominates the degradation mechanism. X-ray photoelectron spectroscopy reveals two new observations post-thermal annealing that accompany previously reported Sn 4+ evolution: (i) the formation of I 3 – intermediates preceding I 2 loss at the surface and (ii) evidence of under-coordinated tin and lead surface sites (Sn δ<2+ and Pb δ<2+ , respectively) in inert and ambient conditions. These two species indicate an activated corrosion (i.e., both oxidation and reduction) process at the surface as a possible chemical pathway for degradation, which is expected to be accelerated under operando voltage and light biases.
Single-crystal Ni-rich Li[Ni x Mn y Co 1-x-y ]O 2 (SC-NMC) cathodes represent a promising approach to mitigate the cracking issue of conventional polycrystalline cathodes. However, many reported SC-NMC cathodes still suffer from unsatisfactory cycling stability, particularly under high charge cutoff voltage and/or elevated temperature. Herein, we report an ultraconformal and durable poly(3,4-ethylenedioxythiophene) (PEDOT) coating for SC-NMC cathodes using an oxidative chemical vapor deposition (oCVD) technique, which significantly improves their high-voltage (4.6 V) and high-temperature operation resiliency. The PEDOT coated SC LiNi 0.83 Mn 0.1 Co 0.07 O 2 (SC-NMC83) delivers an impressive capacity retention rate of 96.7% and 89.5% after 100 and 200 cycles, respectively. Significantly, even after calendar aging at 45 degrees C and 4.6 V, the coated cathode can still retain 85.3% (in comparison with 59.6% for the bare one) of the initial capacity after 100 cycles at a 0.5 C rate. Synchrotron X-ray experiments and interface characterization collectively reveal that the conformal PEDOT coating not only effectively stabilizes the crystallographic structure and maintains the integrity of the particles but also significantly suppresses the electrolyte's corrosion, resulting in improved electrochemical/thermal stability. Our findings highlight the promise of an oCVD PEDOT coating for single-crystal Ni-rich cathodes to meet the grand challenge of high-energy batteries under extreme conditions.
To capture protein conformational transitions using molecular dynamics (MD), several simulation resolutions covering different spatial and temporal scales are typically needed. All-atom (AA) simulations provide fine resolution, but are computationally infeasible for large systems over longer durations. Coarse-grained (CG) and ultra-coarse-grained (UCG) models have a lower resolution and computational cost while still being able to conserve essential protein features. Prior work on a Multiscale Machinelearned Modeling Infrastructure (MuMMI) combined both AA and CG simulations to study RAS-RAF protein interactions, leveraging CG models for longer time scales and using AA to investigate unusual conformations in greater detail. However, MuMMI is still resource-intensive, and this study aims to maximize exploration of the protein conformational space while reducing computational cost. In this paper, we build on prior work that integrates UCG models based on heterogeneous elastic network modeling (hENM) into the MuMMI workflow. We demonstrate that UCG models enable accurate sampling of protein conformations, focusing on simulating RAS-RAF protein interactions. Using higher-resolution CG Martini simulation data, we can automatically refine intramolecular interactions in UCG models. We present a scalable Python package that uses fluctuations observed in higher-resolution CG Martini simulations to estimate bond coefficients of the UCG model. We built novel machine learning-based backmapping methods to recover more detailed CG Martini structures from UCG structures, using diffusion models to learn the mapping between scales. Finally, we present UCG-mini-MuMMI, an accessible and less compute-intensive version of MuMMI as a resource for the scientific community. Incorporating UCG models into MD studies is applicable to a broad range of systems and proteins, and our study offers insights into the advantages and limitations of these methods.
The conversion of lignocellulosic biomass to biofuels and bioproducts is limited by small inhibitory molecules generated during the pretreatment process. The diverse compounds within the cell wall hydrolysate including aldehydes, carboxylic acids, phenolics, and alcohols inhibit microbial growth by disrupting microbial membranes. Although Zymomonas mobilis combines high ethanol productivity with hopanoid-rich membranes that confer solvent tolerance, hydrolysate compounds still inhibit microbial growth. One proposed mitigation strategy is to pump these molecules out through active transport processes, reducing direct toxicity. However, if passive permeation rates are high, active transport would create a futile cycle where the exported molecules diffuse back in, creating a net drag on fitness. To investigate this hypothesis, we measure the passive permeation for thirty-three lignocellulose derived compounds using atomistic molecular dynamics simulations with enhanced sampling. Permeability coefficients determined spanned more than eight orders of magnitude driven largely by the balance between hydrophobicity and polarity. Hydrophobic inhibitors such as aromatic acids, aldehydes, and short chain alcohols readily partitioned into the membrane and showed high permeability consistent with rapid passive influx and strong toxicity. Most polar molecules have lower but still appreciable permeation rates, with only the most polar sugars having low permeabilities. By integrating these predictions together with hydrolysate composition information, we find that most of these molecules are so permeable that futile cycles where passive permeation overwhelms efflux is highly likely. These findings provide a predictive framework for strain engineering, highlighting that, for highly permeable inhibitors, reducing extracellular inhibitor concentrations through hydrolysate detoxification, pretreatment optimization, or dilution may be necessary to mitigate futile cycling and improve microbial productivity in industrial biorefineries.
Understanding structural stability and phase transformation of nanoparticles under high pressure is of great scientific interest, as it is one of the crucial factors for design, synthesis, and application of materials. Even though high-pressure research on nanomaterials has been widely conducted, their shape-dependent phase transition behavior still remains unclear. Examples of phase transitions of CdS nanoparticles are very limited, despite the fact that it is one of the most studied wide band gap semiconductors. Here we have employed in-situ synchrotron wide-angle X-ray scattering (WAXS) and transmission electron microscopy (TEM) to investigate the high-pressure behaviors of CdS nanoparticles as a function of particle shapes. We observed that CdS nanoparticles transform from wurtzite to rocksalt phase at elevated pressure in comparison to their bulk counterpart. Phase transitions also vary with particle shape—rod-shaped particles show a partially reversible phase transition and the onset of the structural phase transition pressure decreases with decreasing surface-to-volume ratios, while spherical particles undergo irreversible phase transition with relatively low phase transition pressure. Additionally, TEM images of spherical particles exhibited sintering-induced morphology change after high-pressure compression. Calculations of the bulk modulus reveals that spheres are more compressible than rods in the wurtzite phase. These results indicate that the shape of the particle plays an important role in determining their high-pressure properties. Our study provides important insights into understanding of the phase-structure-property relationship, guiding future design and synthesis of nanoparticles for promising applications.
The porosity of ligand shells of colloidal quantum dots (QDs) can influence the overall rate and yield of charge transfer processes occurring at their surfaces. However, the density of ligand shells on QDs can also influence their colloidal and photochemical stability. We used time-resolved infrared spectroscopy to show that photoinduced ligand detachment, the tendency for certain ligands to detach from QD surfaces when the nanocrystals are promoted to their excitonic excited states, can be used to transiently enhance the porosity of oleic acidpassivated CdSe QDs in solution. Furthermore, we synthesized CdSe QDs with varying ligand shell densities to examine the corresponding influence that van der Waals interactions among ligands have on the yield of photoinduced ligand detachment and the time scale on which ligands return to QD surfaces. We observed that oleic acid ligands on CdSe QDs with lower shell densities have a higher probability of escape for longer periods of time. Despite this, oleic acid ligands on fully passivated CdSe QDs are still able to photodetach, resulting in a transient increase of their ligand shell porosity. In contrast, QDs with multilayer ligand coronas exhibit negligible photoinduced ligand detachment because the outer molecular layers introduce a type of cage effect, preventing the escape of the interior ligands. Our findings suggest the intriguing possibility that photoinduced ligand detachment can be used to transiently decrease the density of ligand shells of QDs to facilitate charge transfer processes while still allowing them to be fully passivated between excitation events for photochemical and colloidal stability.
Abstract Since their introduction 22 years ago, lightning mapping arrays (LMA) have played a central role in the investigation of lightning physics. Even in recent years with the proliferation of digital interferometers and the introduction of the LOw Frequency ARray (LOFAR) radio telescope, LMAs still play an important role in lightning science. LMA networks use a simple windowing technique that records the highest pulse in either 80 μs or 10 μs fixed windows in order to apply a time‐of‐arrival location technique. In this work, we develop an LMA‐emulator that uses lightning data recorded by LOFAR to simulate an LMA, and we use it to test three new styles of pulse windowing. We show that they produce very similar results as the more traditional LMA windowing, implying that LMA lightning mapping results are relatively independent of windowing technique. In addition, each LMA station has its GPS‐conditioned clock. While the timing accuracy of GPS receivers has improved significantly over the years, they still significantly limit the timing measurements of the LMA. Recently, new time‐of‐arrival techniques have been introduced that can be used to self‐calibrate systematic offsets between different receiving stations. Applying this calibration technique to a set of data with 32 ns uncertainty, observed by the Colorado LMA, improves the timing uncertainty to 19 ns. This technique is not limited to LMAs and could be used to help calibrate future multi‐station lightning interferometers.
Abstract Cities are implementing additional urban green as a means to capture CO 2 and become more carbon neutral. However, cities are complex systems where anthropogenic and natural components of the CO 2 budget interact with each other, and the ability to measure the efficacy of such measures is still not properly addressed. There is still a high degree of uncertainty in determining the contribution of the vegetation signal, which furthermore confounds the use of CO 2 mole fraction measurements for inferring anthropogenic emissions of CO 2 . Carbonyl sulfide (OCS) is a tracer of photosynthesis which can aid in constraining the biosphere signal. This study explores the potential of using OCS to track the urban biosphere signal. We used the Sulfur Transport and dEposition Model (STEM) to simulate the OCS concentrations and the Carnegie Ames Stanford Approach ecosystem model to simulate global CO 2 fluxes over the Bay Area of San Francisco during March 2015. Two observation towers provided measurements of OCS and CO 2 : The Sutro tower in San Francisco (upwind from the area of study providing background observations), and a tower located at Sandia National Laboratories in Livermore (downwind of the highly urbanized San Francisco region). Our results show that the STEM model works better under stable marine influence, and that the boundary layer height and entrainment are driving the diurnal changes in OCS and CO 2 at the downwind Sandia site. However, the STEM model needs to better represent the transport and boundary layer variability, and improved estimates of gross primary productivity for characterizing the urban biosphere signal are needed.
In order to improve the physical consistency between shallow and deep convection, we modify the deep convective closure in the Community Atmosphere Model version 5 (CAM5) coupled with a third-order turbulence closure parameterization (i.e., Cloud Layers Unified by Binormals; CLUBB). The revised closure reserves a portion of the total convective available potential energy for shallow convection via utilizing the heating and moistening profiles from CLUBB to distribute moisture and energy between shallow and deep convection. Simulations at two resolutions (i.e. 2° and 0.5°, respectively) are conducted to investigate the impacts of convective closure on the simulated precipitation diurnal variations. Results from low-resolution simulations show that the revised closure suppresses deep convection until the lower troposphere is sufficiently moistened by shallow convection, which improves the precipitation diurnal variation simulations compared to the default closure, with the precipitation diurnal peak over tropical lands delayed from 12LST to 19LST. The revised closure better simulates the diurnal variations for precipitation over the Asian monsoon region, such as the delayed precipitation onset, but still fails to well capture the nighttime peak for precipitation there. This deficiency is alleviated to some extent when applying the revised closure in highresolution simulations, but nighttime precipitation is still underestimated probably because key processes responsible for nighttime convection are missing. Altogether, our results indicate that establishing the consistency between shallow and deep convection is critical for the precipitation diurnal cycle simulations.
Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.
Convections still need to be parameterized in general circulation models (GCMs) in the coming decades. Performances of GCMs are significantly influenced by the convection schemes used. In contrast to most conventional cloud models that ignore in-cloud inhomogeneities, a new convective cloud model explicitly considering in-cloud inhomogeneities is developed. The new model adopts a single bulk plume approach, but divides the plume into a series of interacting sub-plumes in order to mimic the transition from the plume core to its edges. We implemented the new cloud model in NCAR Community Atmosphere Model version 5.0 (CAM5) and evaluated its performance. Single-column tests show a stronger mass flux profile and low-level detrainment with the new model. In global simulations, the long-lasting wet bias in the tropical free troposphere of CAM5 is alleviated. Spatial pattern and intensity distribution of precipitation is improved, but the global hydrological cycle is slightly over-enhanced. The diurnal cycle of tropical precipitation is also better captured though the precipitation peak still occurs earlier than the observations and the amplitude of the cycle tends to weaken. MJO simulation is slightly improved with the new scheme. In addition, the new cloud model generated more tropical cyclones, in better agreement with observations.