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Rust transformation/rust compatible primers

Proper surface preparation has been the key to obtain good performance by a surface coating. The major obstacle in preparing a corroded or rusted surface is the complete removal of the contaminants and the corrosion products. Sandblasting has been traditionally used to remove the corrosion products before painting. However, sandblasting can be expensive, may be prohibited by local health regulations and is not applicable in every situation. To get around these obstacles, Industry developed rust converters/rust transformers and rust compatible primers (high solids epoxies). The potential use of these products for military equipment led personnel of the Belvoir Research, Development and Engineering Center (BRDEC) to evaluate the commercially available rust transformers and rust compatible primers. Prior laboratory experience with commercially available rust converters, as well as field studies in Hawaii and Puerto Rico, revealed poor performance, several inherent limitations, and lack of reliability. It was obvious from our studies that the performance of rust converting products was more dependent on the amount and type of rust present, as well as the degree of permeability of the coating, than on the product's ability to form an organometallic complex with the rust. Based on these results, it was decided that the Military should develop their own rust converter formulation and specification. The compound described in the specification is for use on a rusted surface before the application of an organic coating (bituminous compounds, primer or topcoat). These coatings should end the need for sandblasting or the removing of the adherent corrosion products. They also will prepare the surface for the application of the organic coating. Several commercially available rust compatible primers (RCP) were also tested using corroded surfaces. All of the evaluated RCP failed our laboratory tests for primers.

Emeric, Dario A.

Formal Techniques for Synchronized Fault-Tolerant Systems

We present the formal verification of synchronizing aspects of the Reliable Computing Platform (RCP), a fault-tolerant computing system for digital flight control applications. The RCP uses NMR-style redundancy to mask faults and internal majority voting to purge the effects of transient faults. The system design has been formally specified and verified using the EHDM verification system. Our formalization is based on an extended state machine model incorporating snapshots of local processors clocks.

DiVito, Ben L.

Provable Transient Recovery for Frame-Based, Fault-Tolerant Computing Systems

We present a formal verification of the transient fault recovery aspects of the Reliable Computing Platform (RCP), a fault-tolerant computing system architecture for digital flight control applications. The RCP uses NMR-style redundancy to mask faults and internal majority voting to purge the effects of transient faults. The system design has been formally specified and verified using the EHDM verification system. Our formalization accommodates a wide variety of voting schemes for purging the effects of transients.

DiVito, Ben L.

Antenna feed system for receiving circular polarization and transmitting linear polarization

An object is to provide for receiving a circularly polarized signal from an antenna feed (10) connected to orthogonally spaced antenna elements (11, 12, 13, 14) and for transmitting a linearly polarized signal through the same feed without switches, and without suffering a 3 dB polarization mismatch loss, using an arrangement of hybrid junctions. The arrangement is comprised of two dividing hybrid junctions (15, 16), each connected to a different pair of antenna elements and a summing hybrid junction (17). In one embodiment, a receiver (18) is connected to the summing hybrid junction directly. A diplexer (19a or 19b) is used to connect a transmitter (20a or 20b) to only one pair of antenna elements. In an alternative embodiment, designated left and right circularly polarized (LCP and RCP) transmitters (21, 22) are connected to the summing hybrid junction by separate diplexers (23, 24), and separate LCP and RCP sensitive receivers (25, 26) are connected to the diplexers in order to transmit linearly polarized signals using all four antenna elements while receiving circularly polarized signals as before. An orthomode junction (30) and horn antenna (32) may replace the two dividing hybrid junctions (15, 16) and antenna feed (10).

Seidel, Boris L.

The Ensemble Canon

Ensemble is an open architecture for the development, integration, and deployment of mission operations software. Fundamentally, it is an adaptation of the Eclipse Rich Client Platform (RCP), a widespread, stable, and supported framework for component-based application development. By capitalizing on the maturity and availability of the Eclipse RCP, Ensemble offers a low-risk, politically neutral path towards a tighter integration of operations tools. The Ensemble project is a highly successful, ongoing collaboration among NASA Centers. Since 2004, the Ensemble project has supported the development of mission operations software for NASA's Exploration Systems, Science, and Space Operations Directorates.

applications programs (computers),

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Lau, William K. M.

Global Air Quality and Climate

Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH4), ozone precursors (O3), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O3 precursor CH4 would slow near-term warming by decreasing both CH4 and tropospheric O3. Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NOx) emissions, which increase tropospheric O3 (warming) but also increase aerosols and decrease CH4 (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH4 volatile organic compounds (NMVOC) warm by increasing both O3 and CH4. Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O3 and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O3 and SOA.

ozone

Analysis of Present Day and Future OH and Methane Lifetime in the ACCMIP Simulations

Results from simulations performed for the Atmospheric Chemistry and Climate Modeling Intercomparison Project (ACCMIP) are analysed to examine how OH and methane lifetime may change from present day to the future, under different climate and emissions scenarios. Present day (2000) mean tropospheric chemical lifetime derived from the ACCMIP multi-model mean is 9.8+/-1.6 yr (9.3+/-0.9 yr when only including selected models), lower than a recent observationally-based estimate, but with a similar range to previous multi-model estimates. Future model projections are based on the four Representative Concentration Pathways (RCPs), and the results also exhibit a large range. Decreases in global methane lifetime of 4.5 +/- 9.1% are simulated for the scenario with lowest radiative forcing by 2100 (RCP 2.6), while increases of 8.5+/-10.4% are simulated for the scenario with highest radiative forcing (RCP 8.5). In this scenario, the key driver of the evolution of OH and methane lifetime is methane itself, since its concentration more than doubles by 2100 and it consumes much of the OH that exists in the troposphere. Stratospheric ozone recovery, which drives tropospheric OH decreases through photolysis modifications, also plays a partial role. In the other scenarios, where methane changes are less drastic, the interplay between various competing drivers leads to smaller and more diverse OH and methane lifetime responses, which are difficult to attribute. For all scenarios, regional OH changes are even more variable, with the most robust feature being the large decreases over the remote oceans in RCP8.5. Through a regression analysis, we suggest that differences in emissions of non-methane volatile organic compounds and in the simulation of photolysis rates may be the main factors causing the differences in simulated present day OH and methane lifetime. Diversity in predicted changes between present day and future OH was found to be associated more strongly with differences in modelled temperature and stratospheric ozone changes. Finally, through perturbation experiments we calculated an OH feedback factor (F) of 1.24 from present day conditions (1.50 from 2100 RCP8.5 conditions) and a climate feedback on methane lifetime of 0.33+-0.13 yr/K, on average. Models that did not include interactive stratospheric ozone effects on photolysis showed a stronger sensitivity to climate, as they did not account for negative effects of climate-driven stratospheric ozone recovery on tropospheric OH, which would have partly offset the overall OH/methane lifetime response to climate change.

atmospheric composition

Long-term Ozone Changes and Associated Climate Impacts in CMIP5 Simulations

Ozone changes and associated climate impacts in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations are analyzed over the historical (1960-2005) and future (2006-2100) period under four Representative Concentration Pathways (RCP). In contrast to CMIP3, where half of the models prescribed constant stratospheric ozone, CMIP5 models all consider past ozone depletion and future ozone recovery. Multimodel mean climatologies and long-term changes in total and tropospheric column ozone calculated from CMIP5 models with either interactive or prescribed ozone are in reasonable agreement with observations. However, some large deviations from observations exist for individual models with interactive chemistry, and these models are excluded in the projections. Stratospheric ozone projections forced with a single halogen, but four greenhouse gas (GHG) scenarios show largest differences in the northern midlatitudes and in the Arctic in spring (approximately 20 and 40 Dobson units (DU) by 2100, respectively). By 2050, these differences are much smaller and negligible over Antarctica in austral spring. Differences in future tropospheric column ozone are mainly caused by differences in methane concentrations and stratospheric input, leading to approximately 10DU increases compared to 2000 in RCP 8.5. Large variations in stratospheric ozone particularly in CMIP5 models with interactive chemistry drive correspondingly large variations in lower stratospheric temperature trends. The results also illustrate that future Southern Hemisphere summertime circulation changes are controlled by both the ozone recovery rate and the rate of GHG increases, emphasizing the importance of simulating and taking into account ozone forcings when examining future climate projections.

tropospheric ozone

Multi-Model Assessment of Global Hydropower and Cooling Water Discharge Potential Under Climate Change

Worldwide, 98% of total electricity is currently produced by thermoelectric power and hydropower. Climate change is expected to directly impact electricity supply, in terms of both water availability for hydropower generation and cooling water usage for thermoelectric power. Improved understanding of how climate change may impact the availability and temperature of water resources is therefore of major importance. Here we use a multi-model ensemble to show the potential impacts of climate change on global hydropower and cooling water discharge potential. For the first time, combined projections of streamflow and water temperature were produced with three global hydrological models (GHMs) to account for uncertainties in the structure and parametrization of these GHMs in both water availability and water temperature. The GHMs were forced with bias-corrected output of five general circulation models (GCMs) for both the lowest and highest representative concentration pathways (RCP2.6 and RCP8.5). The ensemble projections of streamflow and water temperature were then used to quantify impacts on gross hydropower potential and cooling water discharge capacity of rivers worldwide. We show that global gross hydropower potential is expected to increase between +2.4% (GCM-GHM ensemble mean for RCP 2.6) and +6.3% (RCP 8.5) for the 2080s compared to 1971-2000. The strongest increases in hydropower potential are expected for Central Africa, India, central Asia and the northern high-latitudes, with 18-33% of the world population living in these areas by the 2080s. Global mean cooling water discharge capacity is projected to decrease by 4.5-15% (2080s). The largest reductions are found for the United States, Europe, eastern Asia, and southern parts of South America, Africa and Australia, where strong water temperature increases are projected combined with reductions in mean annual streamflow. These regions are expected to affect 11-14% (for RCP2.6 and the shared socioeconomic pathway (SSP)1, SSP2, SSP4) and 41-51% (RCP8.5-SSP3, SSP5) of the world population by the 2080s.

global hydrological models

The Impacts of Rising Temperatures on Aircraft Takeoff Performance

Steadily rising mean and extreme temperatures as a result of climate change will likely impact the air transportation system over the coming decades. As air temperatures rise at constant pressure, air density declines, resulting in less lift generation by an aircraft wing at a given airspeed and potentially imposing a weight restriction on departing aircraft. This study presents a general model to project future weight restrictions across a fleet of aircraft with different takeoff weights operating at a variety of airports. We construct performance models for five common commercial aircraft and 19 major airports around the world and use projections of daily temperatures from the CMIP5 model suite under the RCP 4.5 and RCP 8.5 emissions scenarios to calculate required hourly weight restriction. We find that on average, 10 - 30% of annual flights departing at the time of daily maximum temperature may require some weight restriction below their maximum takeoff weights, with mean restrictions ranging from 0.5 to 4% of total aircraft payload and fuel capacity by mid- to late century. Both mid-sized and large aircraft are affected, and airports with short runways and high temperatures, or those at high elevations, will see the largest impacts. Our results suggest that weight restriction may impose a non-trivial cost on airlines and impact aviation operations around the world and that adaptation may be required in aircraft design, airline schedules, and/or runway lengths.

air transportation system

Multi-Model Impacts of Climate Change on Pollution Transport from Global Emission Source Regions

The impacts of climate change on tropospheric transport, diagnosed from a carbon monoxide (CO)-like tracer species emitted from global CO sources, are evaluated from an ensemble of four chemistry-climate model (CCMs) contributing to the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). Model time-slice simulations for present-day and end of the 21st century conditions were performed under the Representative Concentrations Pathways (RCP) climate scenario RCP 8.5. All simulations reveal a strong seasonality in transport, especially over the tropics. The highest CO-tracer mixing ratios aloft occur during boreal winter when strong vertical transport is co-located with biomass burning emission source regions. A consistent and robust decrease in future CO-tracer mixing ratios throughout most of the troposphere, especially in the tropics, and an increase around the tropopause is found across the four CCMs in both winter and summer. Decreases in CO-tracer mixing ratios in the tropical troposphere are associated with reduced convective mass fluxes in this region, which in turn may reflect a weaker Hadley Cell circulation in the future climate. Increases in CO-tracer mixing ratios near the tropopause are largely attributable to a rise in tropopause height, although a poleward shift in the midlatitude jets may also play an important role in the extra-tropical upper troposphere. An increase in CO-tracer mixing ratios also occurs near the Equator, centred over EquatorialCentral Africa, extending from the surface to the mid troposphere which is most likely related to localised decreases in convection in the vicinity of the Intertropical Convergence Zone, resulting in larger CO-tracer mixing ratios over biomass burning regions and smaller mixing ratios downwind.

Tropospheric Transport

Methodology to Assess the Changing Risk of Yield Failure Due to Heat and Drought Stress Under Climate Change

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

Climate risk assessment

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan Dejesus Oribello

NASA GeneLab RNASeq Consensus Pipeline: A Nextflow Implementation

The NASA GeneLab project (genelab.nasa.gov) seeks to accelerate space biology research through cataloging and democratizing omics data. Since raw omics data is largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data has greater immediate value to a wide range of users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. Previously, GeneLab developed a standardized pipeline for processing RNAseq data, referred to as the ‘GeneLab RNAseq Consensus Pipeline (RCP)’, in collaboration with GeneLab’s Analysis Working Groups. The work presented here is a Nextflow implementation of GeneLab’s RCP that automates and accelerates data processing of RNASeq datasets hosted on GeneLab. In addition to the core data processing, the workflow also includes staging of GeneLab raw data and a robust verification and validation (V&V) program that runs after each processing step to identify errors in real-time, stop additional downstream computation, and preserve computational resources. The workflow, including the staging and V&V functionality, is open source for others to reuse and modify at https://github.com/nasa/GeneLab_Data_Processing/tree/master/RNAseq.

Jonathan D Oribello

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River

High Magnetic Anisotropy and Magnetocaloric Effects in Single-Crystal Cr 2 Te 3

Here, we report a systematic investigation of anisotropic magnetocaloric effects in single-crystal Cr 2 Te 3 . Single-crystal samples are synthesized by chemical vapor transport and characterized by X-ray and Laue diffraction methods. The maximum magnetic entropy change –ΔS M max is 4.50 J kg –1 K –1 for the easy c-axis (3.36 J kg –1 K –1 for the hard axis along ab-plane), and the relative cooling power (RCP) is 296.7 J kg –1 for the easy c-axis (183.84 J kg –1 for the hard axis along ab-plane) for a magnetic field change of 9 T near the Curie temperature. The magneto-crystalline anisotropy constant K u is estimated to be 580.12 kJ m –3 at 140 K, decreasing to 148.60 kJ m –3 at 168 K. Meanwhile, the maximum of the rotational magnetic entropy change –ΔS M R (T, H) between the c-axis and the ab-plane is about 1.14 J kg –1 K –1 for magnetic-field change of 9 T. The critical exponents are estimated by analyzing magnetocaloric effects, which indicate a 2D-Ising type magnetic system. The accuracy of estimated critical exponents is verified by scaling analysis. The maximum magnetic entropy change –ΔS M max ≈ 5.25 J kg –1 K –1 (along the c-axis) and the corresponding adiabatic temperature change ΔT ad ≈ 3.31 K (along the c-axis) are estimated by analyzing heat capacity measurements with a magnetic field up to 9 T.

36 MATERIALS SCIENCE

Self-Powered Circularly Polarized Light Detection Enabled by Chiral Two-Dimensional Perovskites with Mixed Chiral–Achiral Organic Cations

Direct detection of circularly polarized light (CPL) holds great promise for the development of various optical technologies. Chiral 2D organic–inorganic halide perovskites make it possible to fabricate CPL-sensitive photodetectors. However, selectively detecting left-handed circularly polarized (LCP) and right-handed circularly polarized (RCP) light remains a significant challenge. Herein, we demonstrate a greatly enhanced distinguishability of photodiode-type CPL photodetectors based on chiral 2D perovskites with mixed chiral aryl (R)-(+),(S)-(–)-α-methylbenzylammonium (R,S-MBA) and achiral alkyl n-butylammonium (nBA) cations. The (R,S-MBA 0.5 nBA 0.5 ) 2 PbI 4 perovskites exhibit a 10-fold increase in circular dichroism signals compared to (R,S-MBA) 2 PbI 4 perovskites. Here, the CPL photodetectors based on the mixed-cation perovskites exhibit self-powered capabilities with a specific detectivity of 2.45 × 10 12 Jones at a o V bias. Notably, these devices show high distinguishability (gres) factors of –0.58 and +0.54 based on (R,S-MBA 0.5 nBA 0.5 ) 2 PbI 4 perovskites, respectively, surpassing the performance of (R-MBA) 2 PbI 4 -based devices by over 3-fold and setting a record for CPL detectors based on chiral 2D n = 1 perovskites.

36 MATERIALS SCIENCE