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Exploring Phosphonium‐Based Anion Exchange Polymers for Moisture Swing Direct Air Capture of Carbon Dioxide
This study explores the performance and stability of ammonium and phosphonium-based polymeric ionic liquids (PILs) with methyl and butyl substituents in moisture-swing direct air capture of CO 2 . The polymers are synthesized with chloride counterions, followed by ion exchange to the bicarbonate ion, and tests for CO 2 capture capacity and stability under cyclic wet–dry conditions. The phosphonium polymer with methyl substituents [PVBT-MeP] demonstrates the highest CO 2 capture capacity at ≈510 µmol g⁻¹, attributed to minimal steric hindrance and stronger ion pairing with bicarbonate. However, oxidative degradation is detected by 31 P NMR spectroscopy after the moisture swing experiment, with the appearance of a phosphine oxide peak at 61.28 ppm, which indicates phosphorus oxidation as the primary degradation pathway. In contrast, the ammonium polymer with butyl substituents [PVBT-BuN] exhibits the highest stability, showing no degradation over five moisture swing cycles. Additional stability experiments in 0.5 m KHCO 3 solutions reveal no degradation for any PIL, suggesting that oxidative degradation is driven by dynamic acid-base reactions during the moisture swing cycles in the air. Furthermore, these findings reveal the potential of phosphonium-based PILs for moisture-swing direct air capture, achieving high capacity while highlighting the need for optimized stability through counterion and structural design.
Porous Membranes for Moisture Probe Protection (SR18024)
In the presence of contaminants, moisture probes can give false moisture readings and have shorter lifetimes. Absolute humidity probes are composed of porous, hygroscopic metallic oxide thin films (Al 2 O 3 ) coupled to electrodes (e.g. Au and Al). While these materials provide absolute humidity readings at low water levels at a relatively low cost, they are sensitive to the presence of contaminants, especially ammonia, due to its high hygroscopicity and ability to bind to the probe. Without frequent recalibration, especially in the presence of contaminants, the humidity levels are inaccurately reported due to measurement drift that occurs when the pores close, changing the impedance of the probe. The goal of this project was to improve the stability and reliability of these moisture probes by incorporating a molecular sieve into the probe to allow only the water to reach the sensor. Molecular sieves contain pores that allow molecule specific permeation. Two dimensional inorganic nanosheets (e.g. BN, MoO 2 , MoS 2 ) have recently been shown to behave as molecular sieves for water. Compared to zeolites, nanoporous materials have higher flux rates through the pores, leading to faster water permeation. Graphene oxide sheets have also been successfully employed for unimpeded water permeation; however, at lower humidity levels, the structure is unstable and the pores shrink, preventing the sieving of molecules. Compared to graphene oxide, sheets based off of inorganic materials, such as molybdenum, have been found to be more stable at lower humidity levels and have faster permeation rates. By creating a barrier in before the Al 2 O 3 sensor chip to prevent the permeation of contaminants into the probe, the lifetime of the probe will be extended. While the molybdenum sheets are a promising material for this application, their performance against ammonia and tritiated compounds have not yet been evaluated. This technology can be applied to other applications, including gas and liquid purification for environmental remediation, single molecule sensors, field effect transistors, and catalysts.
Moisture Uptake Relaxes Stress in Metal Halide Perovskites at the Expense of Stability
Not provided.
Surface Hydration of Porous Nickel Hydroxides Facilitates the Reversible Adsorption of CO 2 from Ambient Air
Direct air capture (DAC) under humid ambient conditions typically requires the use of organic components, with sorbents that are purely inorganic in composition for the most part operating hundreds of degrees above room temperature. In this work, we report porous metal hydroxides as a novel class of water-tolerant, oxidatively and hydrothermally stable low-temperature sorbents that exhibit competitive DAC working capacities of 1.25 mmol/g over 5 consecutive temperature swing adsorption–desorption cycles in the presence of steam and oxygen. Aqueous miscible organic solvent treatments are used to create highly porous structures with surface areas exceeding 700 m 2 /g that capture CO 2 in the form of bicarbonates under dry conditions, and carbonates under wet conditions. Water exerts a facilitative rather than an inhibiting effect on CO 2 binding, and the presence of hydrating multilayers serves to stabilize carbonate species akin to moisture swing adsorbents except for the fact that solvation results in a remarkable (upto 10-fold) increase, not decrease, in DAC capacity. High-valent doping with cerium is used to improve DAC capacities by amplifying surface basicity, evidencing porous nickel hydroxides specifically (and porous metal hydroxides more generally) as a novel class of robust, earth-abundant DAC sorbents.
Balancing moisture and oxygen can match the crystallization dynamics of inert halide perovskite processing
Understanding crystallization in ambient environments is essential for scaling the fabrication of halide perovskite solar cells. Antisolvent-free perovskite deposition offers improved compatibility with high-throughput processing but introduces distinct crystallization dynamics relative to the more ubiquitous use of antisolvents in lab-scale perovskite fabrication. These dynamics are driven by interactions between solutes, solvent and the deposition environment. Using in situ wide-angle X-ray scattering during spin-coating and annealing, we demonstrate how relative humidity (RH) and oxygen, can be tuned to drive polytype evolution during ambient crystallization of formamidinium lead iodide to match that of inert synthesis and achieve comparable film and device quality. In an inert (N 2 ) environment, we find that perovskite films follow a well-established 2H → 3C phase transformation with a short period of coexistence of the 4H and 6H phase during heating. During crystallization in dry air (RH 0%), the added presence of oxygen leads to the dominance of 4H intermediate for an extended duration, establishing a 2H → 4H → 3C pathway. Introducing low humidity (RH 10%) suppresses the 4H phase to a short-lived intermediate above 100 °C, facilitating a more direct transition to the desired 3C phase and almost replicating the crystallization behavior observed under inert conditions. Interestingly, films crystallized under RH 10% show a lower onset temperature for the perovskite 3C phase than under N 2 . At higher humidity (RH 40%), the strong interaction of oxygen and moisture with iodoplumbates appears to stabilize higher order polytypes (4H and 6H). Devices fabricated under RH 10% achieve higher efficiency and enhanced stability compared to those produced under inert atmosphere. These findings provide mechanistic insight into crystallization pathways in different environments and provide a framework to transfer processes from inert to ambient conditions. The results highlight the critical role of controlled humidity in tuning antisolvent-free perovskite crystallization for scalable processing.
Understanding Instability in Formamidinium Lead Halide Perovskites: Kinetics of Transformative Reactions at Grain and Subgrain Boundaries
Transformative and reconstructive reactions impart significant structural changes at particle boundaries of hybrid perovskites, which influence environmental stability and optoelectronic properties of these materials. Here, we investigate the moisture-induced transformative reactions in formamidinium based perovskites FAPbX 3 (X=I, Br) and show that the ambient stability of these materials can be adjusted from a few hours to several months. For FAPbI 3 , roles of water vapor, particle size, and light illumination on the kinetic pathways of the cubic (a) transformation to the hexagonal (d) phase are analyzed by X-ray diffraction, optical microscopy, photoluminescence and solid-state NMR spectroscopy techniques. The grain and sub-grain boundaries exhibit different α→δ-FAPbI 3 phase transformation kinetics. Our study suggests that the dynamic transformation involves the local water-induced dissolution of the cubic phase occurring at the crystal surfaces followed by precipitation of the hexagonal phase. Insights into structures and dynamics of a kinetically trapped α-|δ-FAPbI 3 are obtained by 1 H, 2 H, and 207 Pb ssNMR spectroscopy.
A data fusion approach to optimize compositional stability of halide perovskites
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Chapter 1: Halide Organic Photovoltaics for Energy: Hybrid Perovskites for Solar Cells
The following sections are included: Fundamentals of Photovoltaics, What Limits PV Device Efficiencies?, Traditional Photovoltaics, Perovskite Halide-Based Hybrid Semiconductors for Photovoltaics: Novel Materials in a League of Their Own, Solution Processability, Tunability, Perovskite Solar Cell Architectures, Pairing Perovskite Absorbers, Reduction/Oxidation and Electrochemical Reactivity Considerations for High-Performance Halide Perovskite Solar Cells, Metal Electrode Corrosion, Proton-Mediated Reduction of Ni3+ at NiOx Interfaces, Electrochemistry in Solid-State Perovskite Devices, Overview of Stability Considerations for High Performance Perovskite Solar Cells, Moisture-Induced Degradation, Oxygen-Mediated Degradation, Illumination-Dependent Degradation, Bias-Dependent Degradation, Stability Considerations for Charge Selective Contacts, Electrode-Induced Degradation Modes, Conclusion, and References.
Package Development for Reliability Testing of Perovskites
Metal halide perovskite solar cells have reached a critical point in their development. At a current certified record efficiency of 25.7% for a single-junction, research-scale cell, they now garner serious attention from the solar cell industry as a promising route to widespread, low-cost photovoltaics in single- or tandem-junction configurations. However, more work to demonstrate their durability under real-world outdoor test conditions is necessary to ensure the long-term success and deployment of the technology. Differences in chemistry, processes, and their combination result in unique performance limiters for both efficiency and stability. Further, as many active formulations and layer/cell stack combinations are sensitive to temperature, air, and moisture, it is important to separate intrinsic limitations to stability relative to these extrinsic sources. This presents a particular need for the development of an appropriate and reliable package for environmental (i.e., accelerated and outdoor) testing that will permit these different factors to be evaluated and understood.
Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells
Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.
Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells
Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.
Antisolvent‐Mediated Air Quench for High‐Efficiency Air‐Processed Carbon‐Based Planar Perovskite Solar Cells
Perovskite solar cells (PSCs) have becoma a leading low‐cost photovoltaic technology, achieving power conversion efficiencies (PCEs) of up to 26.1%. However, their commercialization is hindered by stability issues and the need for controlled processing environments. Carbon‐electrode‐based PSCs (C‐PSCs) offer enhanced stability and cost‐effectiveness compared to traditional metal‐electrode PSCs, i.e., Au and Ag. However, processing challenges persist, particularly in air conditions where moisture sensitivity poses a significant hurdle. Herein, a novel air processing technique is presented for planar C‐PSCs that incorporates antisolvent vapors, such as chlorobenzene, into a controlled air‐quenching process. This method effectively mitigates moisture‐induced instability, resulting in champion PCEs exceeding 20% and robust stability under ambient conditions. The approach retains 80% of initial efficiency after 30 h of operation at maximum power point without encapsulation. This antisolvent‐mediated air‐quenching technique represents a significant advancement in the scalable production of C‐PSCs, paving the way for future large‐scale deployment.
Mitigating electrochemical degradation in CsPbBr{sub 3} gamma detectors by organic and inorganic encapsulation.
CsPbBr3 perovskite semiconductors have emerged as a leading candidate for nextgeneration radiation detectors because of their exceptional charge transport properties, defect tolerance, and record-breaking sensitivity and energy resolution. Their long-term stability, however, is hindered by electrode-driven electrochemical decomposition, which is accelerated by moisture- and oxygen-assisted ion migration during operation. Here, we investigated organic and inorganic encapsulation strategies as both environmental barriers and means to suppress interfacial degradation pathways. Atomic layer deposition (ALD) of Al2O3 provided a conformal passivation layer that blocked environmental ingress, suppressed ionic diffusion, reduced leakage current, enhanced energy resolution and expanded the operational electric-field window beyond 5 kV∙cm1 . By contrast, organic encapsulants such as paraffin wax and polystyrene slowed moisture diffusion but did not suppress interfacial reactions, with wax extending stability to over 90 days. These results show that ALD-Al2O3 suppresses dominant interfacial degradation pathways, enabling stable, high-field operation and advancing the practical deployment of CsPbBr3 γ-ray detectors.
Upper Troposphere Smoke Injection From Large Areal Fires
Abstract Large areal fires, such as those ignited following a nuclear detonation, can inject smoke into the upper troposphere and lower stratosphere. Detailed fire simulations allow for assessment of how local weather interacts with these fires and affects smoke lofting. In this study, we employ the fire simulation package in the Weather Research and Forecasting (WRF‐Fire) model, Version 4.0.1, to explore how smoke lofting from a fire burning a homogeneous fuel bed changes with varying local winds, relative humidity, and atmospheric boundary‐layer stability for two different‐sized areal fires. The presence of moisture has the greatest influence on the results by raising the altitude of lofting, while faster wind speeds dampen lofting and lower the injection height. Stably stratified conditions inhibit plume propagation compared with neutrally stratified conditions, although the impact of stability is not as strong as that of moisture and winds. These findings highlight the importance of using an appropriate atmospheric profile when simulating large fires, as the local weather can have a meaningful influence on smoke lofting.
Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem
Background: Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics’ seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. Results: We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages ( Leviviricetes ), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a “seed-bank” viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: “Kill-The-Winner” which proposes that lytic phages are actively infecting abundant bacteria, and “Piggyback-The-Persistent” which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth. Conclusion: Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.
Savannah River Site Climatology for Research Activities Conducted Onsite and in P-Area (1994-2023)
This report presents a climatology of meteorological variables at the Savannah River Site (SRS) using measurements from the P-Area and Central Climatology meteorological towers to support research activities at the Savannah River Site. Key values included in this report are wind, surface pressure, temperature, relative humidity, soil moisture, cloud fraction, cloud base, lightning, atmospheric stability, and boundary layer parameters. The Central Climatology tower is useful in that it is instrumented at four levels, allowing for an examination of height dependence on some variables.
Savannah River Site Climatology for Research Activities Conducted Onsite and in P-Area (1994-2023)
Executive Summary This report presents a climatology of meteorological variables at the Savannah River Site (SRS) using measurements from the P-Area and Central Climatology meteorological towers to support research activities at the Savannah River Site. Key values included in this report are wind, surface pressure, temperature, relative humidity, soil moisture, cloud fraction, cloud base, lightning, atmospheric stability, and boundary layer parameters. The Central Climatology tower is useful in that it is instrumented at four levels, allowing for an examination of height dependence on some variables.