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At least 991 records · Page 55

Electronic and Structural Properties of the Polymer-Electrolyte Interphase in Electrochemically Doped Polymers

The advance of soft, polymer-based (photo)electrochemical energy transformation and storage applications requires a framework for polymer and electrolyte design that includes a deep understanding of the polymer–electrolyte interphase. Here, we report on the investigations of two napthalenediimide (NDI)–bithiophene (T2)-based semiconducting copolymers using computational modeling and in situ, ex situ, and operando techniques to reveal how changes in electrolyte and polymer chemistry modulate the electronic and structural properties of polymer electrodes during electrochemical (de)doping. These systems are shown to host an ensemble of polarons, in contrast with the single polaron-like character often reported, whose properties vary with the nature of the local environment. Importantly, these polarons serve as reporters of the nanoscale environments in which they reside. We demonstrate that controlling the polymer and electrolyte chemistry regulates the nature of the charge carriers generated upon electrochemical doping and/or exciton dissociation in a photoelectrochemical solar cell: For instance, divalent counterions enable polaron and bipolaron formation at lower reducing potentials, while supporting more bipolaron formation than monovalent counterions. A novel application of NEXAFS reveals insights into charge (de)localization, providing a pathway for future investigation of electron transport mechanisms. Finally, simulations of polymer swelling of an amorphous interphase show that charge formation has a large impact on polymer swelling and ion penetration. These studies deliver insights to enable the control of charge-carrier and ion transport, the rates of electron transfer and catalytic efficiency, device stability, and overall device performance.

14 SOLAR ENERGY↗

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗

Submodule-Level Decentralized Control for Cascaded Quadruple Active Bridge-Based Medium-Voltage Converters: Preprint

High-power, low-voltage DC (LVDC) loads, such as AI data centers, electric vehicle fast-charging hubs, and hydrogen electrolyzers, are accelerating the deployment of solid-state transformers (SSTs) that directly interface medium-voltage AC (MVAC) to LVDC, streamlining power delivery. This paper proposes a submodule-level decentralized control strategy for an SST comprising a cascaded H-bridge (CHB) active rectifier on the MVAC side and per-module quadruple-active-bridge (QAB) converters on the LVDC side with local controllers. The proposed strategy eliminates the need for high-fidelity, real-time cross-isolation communication by synchronizing all active bridges to a common heartbeat signal and enabling the primary- and secondary-side controllers to generate independent local control signals (phase shifts). The resultant phase shifts naturally govern average and double-line frequency power transfer between active bridges, enabling each side to meet its control objectives using only local measurements. Detailed controller design considerations are presented based on a stability analysis. Comprehensive electromagnetic-transient simulations demonstrate tight DC-link voltage regulation, high-quality grid currents, and robust operation under load transients and grid disturbances, without real-time communication among the submodule controllers. These results indicate that the proposed scheme can significantly enhance the reliability, scalability, and flexibility of cascaded bridge-based medium-voltage converters.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Polymorphs of the n–Type Polymer P(NDI2OD–T2): A Comprehensive Description of the Impact of Processing on Crystalline Morphology and Charge Transport

A systematic study of the polymorphs emerging in P(NDI2OD-T2) (also commercially known as N2200), a prototypical organic semiconducting n-type polymer, is presented. Using a tightly integrated experimental and computational approach, detailed atomistic-level descriptions are provided investigating the three known P(NDI2OD-T2) polymorphs observed at room temperature as a function of thin-film processing. Importantly, over the course of the work, a missing link is uncovered, a fourth polymorph referred to here as Form I-β; this new form is a morphological intermediary observed upon thermal annealing, which evolves from Form I but tends to disappear upon full polymer chain melting. The computationally derived polymorph structures show excellent agreement with experimental X-ray scattering characterization. The relative stabilities of each polymorph are calculated in terms of both the bulk material and the polymorph-air interface. An energy landscape is then constructed to qualitatively compare the thermodynamic versus kinetic origins of each polymorph, and the factors driving (supra)assembly and associated transformations among polymorphs using an approach generalizable to other organic semiconducting polymers. Lastly, the relationships among preferential polymorphic crystallinity, relative chain orientations, and directional charge transport properties in P(NDI2OD-T2) are explored. Altogether, this work provides unprecedented insights into complex structure-processing-transport relationships in a representative semiconducting organic polymer.

36 MATERIALS SCIENCE↗

Why are Lead Iodide‐Based Perovskite Precursor Inks Yellow?

A challenge faced by metal halide perovskite (MHP) photovoltaics is scaling up solution deposition processes to realize rapid and inexpensive manufacturing. The challenge lies in completely understanding and controlling solution speciation, nucleation, and self-assembly of iodoplumbate complexes during solvent evaporation as the liquid transforms into gels and solids. An accurate description of solution species, at all points in the transformation, is a prerequisite to design robust and reliable processes. Here, in this study, the common assumption that initial monoplumbate solution species typically invoked (e.g., [PbI 6 ] 4− ) are certainly not the origin of optical absorbance at >400 nm wavelengths is disproved, as are many large particles of common “intermediate” iodoplumbate phases with face- or edge-sharing connectivity. Instead, a new perspective is offered, involving (partially) corner-sharing iodo(poly)plumbates (>1 Pb 2+ per complex) that experience highly dynamic chemical environments. It is outlined how the MHP field would benefit by elucidating these phenomena. Future work is required to determine the size and kinetic behavior of polyplumbate species, and contextualize these findings in relation to broader trends in materials chemistry beyond MHPs. Ultimately, a complete explanation for the solution speciation, optical absorbance signatures, and the color of MHP precursor inks remains an open challenge to the community.

14 SOLAR ENERGY↗

Technical Routes to Achieve High Circular Polarized Luminescence in Chiral Perovskites: A Mini‐Review

Chiral hybrid organic-inorganic perovskites (HOIPs) have emerged as promising materials for optoelectronic and spintronic applications, leveraging unique properties such as circularly polarized luminescence (CPL), circularly polarized nonlinear optical (NLO) emission, and chiral-induced spin selectivity (CISS). However, challenges remain in stabilizing these materials under environmental stresses and precisely controlling chirality for scalable use. This review summarizes five main strategies to induce chirality in HOIPs, i.e., direct incorporation of chiral cations, surface modification with chiral ligands, ion doping, template-induced chirality, and chiral metasurfaces. Each approach offers distinct advantages for optimizing CPL efficiency and device stability, paving the way for next-generation applications in CPL detectors, information encryption, spintronic devices, etc.

14 SOLAR ENERGY↗

The Two Arctic Wintertime Boundary Layer States: Disentangling the Role of Cloud and Wind Regimes in Reanalysis and Observations During MOSAiC

The wintertime central Arctic atmosphere comprises a radiatively clear and a radiatively opaque state, which are linked to synoptic forcing and mixed-phase clouds. Weather and climate models often lack process representations surrounding these states, but prior work mostly treated the problem as an aggregate of synoptic conditions, resulting in partially overlapping biases. Here, we disaggregate the Arctic states and confront ERA5 reanalysis with observations from the MOSAiC campaign over the central Arctic sea ice during winter 2019/2020. Low-level winds and liquid water path (LWP) are combined to derive different synoptic classes. Results show that the clear state is primarily formed by weak/moderate winds and the absence of liquid-bearing clouds, while strong winds and enhanced LWP primarily form the radiatively opaque state. ERA5 struggles to reproduce these basic statistics, shows too weak sensitivity of thermal radiation to synoptic forcing, and overestimates thermal radiation for similar LWP amounts. The latter is caused by a warm bias, which has a pronounced inversion structure and is largest in clear and calm conditions. Under strong synoptic forcing, the warm bias is constant with height and discrepancies in mixed-phase cloud altitude appear. Separating synoptic conditions is regarded as useful for process-oriented evaluation of the Arctic troposphere in models.

54 ENVIRONMENTAL SCIENCES↗

Recommendations for developing, documenting, and distributing data products derived from NEON data

The National Ecological Observatory Network (NEON) provides over 180 distinct data products from 81 sites (47 terrestrial and 34 freshwater aquatic sites) within the United States and Puerto Rico. These data products include both field and remote sensing data collected using standardized protocols and sampling schema, with centralized quality assurance and quality control (QA/QC) provided by NEON staff. Such breadth of data creates opportunities for the research community to extend basic and applied research while also extending the impact and reach of NEON data through the creation of derived data products—higher level data products derived by the user community from NEON data. Derived data products are curated, documented, reproducibly-generated datasets created by applying various processing steps to one or more lower level data products—including interpolation, extrapolation, integration, statistical analysis, modeling, or transformations. Derived data products directly benefit the research community and increase the impact of NEON data by broadening the size and diversity of the user base, decreasing the time and effort needed for working with NEON data, providing primary research foci through the development via the derivation process, and helping users address multidisciplinary questions. Creating derived data products also promotes personal career advancement to those involved through publications, citations, and future grant proposals. However, the creation of derived data products is a nontrivial task. Here we provide an overview of the process of creating derived data products while outlining the advantages, challenges, and major considerations.

54 ENVIRONMENTAL SCIENCES↗

Equation of State for the Thermodynamic Properties of Trans-1,2-dichloroethene [R-1130(E)]

We present an empirical equation of state in terms of the Helmholtz energy for trans-1,2-dichloroethene [R-1130(E)]. The range of validity is from the triple-point temperature, 223.31 K to 525 K with pressures up to 30 MPa. It may be used to calculate all thermodynamic properties in the fluid phase, including liquid, gas, and supercritical regions. Comparisons are given with existing literature data and estimated uncertainties are provided. In addition, checks were made for correct extrapolation behavior so that the equation behaves in a physically realistic manner when used outside of its range of validity, enabling its use in mixture models. The estimated uncertainties (at a k = 2 or 95 % level of confidence) are based on comparisons with critically assessed data and are 0.25 % for vapor pressure for temperatures in the range 300 K < T < 454 K, rising to 1.5 % as the temperature decreases from 300 K to 265 K. For density in the liquid phase the estimated uncertainty is 0.14 % for temperatures 270 K < T < 410 K and for pressures up to 30 MPa. For the vapor phase the estimated uncertainty in density is 3 %. The uncertainty for liquid-phase heat capacity is 1 % at atmospheric pressure over the temperature range 268 K < T < 309 K, and the uncertainty for the speed of sound in the liquid phase is 0.25 % for temperatures 230 K < T < 420 K and for pressures up to 30 MPa. The uncertainties are larger outside of these specified ranges and in the critical region.

1,2-Dichloroethene↗

Constrained or unconstrained? Neural-network-based equation discovery from data

Throughout many fields, practitioners often rely on differential equations to model systems. Yet, for many applications, the theoretical derivation of such equations and/or the accurate resolution of their solutions may be intractable. Instead, recently developed methods, including those based on parameter estimation, operator subset selection, and neural networks, allow for the data-driven discovery of both ordinary and partial differential equations (PDEs), on a spectrum of interpretability. The success of these strategies is often contingent upon the correct identification of representative equations from noisy observations of state variables and, as importantly and intertwined with that, the mathematical strategies utilized to enforce those equations. Specifically, the latter has been commonly addressed via unconstrained optimization strategies. Representing the PDE as a neural network, we propose to discover the PDE (or the associated operator) by solving a constrained optimization problem and using an intermediate state representation similar to a physics-informed neural network (PINN). The objective function of this constrained optimization problem promotes matching the data, while the constraints require that the discovered PDE is satisfied at a number of spatial collocation points. We present a penalty method and a widely used trust-region barrier method to solve this constrained optimization problem, and we compare these methods on numerical examples. Our results on several example problems demonstrate that the latter constrained method outperforms the penalty method, particularly for higher noise levels or fewer collocation points. This work motivates further exploration into using sophisticated constrained optimization methods in scientific machine learning, as opposed to their commonly used, penalty-method or unconstrained counterparts. For both of these methods, we solve these discovered neural network PDEs with classical methods, such as finite difference methods, as opposed to PINNs-type methods relying on automatic differentiation. Here, we briefly highlight how simultaneously fitting the data while discovering the PDE improves the robustness to noise and other small, yet crucial, implementation details.

Data-driven discovery↗

Mixed lipid bilayers enable enhanced stability and activity retention of Lipase A in low-pH environments

Lipase A (LipA) from Bacillus subtilis is a versatile and industrially relevant enzyme, but its activity is compromised under acidic conditions due to aggregation and deactivation. In this study, we investigated the use of mixed lipid bilayers to stabilize and improve activity retention of LipA at low pH. Attachment to lipid bilayers, particularly those containing cationic lipids, greatly enhanced the long-term stability of LipA in acidic conditions while also leading to improvements in activity. Tethering to cationic bilayers not only shifted the apparent pH activity profile toward more acidic conditions, but also significantly enhanced activity retention upon incubation at pH 6. Notably, this protective effect persisted even without direct tethering, indicating that reversible, non-covalent interactions with the bilayer surface are sufficient for long-term stability. Circular dichroism further revealed that the secondary structure of LipA was retained, while dynamic light scattering suggested that activity loss in solution was primarily due to aggregation of the native state. Together, these findings support a model in which lipid bilayers mitigate aggregation and stabilize LipA through transient interactions and electrostatic modulation of the local surface environment. Furthermore, this approach exemplifies a simple, tether-free strategy for enhancing enzyme performance in acidic or destabilizing conditions, with implications for biocatalysis, biosensing, and therapeutic delivery.

Biocatalysis↗

Quantification of [MTBD][beti] loading and its effects on Pt/HSC electrode performance in hydrogen fuel cells

High surface area carbon-supported platinum catalysts (Pt/HSC) are widely used in polymer electrolyte membrane fuel cells but often suffer from limited proton and oxygen transport within porous domains. To address these challenges, we integrate the ionic liquid [MTBD][beti] into Pt/HSC catalyst layers using two deposition methods-one-pot and sequential deposition-to tune IL distribution within micropores and mesopores. A combination of ex situ and in operando techniques were employed to elucidate electrode structure-performance relationships across a range of IL loadings. Sequential deposition achieved more efficient pore filling and higher IL retention at lower IL:C ratios, enabling enhanced proton conductivity and protection of active sites. Compared to the IL-free Pt/HSC, IL-modified electrodes demonstrated up to 28% improvement in mass activity and enhanced high-current-density performance under low relative humidity, while maintaining comparable performance under humidified conditions. Electrochemical impedance spectroscopy and CO displacement experiments reveal that improvements are linked to reduced ionic resistance and lower sulfonate adsorption on Pt sites, rather than changes in electrochemical surface area. However, excessive IL loading leads to mass transport losses. These results highlight the importance of selective pore filling and efficient IL distribution in achieving kinetic gains without compromising ionic and gas transport.

08 HYDROGEN↗

Hydrodynamic modeling of plasma channel systems for laser plasma accelerators

Structured plasma channels are an essential technology for driving high-gradient, plasma-based acceleration and control of electron and positron beams for advanced concepts accelerators. Laser and gas technologies can permit the generation of long plasma columns known as hydrodynamic, optically-field-ionized (HOFI) channels, which feature low on-axis densities and steep walls. By carefully selecting the background gas and laser properties, one can generate narrow, tunable plasma channels for guiding high intensity laser pulses. Here, we present on the development of simulations of HOFI channels using the FLASH code, a publicly available radiation hydrodynamics code. We explore sensitivities of the channel evolution to laser profile, intensity, and background gas conditions, and identify relevant scalings with laser intensity through a range of practical channel delays.

Accelerators↗

Mechanistic Insights into Dinitrogen Reduction to Ammonia in Light-Controlled Nanocrystal:Nitrogenase Complexes

Developing systems that can efficiently capture photon energy and convert this energy into fuels and chemicals requires understanding how to assemble molecular components with diverse functions into complete systems possessing selectivity and efficiency in directing charge carriers to catalytic reactions. There are many challenges to achieving this goal. One promising approach is the development of hybrid systems that combine semiconductor nanocrystals (NCs) for light capture and enzymes as efficient catalysts. Such biohybrid systems capitalize on the tunable electronic and optical properties of NCs while leveraging the unmatched specificity and efficiency of enzymes in catalyzing chemical reactions, thereby offering opportunities to surpass the limitations of each component alone. Here, we focus on recent progress in developing a biohybrid system that combines CdS NCs for photon capture with the enzyme nitrogenase to accomplish light-driven dinitrogen (N 2 ) reduction to ammonia (NH 3 ). Integrating light-harvesting materials with biological catalysts requires a deep understanding of NC properties, protein stability, and electron transfer (ET), making it an inherently multidisciplinary problem. The reduction of N 2 to NH 3 is a challenging reaction, with a high demand in both agriculture and industrial chemical production. This reaction is intrinsically energy intensive, due to the need to activate the N≡N triple bond. The current standard industrial approach to N 2 reduction, the Haber−Bosch reaction, obtains the necessary energy input from fossil fuels, whereas biological systems capable of N 2 reduction utilize the hydrolysis of ATP as their energy source. Replacing these costly, energy-intensive inputs with renewable light energy represents a critical step toward sustainable NH 3 production. Recent progress has demonstrated that semiconductor CdS NCs can be coupled to the catalytic component of nitrogenase, the MoFe protein, to form a biohybrid CdS NC:MoFe protein complex, enabling light-driven N 2 reduction rather than energy input from fossil fuels or ATP. This illustrates how inorganic NCs can functionally replace the natural Fe protein partner, yielding a biohybrid catalyst that enables controlled electron delivery and provides not only light-driven NH 3 production but also new approaches for probing enzyme catalytic function. The CdS NC:MoFe protein biohybrid system enables light-initiated electron delivery at ambient temperature, as well as temperatures below freezing, allowing for stabilization and spectroscopic characterization of key reaction intermediates. These findings highlight how photochemical biohybrids can serve as both functional catalysts and mechanistic probes. Beyond studies of the nitrogenase mechanism, studies of the CdS NC:MoFe system reveal how variables such as NC size, electrostatic binding interactions, and sacrificial electron donors (SEDs) govern complex stability, charge transfer efficiency, and catalytic performance. In addition, studies of nitrogenase and the high activation barrier for N 2 reduction are enabling investigations of new and interesting questions regarding the properties and limitations of NC biocatalysis. In this Account, we describe the key features of CdS NC:MoFe protein biohybrids and the parameters for optimal light-driven N 2 reduction, and how controlling ET with light illuminates the path to new insights into the nitrogenase mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photophysical Properties and Phase Behavior of Ultrawide Photovoltaic Bandgap Cesium–Lead-Based Triple Halide Perovskites

Metal halide perovskite films in the top cell of triple-junction tandems require bandgaps around 2.0 eV to achieve current matching, assuming that the middle absorbing layer is the commonly used FAPbI 3 composition and the bottom cell has a bandgap around 1.1 eV. Unfortunately, mixed organic/inorganic metal halide perovskites that have the necessary Br content to reach a bandgap of 2.0 eV segregate into iodine-rich and bromine-rich phases under illumination, limiting their obtainable voltage. Previous reports have shown improved photostability using either Cs-based inorganic compositions or Cl incorporation on the X-site. Here, we investigate the inorganic triple halide compositional space CsPb­(I 1–x–y Br y Cl x ) 3 where bandgaps near 2.0 eV are expected based on the knowledge that CsPbI2Br has a bandgap of 1.90 eV. Incorporation of Cl occurs readily for x ≤ 0.07–0.10 within perovskites with a Br content of 0.3 ≤ y ≤ 0.42. When x >0.1, X-ray diffraction and photoluminescence (PL) measurements indicate that multiple compositional phases form. We hypothesize that the variable sizes of the three halide ions are not supported within the rigid Cs lattice, resulting in the formation of multiple compositional phases. The photoluminescence quantum yield of the single-phase compositional space–CsPb­(I 1–x–y Br y Cl x ) 3 where x ≤ 0.07was typically 0.001–0.004%, most likely as a result of a high defect density, including mobile iodine species. PL light-soaking measurements of many perovskite compositions with bandgaps in the range of 1.89–2.05 eV demonstrate that phase segregation occurs when initial bandgaps are above 1.95 eV regardless of halide content: indicating further iodide oxidation and corresponding migration under illumination. The conclusion is that further compositional or additive engineering is necessary for the development of inorganic triple halide compositions that accomplish the elusive goal of fabricating high-quality and photostable 2.0 eV films for use in multijunction tandems.

Electrical conductivity↗

Tuning Thermal Stability through Dopant Size in Chemically Doped DPP–Thiophene Polymers

Molecular doping of conjugated polymers (CPs) is a key strategy for improving the performance of organic electronics devices, particularly thermoelectrics. Doped donor–acceptor (D–A) conjugated polymers, characterized by a tunable energy gap between the Fermi level and the transport band, show great promise in achieving high electrical conductivity (σ) while preserving a favorable Seebeck coefficient (S). Despite the promising performance enhancement of chemically doped D–A polymers, their thermal stability remains largely underexplored, a crucial consideration for the long-term operation of organic thermoelectric devices. In this study, we investigated the dopant size-dependent thermal stability of a diketopyrrolopyrrole-thiophene (DPP-T) D–A copolymer, utilizing two p-dopants: 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F 4 TCNQ) and Mo(tfd-CO 2 Me) 3 . Temperature-dependent UV–vis–NIR spectroscopy revealed that DPP-T/F 4 TCNQ is more prone to dedoping under a high temperature thermal stress than DPP-T/Mo(tfd-CO 2 Me) 3 . Although the F 4 TCNQ doped polymer shows higher initial in-plane conductivity than its Mo(tfd-CO 2 Me) 3 counterpart, it undergoes a conductivity loss of more than an order of magnitude after annealing at 120 °C for 30 min. In contrast, the in-plane conductivity of DPP-T/Mo(tfd-CO 2 Me) 3 remains stable under the same thermal conditions. Thermogravimetric analysis ruled out dopant sublimation as a primary contributor to dedoping, leading us to attribute the conductivity loss in F 4 TCNQ-doped DPP-T to dopant phase separation and migration. This observation was further confirmed by X-ray scattering studies and nanoscale infrared microscopy and spectroscopy studies. This work could provide further insights into the thermal stability of doped conjugated polymers and suggests that incorporating bulkier dopants is an effective strategy to enhance the thermal robustness of doped DPP-type systems.

Conjugated polymers↗

Pressure-Driven Helium Insertion for Structural Stability of CH 3 NH 3 PbBr 3 Hybrid Perovskites

Organic−inorganic metal halide perovskites (MHPs) have garnered significant attention due to their outstanding performance in optoelectronic devices, but they are prone to degradation through a variety of pathways. High-pressure studies are being used to understand the mechanical and structural stability of MHPs and investigate new methods for improving these. In this study, we map the high-pressure, low-temperature structural phase diagram of CH 3 NH 3 PbBr 3 (MAPbBr 3 ) between 15−300 K and up to 1.5 GPa. We first compare the temperature and pressure effects on the global and local structures of MAPbBr 3 using synchrotron X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS), respectively, and find evidence of PbBr 6 octahedral distortion. Our results also suggest that He inserts into the MAPbBr 3 structure. The thermodynamics of He insertion into MAPBHe x are calculated to be plausible at room temperature for x ≤ 1 and P = 1−3 GPa and shown to stabilize higher-symmetry phases. This phenomenon increases the fitted bulk modulus of MAPbBr 3 . Structural stabilization by inert atom insertion is proposed as a method to improve the mechanical robustness of MHPs and other soft hybrid materials.

Diffraction↗

Synthesis and Characterization of [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ) for Light-Driven Quantum Dot-Catalyst Hydrogen Evolution

Light-driven hydrogen generation from water is a route to carbon-neutral fuels. However, the integrated light absorbers and catalysts must be compatible and functional under the same conditions. A sulfate-functionalized complex, [Ni(H 2 O)(7-P Ph 2 N ArSO3 ) 2 ](NaBF 4 ), where P Ph 2 N ArSO3 = 4-(3,6-diphenyl-1,3,6-azadiphosphepan-1-yl)benzenesulfonate), was synthesized and characterized. A solid-state structure from single-crystal X-ray crystallography is also reported. The electrocatalytic activity for hydrogen evolution of this complex in 7:3 H 2 O:CH 3 CN was characterized by cyclic voltammetry and controlled potential electrolysis, with a maximum observed rate of 83 s –1 . Density functional theory was used to characterize the favorable binding of the sulfate functionalities to cadmium sulfide quantum dots. Experimental assembly of these catalysts onto cadmium sulfide quantum dots was successful. In conclusion, both fast electron transfer and light-driven pH-dependent hydrogen evolution were observed.

36 MATERIALS SCIENCE↗