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At least 739 records · Page 41

Weakly solvating electrolytes: a solvation-centric paradigm for rechargeable metal batteries

Electrolyte design has long followed a solvation-first paradigm that prioritizes solvents capable of maximizing salt dissociation and ionic conductivity, while treating interfacial degradation and rheological limitations as secondary constraints. Although this approach has enabled significant progress in lithium-ion and sodium-ion batteries, it inherently favors solvent-dominated solvation structures that destabilize reactive metal interfaces. Weakly solvating electrolytes (WSEs) offer a fundamentally different strategy. By using solvents with intrinsically low donor strength and minimal electrostatic affinity for cations, WSEs suppress cation–solvent coordination and promote anion-rich solvation shells without relying on salt superconcentration. This shift lowers desolvation barriers, redirects interfacial decomposition pathways, and supports the formation of inorganic-rich, stable interphases. In this review, we discuss the molecular and solvation criteria that distinguish WSEs from conventional and concentrated or locally concentrated electrolyte systems, examine their implementation across different chemistries, and identify unresolved design challenges. WSEs are presented not as a niche formulation, but as a solvation-centric framework for rethinking electrolyte function in metal battery technologies.

Karbak, Mehdi [Pacific Northwest National Laborato↗

Next-generation tunnel FETs: exploring material perspectives and areal tunneling configurations

The end of Dennard scaling, which facilitated proportional increases in computing power without added energy costs until the mid-2000s, has underscored the urgent need for innovative semiconductor devices that can enhance energy efficiency. Tunnel field-effect transistors (TFETs) have emerged as promising candidates to surpass the energy efficiency of conventional metal oxide semiconductor field-effect transistors (MOSFETs). Unlike MOSFETs, which rely on thermionic emission to overcome the source-channel potential barrier, TFETs operate through quantum tunneling, potentially enabling sub-60 mV dec −1 subthreshold swing (SS) for low-voltage operation. However, lateral TFETs have faced challenges in achieving adequate on-state current (I ON ) and a broad SS operation window, limiting their practical utility. This review article advocates for areal TFETs, which utilize face-to-face tunnel junctions that ideally offer step-function current turn-on characteristics and allow I ON to scale with device area rather than width. We highlight recent advancements in integrating 2D materials into tunneling structures, which could facilitate efficient band-to-band tunneling through atomically thin layers, while addressing challenges of gate field screening. We then discuss the nearer-term prospects of epitaxial areal TFETs comprising III–V compound semiconductors and group-IV semiconductors based on recent experimental progress. The review examines both quantum mechanical and semiclassical modeling approaches for TFETs, including techniques to reduce the computational complexity. The article delves into ongoing challenges in material synthesis, interface engineering, device fabrication, and integration pathways, concluding with recommendations for future research directions to overcome the fundamental power density limitations of conventional transistor technology.

2D materials↗

Coevolution of the Ess1-CTD axis in polar fungi suggests a role for phase separation in cold tolerance

Most of the world’s biodiversity lives in cold (-2° to 4°C) and hypersaline environments. To understand how cells adapt to such conditions, we isolated two key components of the transcription machinery from fungal species that live in extreme polar environments: the Ess1 prolyl isomerase and its target, the carboxy-terminal domain (CTD) of RNA polymerase II. Polar Ess1 enzymes are conserved and functional in the model yeast, Saccharomyces cerevisiae. By contrast, polar CTDs diverge from the consensus (YSPTSPS) 26 and are not fully functional in S. cerevisiae. These CTDs retain the critical Ess1 Ser-Pro target motifs, but substitutions at Y1, T4, and S7 profoundly affected their ability to undergo phase separation in vitro and localize in vivo. We propose that environmentally tuned phase separation by the CTD and other intrinsically disordered regions plays an adaptive role in cold tolerance by concentrating enzymes and substrates to overcome energetic barriers to metabolic activity.

59 BASIC BIOLOGICAL SCIENCES↗

Establishing the Role of Metal, Interface, and Vacancy Sites in Pt/TiO 2 -Catalyzed Acetic Acid Hydrodeoxygenation

Catalytic hydrodeoxygenation (HDO) following catalytic fast pyrolysis (CFP) offers an approach to convert the vapor-phase product of biomass pyrolysis to a stable bio-oil product by reducing the oxygen content. Fundamental insights into the HDO of carboxylic acids, which are a corrosive and acidic CFP product, on promising catalyst materials, such as Pt/TiO 2 , are needed to inform the design of multifunctional HDO catalysts with improved carbon efficiency. In this contribution, density functional theory (DFT) calculations were used to assess the role of Pt-metal and Pt-TiO 2 -interface sites on acetic acid HDO (AA-HDO), and to determine the effect of interfacial oxygen vacancies at the Pt-TiO 2 interface, by calculating the reaction energetics for key AA-HDO surface intermediates and elementary steps on each site type. Pt-metal sites, modeled via Pt(111), preferred to form undesired decarboxylation products (CH 4 and CO 2 ), whereas Pt-TiO 2 -interface sites, modeled via an anatase-supported Pt nanowire, favored the formation of desired deoxygenation products (acetaldehyde and ethane). Interfacial-vacancy sites lowered the activation energy barrier for the first C-O bond-scission step in AA-HDO, predicted to be the rate-limiting step for AA-HDO at the Pt-TiO 2 interface in the absence of a vacancy. These atomistic insights reveal the importance of metal-metal oxide interface sites in AA-HDO selectivity and can be used to inform the rational design of improved HDO catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Predictive Design of Hybrid Improper Ferroelectric Double Perovskite Oxides

The computational design of suitable multiferroic double perovskite oxides requires finding materials that exhibit sizable polarization, magnetization, and coupling between them. Oxides with the chemical formula of AA'BB'O 6 with building blocks of ABO 3 single perovskite oxides in centrosymmetric Pnma symmetry are strong candidates that have been reported to satisfy such criteria. The system lowers to noncentrosymmetric, polar P2 1 symmetry if A/A' layered and B/B' rocksalt cation orderings are imposed. A detailed compositional search over a variety of chemical spaces followed by evaluating their polarization may lead to the identification of more of these compounds with ferroelectric ordering. The standard density functional theory practices to estimate polarization within the Berry phase formalism require the systems to be perfectly insulating. The number of compounds that can be evaluated using this method is therefore limited. In this work, we introduce a predictive learning strategy based on importance sampling to build a series of machine learning models using results from first-principles simulations to predict polarization and the corresponding switching barrier. The geometry-driven features related to charge states and cationic radii play key roles in predicting the switching barrier with complementary contributions from the key structural mode-based order parameters. These modes become important to draw reasonable predictions of polarization components from machine learning models. In conclusion, our predictive models identify candidates with high polarizations and low switching barriers from a pool of double perovskite oxides, suitable for future investigation for their potential applications in spintronic devices.

36 MATERIALS SCIENCE↗

Periodic Trends in Adsorption Energies around Single-Atom Alloy Active Sites

Single-atom alloys (SAAs) make up a special class of alloy surface catalysts that offer well-defined, isolated active sites in a more inert metal host. The dopant sites are generally assumed to have little or no influence on the properties of the host metal, and transport of chemical reactants and products to and from the dopant sites is generally assumed to be facile. Here, by performing density functional theory calculations and surface science experiments, we identify a new physical effect on SAA surfaces, whereby adsorption is destabilized by ≤300 meV on host sites within the perimeter of the reactive dopant site. We identify periodic trends for this behavior and demonstrate a zone of exclusion around the reactive sites for a range of adsorbates and combinations of host and dopant metals. Experiments confirm an increased barrier for diffusion of CO toward the dopant on a RhCu SAA. Furthermore, this effect offers new possibilities for understanding and designing active sites with tunable energetic landscapes surrounding them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Defect characterization and charge transport measurements in high-resolution Ni/n-4H-SiC Schottky barrier radiation detectors fabricated on 250 μ m epitaxial layers

Advances in the growth processes of 4H-SiC epitaxial layers have led to the continued expansion of epilayer thickness, allowing for the detection of more penetrative radioactive particles. In this work, we report the fabrication and characterization of high-resolution Schottky barrier radiation detectors on 250 μm thick n-type 4H-SiC epitaxial layers, the highest reported thickness to date. Several 8 × 8 mm 2 detectors were fabricated from a diced 100 mm diameter 4H-SiC epitaxial wafer grown on a conductive 4H-SiC substrate with a mean micropipe density of 0.11 cm -2 From the Mott–Schottky plots, the effective doping concentration was found to be in the range (0.95–1.85) × 10 14 cm -3 , implying that full depletion could be achieved at ~5.7 kV (0.5 MV/cm at the interface). The current-voltage characteristics demonstrated consistently low leakage current densities of 1–3 nA/cm 2 at a reverse bias of -800 V. This resulted in the pulse-height spectra generated using a 241Am alpha source (5486 keV) manifesting an energy resolution of less than 0.5% full width at half maximum (FWHM) for all the detectors at -200 V. The charge collection efficiencies (CCEs) were measured to be 98–99% with no discernable correlation to the energy resolution. A drift-diffusion model fit to the variation of CCE as a function of bias voltage, revealed a minority carrier diffusion length of ~10 μm. Deep level transient spectroscopy measurements on the best resolution detector revealed that the excellent performance was the result of having ultralow concentrations of the order of 1011 cm-3 lifetime limiting defects—Z 1/2 and EH 6/7 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Adsorption and Surface Diffusion of Metals on α-Al2O3 for Advanced Manufacturing Applications

Abstract The adsorption and diffusion of Mo and Nb adatoms on the $$\alpha$$ α -Al 2 O 3 (0001) surface were explored using density functional theory-based methods. Adsorption energies of Mo and Nb adatoms at minima sites on the surface were determined. Mo and Nb adatoms prefer to adsorb to the same locations on the surface, and larger adsorption energies calculated for Nb compared to Mo indicate that Nb adatom-surface interactions are stronger than Mo. Using minima adsorption sites as initial and final locations for surface diffusion, energy barriers for diffusion were calculated using the nudged elastic band method. Overall, Mo and Nb follow roughly the same diffusion paths. The diffusion pre-factors for Mo and Nb are similar; however, Mo diffusion has a lower energy barrier and thus a larger diffusion coefficient compared with Nb. These results provide insight into the role of surface diffusion of Mo and Nb adatoms during advanced manufacturing processes.

Biaggne, Austin (ORCID:0000000328074960)↗

Plasmon-Induced CO 2 Conversion on Al@Cu 2 O: A DFT Study

In plasmonic catalysis, localized surface plasmon was leveraged to drive chemical reactions. This approach is promising for catalyzing many challenging reactions at relatively low temperatures and pressures. We apply density functional calculations to provide the insight for the mechanism of plasmon-induced direct CO 2 dissociation on an Al@Cu 2 O core-shell structure, which was observed in a previous experimental study. We show that the interaction of Cu 2 O with CO 2 results in the accessible antibonding states of the adsorbed CO 2 in the range of visible light. Though the intrinsic activation barrier for direct CO 2 dissociation is as high as 3.6 eV, we find that an effective reaction barrier of CO 2 dissociation under photon excitation could be reduced by 2 eV. We also show that the charge transfer is more pronounced in the final state of the dissociation due to the strong hybridization of the dissociated species with Cu 2 O. These results thus provide an explanation for the visible-light-induced direct CO 2 dissociation at relatively low temperature and under ambient pressure. This finding also shows the promising impact of plasmonic catalysis in mitigating carbon emission.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Activity of Ni Clusters Supported on TiC(001) toward CO 2 and H 2 Dissociation

Small Ni particles supported on TiC(001) were shown to display a very high activity for the catalytic hydrogenation of CO 2 but the underlying chemistry is, to a large extent, unknown. Here, by means of periodic density functional theory (DFT) calculations with the BEEF–vdW functional, we explore the adsorption and subsequent dissociation of CO 2 and H 2 on several Ni n clusters ( n = 4, 9, 13, and 16) supported on TiC(001) and compare the results to those obtained for the bare Ni(111) and TiC(001) surfaces using exactly the same computational approach. The calculations reveal that the Ni n /TiC system exhibits stronger adsorption energies and lower dissociation energy barriers for CO 2 and H 2 than the bare Ni(111) and TiC(001) surfaces. Furthermore, this is in line with the experimental finding evidencing that the Ni/TiC system has a catalytic activity higher than that of the separated Ni and TiC constituents. In addition, the calculated results show that two-dimensional (2D) supported clusters adsorb CO 2 and H 2 stronger than the three-dimensional (3D) supported clusters and also the 2D clusters exhibit lower energy barriers for CO 2 dissociation. Within the 2D supported clusters, larger particles feature slightly stronger adsorption energies and lower CO 2 dissociation energy barriers. Finally, H 2 dissociation proceeds with a very low energy barrier on all of the studied models, which makes these novel systems potential good candidates for hydrogenation reactions.

36 MATERIALS SCIENCE↗

Single-hole couplings in GaAs/AlGaAs double dots probed with transport and EDSR spectroscopy

Here, we report a detailed study of the tunnel barriers within a single-hole GaAs/AlGaAs double quantum dot device (DQD). For quantum information applications as well as fundamental studies, careful tuning and reliable measurements of the barriers are important requirements. In order to tune a DQD device adequately into the single-hole electric dipole spin resonance regime, one has to employ a variety of techniques to cover the extended range of tunnel couplings. In this work, we demonstrate four separate techniques, based upon charge sensing, quantum transport, time-resolved pulsing, and electron dipole spin resonance spectroscopy to determine the couplings as a function of relevant gate voltages and magnetic field. Measurements were performed under conditions of both symmetric and asymmetric tunnel couplings to the leads. Good agreement was observed between different techniques when measured under the same conditions. The results indicate that even in this relatively simple circuit, the requirement to tune multiple gates and the consequences of real potential profiles result in non-intuitive dependencies of the couplings as a function of the plunger gate voltage and the magnetic field.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction

Abstract The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior skill than traditional physics-based NWP. However, among these leading DL models, there is a wide variance in both the training settings and architecture used. Further, the lack of thorough ablation studies makes it hard to discern which components are most critical to success. In this work, we show that it is possible to attain high forecast skill even with relatively off-the-shelf architectures, simple training procedures, and moderate compute budgets. Specifically, we train a minimally modified Swin Transformer V2 (SwinV2) on ERA5 data and find that it attains superior skill in terms of mean-square errors of deterministic forecasts when compared against the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS). Almost all DL–NWP systems share a core set of hyperparameters and design decisions. To aid and expedite future DL–NWP research, we present an in-depth, systematic exploration of different loss functions, model sizes and depths, patch sizes, and multistep training objectives. We also examine the model performance with metrics beyond the typical accuracy (ACC) and RMSE and investigate how the performance scales with model size. Through our open-source code, scoring pipelines, and models, we share our findings on key aspects of the training pipeline. These ablations reduce the necessity for expensive hyperparameter tuning and lower the barrier to entry for future DL–NWP research. Significance Statement This study investigates the potential of using large-scale transformer-based models for weather prediction, showing that it is possible to achieve high forecast accuracy with simpler, off-the-shelf architectures. By training a minimally modified SwinV2 transformer on ERA5 data, we show that the model achieves competitive forecast skill in terms of mean-square error for key variables, outperforming the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS) at all lead times. Our findings suggest that effective training strategies, such as multistep fine-tuning and channel-weighted losses, significantly enhance the model’s performance. However, we also highlight that these improvements come with trade-offs in other areas, such as ensemble spread and high-frequency spatial detail. This work highlights the promise of deep learning in improving weather forecasts, which could lead to better preparedness and response to weather events, ultimately benefiting society by providing more reliable weather predictions.

Willard, Jared D. [Lawrence Berkeley National Labo↗

Wood Decomposition: Understanding Processes Regulating Carbon Transfer to Soil Carbon Pools Using FACE Wood at Multiple Scales

Dead wood comprises approximately 20% of forest biomass. While it is widely recognized for its role in ecosystem functions relative to habitat and nutrient cycling, there are considerable uncertainties associated with its role in the forest carbon (C) cycle. The principal uncertainty is whether dead wood contributes to the soil C pool. With little supporting evidence, the presumption is that C in wood is respired back to the atmosphere through decomposition processes. The inability to attribute forest soil C to its source components has been a barrier to addressing this important forest carbon cycle question. The U.S. Dept. of Energy’s Free Air CO 2 Enrichment (FACE) experiment produced wood that has a distinct δ 13 C signature that can be used to trace its fate through organic matter decomposition processes. Using two hardwood species (aspen, birch) from the Rhinelander FACE site and pine from the Duke FACE site, the FACE Wood Decomposition Experiment (FWDE) was established in 2011 to provide the foundation for addressing wood decomposition and its associated processes at the continental scale. Plots were installed on nine experimental forests representing a range in bioclimatic forest conditions within the continental U.S. Each identical plot has logs of the three species incubating on the soil surface and pine logs suspended in the air, representing standing dead wood. Abiotic conditions are monitored continuously, and soil and forest conditions characterized. Logs on the sites have been measured every two years to assess decay. This project was initiated in 2016 with specific objectives to: (a) determine whether dead wood C contributes to the soil C pool, (b) assess the fungal community composition mediating the decay, (c) assess the interactions of termites with microbial decay, and (d) develop a mechanistic model to simulate wood decomposition. The principal field sampling was conducted in 2017; correspondingly, the results reported here represent six years of decomposition. Wood decomposition varied from 13 to 75 % loss across the bioclimatic gradient. Sites in the southeastern U.S. coastal plain and piedmont had fastest decomposition rates for each of the species. In contrast sites in the Rocky Mountains had the slowest decay rates, which were associated with cold temperatures. Standing deadwood decomposes at a much slower rate than logs on the soil surface; a response due to differences in wood moisture content. Wood carbon was measured in the mineral soil across each of the sites; accordingly, this is the first study to affirm that a portion of the wood C does become part of the soil C pool. Averaged across the FWDE sites, approximately 1.4% of the soil C in the upper 10 cm of the mineral soil directly beneath the log was derived from the deadwood; within 50 cm of the log, wood C accounted for an average of 2.1%. These results demonstrate that the contribution of deadwood to the soil C pool is a soil volume surrounding the log; and it’s likely a larger volume than what we sampled. We also hypothesized that there would be more wood C in the mineral soil when termites were present. However, that hypothesis wasn’t supported by measurements on the Santee Experimental Forest termite exclusion (SEF-TX) plots under FACE logs that incubated for 6 years. Across all the sites, the majority of the wood C was transferred to the atmosphere. Approximately 7,000 fungal species were sequenced. The fungal communities were different among each of the sites suggesting local colonization; interestingly, within sites the three species also exhibited differences in fungal community composition. White rot was the dominant fungal form in pine and hardwood, which yields less lignin in the wood residue. Brown rot occurred in approximately 20% of the pine and aspen logs, and it did not occur in birch logs. The occurrence of brown rot was only weakly correlated to site factors. We conducted two additional experiments to assess the effects of termites on wood decomposition and the associated interactions with the fungal community. Pine and birch logs were incubated on the Santee Experimental Forest termite exclusion plots in upland and riparian settings. There was no difference in decay between areas where termites were able colonize and plots where they had been excluded. Highly variable foraging by termites was a primary contributor the result. Correspondingly, fungal communities did not vary on logs incubated among the two treatments, but they did reflect site and species differences. The second experiment was conducted on each of the nine FWDE sites where pine and birch wood blocks were incubated for two years with and without a wrapping designed to exclude termites and other arthropods. The effects of termites on wood decomposition could be confirmed on two of the four sites known to have subterranean termites. On the two southeastern sites, termites contributed approximately 8% to mass loss in pine blocks over two years. A major factor clouding the role of termites in wood decomposition is the inability to assess the time, duration, and intensity of the foraging with the logs. Another uncertainty is related to whether a piece of wood will be foraged. A process-based wood decomposition model was developed representing biological processes mediated by fungi, bacteria, termites, beetles, as well as physical and chemical processes. The Coarse Wood Decomposition Model (CWDM) was parameterized based on a thorough review of the literature and it was validated using data from the FWDE. In the initial setup, the model considers softwoods and hardwoods groups, as opposed to individual species. Sensitivity analyses incorporating climate data from 89 locations in North America demonstrated that CWDM was stable from the tropics to the boreal zone. Model calibration and validation showed it to perform very well. The CWDM is poised for additional testing with subsequent FWDE data as well as other data sets, and it is available for incorporation into forest biogeochemical models or DOEs Earth System Modeling framework.

54 ENVIRONMENTAL SCIENCES↗

Multistability of isolated and hydrogenated Ga–O divacancies in β–Ga 2 O 3

This work systematically explores 19 unique configurations of the close-associate Ga–O divacancies (V Ga V O ) in β–Ga 2 O 3 , including their complexes with H impurities, using hybrid functional calculations. Interestingly, most configurations are found to retain the negative-U behavior of V O , as they exhibit a thermodynamic (–/3–) charge-state transition level energetically located in the upper part of the band gap, where the 3– charge state is associated with the formation of a Ga–Ga dimer. The energy positions of the thermodynamic (–/3–) charge-state transition levels divide the divacancy configurations into three different groups, which can be understood from the three possible Ga–Ga dimerizations resulting from the tetrahedral and octahedral Ga sites. The relative formation energies of the different divacancy configurations, and hence the electrical activity of the divacancies, is found to depend on the Fermi-level position, and the energy barriers for transformation between different divacancy configurations are explored from nudged elastic band calculations. Hydrogenation of the divacancies is found to either passivate their negative-U charge-state transition levels or shift them down in Fermi level position, depending on whether the H resides at V O or forms an O–H bond at V Ga , respectively. Finally, the divacancy is discussed as a potential origin of the so-called E$^{*}_{2}$ center previously observed by deep-level transient spectroscopy.

36 MATERIALS SCIENCE↗

Hydrogen trapping energetics at BCC iron-helium interfaces

Density functional theory (DFT) calculations have been performed to assess the trapping and segregation strength of hydrogen (H) to helium (He) interfaces in BCC (Fe) as a function of He density and surface orientation. The He density ranges from 0 to 2 He/V which corresponds to equilibrium bubbles that are expected to form in the structural components in a fusion reactor environment. The DFT calculations consist of a slab of BCC metal and an initial lattice of FCC He. Here, the report on the binding energy of H to these interfaces as well as the migration barriers into and away from the surface, which together provide information on the de-trapping energy for H at He bubbles. It was found that the binding energy of H to He-Fe interfaces decreases with increasing He density. Migration barriers are also modified due to the He density, which are sensitive to the surface orientation as well as the diffusion pathway. These results provide valuable first-principles energetics that are necessary for higher-order, mesoscale models, and provide insight into the extent to which He bubbles may trap tritium in fusion structural materials.

42 ENGINEERING↗

Computational Study of an Iron(II) Polypyridine Electrocatalyst for CO 2 Reduction: Key Roles for Intramolecular Interactions in CO 2 Binding and Proton Transfer

A solar-driven conversion of CO 2 into fuels by artificial photosynthesis would not only mitigate the greenhouse effect but also provide an alternative to obtain fuels in a renewable fashion. To this end, the new iron polypyridine catalyst [Fe(bpy NHEt PY2Me)L 2 ] 2+ (L = H 2 O, CH 3 CN) was recently developed for the electrochemical reduction of CO 2 to CO. Here, we performed density functional theory (DFT) electronic structure calculations to shed light on a possible pathway for CO 2 reduction and the origin of the selectivity between CO 2 reduction versus the hydrogen evolution reaction. The metal center remains Lewis acidic throughout the reduction process due to ligand loss and mainly ligand-based reduction stabilized by antiferromagnetic coupling to a high-spin Fe(II) center. This results in a high barrier for hydride formation but a facile addition and activation of CO 2 via an η 2 coordination and stabilizing hydrogen bonding by the amine group. The second unoccupied equatorial coordination site opens up the possibility for an intramolecular protonation with a coordinated water ligand. This facilitates protonation because not only CO 2 but also the proton source H 2 O is activated and properly aligned for a proton transfer due to the Fe-OH 2 bond; consequently, both protonation steps are facile. The moderate ligand field allows a rapid ligand exchange for a second intramolecular protonation step and facilitates an exergonic CO release. The lower selectivity of the related [Fe(bpy OH PY2Me)L 2 ] 2+ complex can be related to its more acidic second coordination sphere, which enables an intramolecular proton transfer that is kinetically competitive with CO 2 addition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The role of native defects and their diffusivity in CdTe

CdTe is a leading thin-film technology for solar-cell applications. Basic features such as the optimum band gap of 1.5 eV and simple manufacturing process have been driving the research on improving the current record efficiency of 22% for CdTe solar cells toward the theoretical limit of 32%. Low p-type doping and short carrier lifetimes in the CdTe absorber have been suggested as the main limiting factors and attributed to defect compensation and carrier recombination. Understanding the role of point defects and impurities in CdTe is crucial to solving these problems. Despite many years of research, the sources of compensation and the microscopic recombination mechanisms are still unclear. By using hybrid density functional calculations with spin-orbit coupling and large supercells, we investigate the electronic properties, the formation energies, and the diffusivities of the native defects in CdTe. As possible sources of compensation for p-type conductivity, we discuss the structural and electronic properties of Cd interstitial, Te vacancies, and TeCd antisites. The stability of each defect is discussed in terms of both the defect formation energy and the migration barrier. We also address possible mechanisms that lead to non-radiative recombination.

14 SOLAR ENERGY↗

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1-x-yScxGdyN Heterostructural Alloys

Ternary nitride alloys based on wurtzite AlN are a promising platform to realize functional materials, particularly ferroelectrics and optical emitters, that can smoothly integrate with conventional microelectronics. Here, a strategic design is presented to enable multifunctional materials by substituting multiple elements into AlN to create quaternary nitride alloys. By combining computational predictions and combinatorial thin film synthesis, the phase diagram of these quaternary Al-Sc-Gd-N alloys (or pseudo-ternary heterostructural AlN-ScN-GdN alloys) is successfully predicted as a function of effective temperature, and we experimentally grow Al1-x-xScxGdyN thin films for the first time. It is revealed that Al1-x-xScxGdyN crystallizes in a wurtzite-derived structure for X + y <~ 0.35, consistent with the calculated phase diagram. The computational investigation explores whether co-substitution induces cooperative effects on these alloys' piezoelectric and ferroelectric properties, finding that it is beneficial for reducing the polarization switching barrier. We calculate that Al1-x-xScxGdyN thin films should display ferroelectric switching. This is supported by our experimental measurements of a high optical bandgap, enhanced piezoelectric coefficient, and a change in the calculated polarization switching mechanism, and we achieve preliminary ferroelectric switching that experimentally realizes the prediction. Overall, our work sets the foundation toward quaternary wurtzite-nitride-based multifunctional materials, including piezoelectrics, ferroelectrics, and possibly even multiferroics.

36 MATERIALS SCIENCE↗