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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Distinct Mechanisms of Triplet Pair Decay in Amorphous and Crystalline Heteroacene Thin Films

Triplet pairs (TT) in crystalline molecular semiconductors have unique spin properties of interest for quantum information or enhancing solar photoconversion. The population and diffusion dynamics of TT have been the subject of recent studies, both in covalent dimers and in crystalline systems. Here, in this study, we monitor the triplet population in neat polycrystalline and amorphous films of a heteroacene with known TT spectral properties and tunable spin polarization depending on the intermolecular geometry. Transient measurements reveal an anomalous power dependence in polycrystalline films that we attribute to the fast diffusion and interaction of dissociated triplet pairs confined to one-dimensional stacks of strongly coupled molecules. The nongeminate triplet interaction after dephasing facilitates conversion to the triplet 3 TT and eventually T 1 +S 0 . Amorphous films have no power dependence and proceed directly from 1 TT to 3 TT and subsequently T 1 +S 0 via state mixing facilitated by nonparallel geometries and weak exchange coupling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Integrating terrestrial scavenging ecology into contemporary wildlife conservation and management

Scavenging plays a vital role in maintaining ecosystem health and contributing to ecological functions; however, research in this sub-discipline of ecology is underutilized in developing and implementing wildlife conservation and management strategies. We provide an examination of the literature and recommend priorities for research where improved understanding of scavenging dynamics can facilitate the development and refinement of applied wildlife conservation and management strategies. Due to the application of scavenging research broadly within ecology, scavenging studies should be implemented for informing management decisions. In particular, a more direct link should be established between scavenging dynamics and applied management programs related to informing pharmaceutical delivery and population control through bait uptake for scavenging species, prevention of unintentional poisoning of nontarget scavenging species, the epidemiological role that scavenging species play in disease dynamics, estimating wildlife mortalities, nutrient transfer facilitated by scavenging activity, and conservation of imperiled facultative scavenging species. This commentary is intended to provide information on the paucity of data in scavenging research and present recommendations for further studies that can inform decisions in wildlife conservation and management. Additionally, we provide a framework for decision making when determining how to apply scavenging ecology research for management practices and policies. Due to the implications that scavenging species have on ecosystem health, and their overall global decline as a result of anthropic activities, it is imperative to advance studies in the field of scavenging ecology that can inform applied conservation and management programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hidden Features: How Subsurface and Landscape Heterogeneity Govern Hydrologic Connectivity and Stream Chemistry in a Montane Watershed

ABSTRACT Hydrologic connectivity is defined as the connection among stores of water within a watershed and controls the flux of water and solutes from the subsurface to the stream. Hydrologic connectivity is difficult to quantify because it is goverened by heterogeniety in subsurface storage and permeability and responds to seasonal changes in precipitation inputs and subsurface moisture conditions. How interannual climate variability impacts hydrologic connectivity, and thus stream flow generation and chemistry, remains unclear. Using a rare, four‐year synoptic stream chemistry dataset, we evaluated shifts in stream chemistry and stream flow source of Coal Creek, a montane, headwater tributary of the Upper Colorado River. We leveraged compositional principal component analysis and end‐member mixing to evaluate how seasonal and interannual variation in subsurface moisture conditions impacts stream chemistry. Overall, three main findings emerged from this work. First, three geochemically distinct end members were identified that constrained stream flow chemistry: reach inflows, and quick and slow flow groundwater contributions. Reach inflows were impacted by historic base and precious metal mine inputs. Bedrock fractures facilitated much of the transport of quick flow groundwater and higher‐storage subsurface features (e.g., alluvial fans) facilitated the transport of slow flow groundwater. Second, the contributions of different end members to the stream changed over the summer. In early summer, stream flow was composed of all three end members, while in late summer, it was composed predominantly of reach inflows and slow flow groundwater. Finally, we observed minimal differences in proportional composition in stream chemistry across all four years, indicating seasonal variability in subsurface moisture and spatial heterogeneity in landscape and geologic features had a greater influence than interannual climate fluctuation on hydrologic connectivity and stream water chemistry. These findings indicate that mechanisms controlling solute transport (e.g., hydrologic connectivity and flow path activation) may be resilient (i.e., able to rebound after perturbations) to predicted increases in climate variability. By establishing a framework for assessing compositional stream chemistry across variable hydrologic and subsurface moisture conditions, our study offers a method to evaluate watershed biogeochemical resilience to variations in hydrometeorological conditions.

Johnson, Keira [College of Earth, Ocean, and Atmos↗
DOE OSTI2021

CHARMM-GUI Drude prepper for molecular dynamics simulation using the classical Drude polarizable force field

Explicit treatment of electronic polarizability in empirical force fields (FFs) represents an extension over a traditional additive or pairwise FF and provides a more realistic model of the variations in electronic structure in condensed phase, macromolecular simulations. To facilitate utilization of the polarizable FF based on the classical Drude oscillator model, Drude Prepper has been developed in CHARMM-GUI. Drude Prepper ingests additive CHARMM protein structures file (PSF) and pre-equilibrated coordinates in CHARMM, PDB, or NAMD format, from which the molecular components of the system are identified. These include all residues and patches connecting those residues along with water, ions, and other solute molecules. This information is then used to construct the Drude FF-based PSF using molecular generation capabilities in CHARMM, followed by minimization and equilibration. In addition, inputs are generated for molecular dynamics (MD) simulations using CHARMM, GROMACS, NAMD, and OpenMM. Validation of the Drude Prepper protocol and inputs is performed through conversion and MD simulations of various heterogeneous systems that include proteins, nucleic acids, lipids, polysaccharides, and atomic ions using the aforementioned simulation packages. Stable simulations are obtained in all studied systems, including 5 μs simulation of ubiquitin, verifying the integrity of the generated Drude PSFs. Additionally, the ability of the Drude FF to model variations in electronic structure is shown through dipole moment analysis in selected systems. Finally, the capabilities and availability of Drude Prepper in CHARMM-GUI is anticipated to greatly facilitate the application of the Drude FF to a range of condensed phase, macromolecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Comparing π‐complexation capabilities of ionic liquids containing silver(I) and copper(I) ions by headspace single drop microextraction in combination with high‐performance liquid chromatography

Selective π‐complexation capabilities of silver(I) and copper(I) ions can be effectively facilitated in ionic liquids. To understand the effects of environmental factors that influence the π‐complexation of these metal ions with analytes, techniques that employ small volumes of ionic liquid that can be readily analyzed are desired. In this study, headspace single drop microextraction coupled with HPLC is used to investigate a diverse set of environmental factors on the metal ion‐mediated complexation with aromatic compounds in ionic liquid media. Silver(I) and copper(I) bis[(trifluoromethyl)sulfonyl]imide salts were both studied by dissolving them in the 1‐decyl‐3‐methylimidazolium bis[(trifluoromethyl)sulfonyl]imide ionic liquid and employing the mixture as extraction media for aromatic compounds. Water and acetonitrile within the sample solution were observed to interfere with the complexation of silver(I) ions and aromatic compounds, while ethylene glycol and triethylene glycol did not. The temperature and extraction times were optimized to fully facilitate the π‐complexation capabilities of metal ions in ionic liquid media. Partition coefficients between the sample headspace and metal ion were determined using a three‐phase equilibria model. Although no discernable difference in analyte partitioning between the headspace and ionic liquid solvent was observed, analyte partition coefficients to silver(I) ion tended to be greater compared to copper(I) ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Structural and biochemical analyses of selectivity determinants in chimeric Streptococcus Class A sortase enzymes

Abstract Sequence variation in related proteins is an important characteristic that modulates activity and selectivity. An example of a protein family with a large degree of sequence variation is that of bacterial sortases, which are cysteine transpeptidases on the surface of gram‐positive bacteria. Class A sortases are responsible for attachment of diverse proteins to the cell wall to facilitate environmental adaption and interaction. These enzymes are also used in protein engineering applications for sortase‐mediated ligations (SML) or sortagging of protein targets. We previously investigated SrtA from Streptococcus pneumoniae , identifying a number of putative β7–β8 loop‐mediated interactions that affected in vitro enzyme function. We identified residues that contributed to the ability of S. pneumoniae SrtA to recognize several amino acids at the P1′ position of the substrate motif, underlined in LPXT G , in contrast to the strict P1′ Gly recognition of SrtA from Staphylococcus aureus . However, motivated by the lack of a structural model for the active, monomeric form of S. pneumoniae SrtA, here, we expanded our studies to other Streptococcus SrtA proteins. We solved the first monomeric structure of S. agalactiae SrtA which includes the C‐terminus, and three others of β7–β8 loop chimeras from S. pyogenes and S. agalactiae SrtA. These structures and accompanying biochemical data support our previously identified β7–β8 loop‐mediated interactions and provide additional insight into their role in Class A sortase substrate selectivity. A greater understanding of individual SrtA sequence and structural determinants of target selectivity may also facilitate the design or discovery of improved sortagging tools.

Gao, Melody↗
DOE OSTI2024

Structural studies of intrinsically disordered MLL -fusion protein AF9 in complex with peptidomimetic inhibitors

AF9 (MLLT3) and its paralog ENL(MLLT1) are members of the YEATS family of proteins with important role in transcriptional and epigenetic regulatory complexes. These proteins are two common MLL fusion partners in MLL -rearranged leukemias. The oncofusion proteins MLL-AF9/ENL recruit multiple binding partners, including the histone methyltransferase DOT1L, leading to aberrant transcriptional activation and enhancing the expression of a characteristic set of genes that drive leukemogenesis. The interaction between AF9 and DOT1L is mediated by an intrinsically disordered C-terminal ANC1 homology domain (AHD) in AF9, which undergoes folding upon binding of DOT1L and other partner proteins. We have recently reported peptidomimetics that disrupt the recruitment of DOT1L by AF9 and ENL, providing a proof-of-concept for targeting AHD and assessing its druggability. Intrinsically disordered proteins, such as AF9 AHD, are difficult to study and characterize experimentally on a structural level. In this study, we present a successful protein engineering strategy to facilitate structural investigation of the intrinsically disordered AF9 AHD domain in complex with peptidomimetic inhibitors by using maltose binding protein (MBP) as a crystallization chaperone connected with linkers of varying flexibility and length. The strategic incorporation of disulfide bonds provided diffraction-quality crystals of the two disulfide-bridged MBP–AF9 AHD fusion proteins in complex with the peptidomimetics. These successfully determined first series of 2.1–2.6 Å crystal complex structures provide high-resolution insights into the interactions between AHD and its inhibitors, shedding light on the role of AHD in recruiting various binding partner proteins. We show that the overall complex structures closely resemble the reported NMR structure of AF9 AHD/DOT1L with notable difference in the conformation of the β-hairpin region, stabilized through conserved hydrogen bonds network. These first series of AF9 AHD/peptidomimetics complex structures are providing insights of the protein–inhibitor interactions and will facilitate further development of novel inhibitors targeting the AF9/ENL AHD domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗
DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mechanism of Contrasting Ionic Conductivities in Li 2 ZrCl 6 via I and Br Substitution

Understanding the complex structural and chemical factors that influence ionic conduction mechanisms is paramount for developing advanced inorganic superionic conductors in all‐solid‐state batteries, particularly halide solid electrolytes with excellent electrochemical oxidative stability and mechanical sinterability. Herein, contrasting ionic conduction behaviors in I − and Br − substituted Li 2 ZrCl 6 are revealed by combining experimental structural analyses and theoretical calculations. The inter‐slab distance along the c ‐axis, which varies with the anion substitution and M2‐M3 site disorder, is a key factor for opening the ab ‐plane conduction and facilitating the overall Li + conduction. Increased M3 site occupancy generally leads to contracted inter‐slab distance. The substantial increase in Li + conductivity upon I substitution (from 0.40 to 0.91 mS cm −1 ) originates from a sufficiently expanded lattice volume owing to its large ionic radii (I − = 2.20 Å), particularly inter‐slab distance that facilitates the ab intra‐plane Li + conduction, which also benefits from decreased M2‐M3 disorder. In contrast, Br (Br − = 1.96 Å) substitution results in insufficiently expanded Li + channels, which, exacerbated by increased M2‐M3 disorder, leads to degradation in Li + conductivity. Implementing I − substituted Li 2 ZrCl 6 resulted in superior electrochemical performance in LiCoO 2 ||Li‐In cells compared to those with an unsubstituted catholyte.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Development of a wind turbine model and simulation platform using an acausal approach: Multiphysics modeling, validation, and control

This article presents the development of the Control-oriented, Reconfigurable, and Acausal Floating Turbine Simulator (CRAFTS). CRAFTS has a modular, hierarchical model architecture that enables rapid and accurate simulation of wind turbines. The architecture facilitates the incorporation of model variants, and its system reconfiguration features help simulate multiple design variants. CRAFTS also supports the integration of models developed on a causality-free platform (e.g., Modelica®) with existing causal models. This article focuses on the validation of a land-based wind turbine models against OpenFAST, an industry-standard platform, for several test cases. Closed-loop scenarios are also tested using the standard ROSCO controller and compared against OpenFAST. In addition, a nonlinear controller developed in our prior work is also evaluated. The test cases demonstrate the user-friendly and computationally efficient capabilities of CRAFTS to facilitate control co-design, assist in incorporating multiphysics models, be adaptable to design variants, and allow for rapid simulations to validate models and evaluate controllers.

17 WIND ENERGY↗
DOE OSTI2020

Chapter 10: Crystallography of Metabolic Enzymes

The metabolic enzymes like any enzymes generally display globular architecture where secondary structure elements and interactions between them preserve the spatial organization of the protein. A typical enzyme features a well-defined active site, designed for selective binding of the reaction substrate and facilitating a chemical reaction converting the substrate into a product. While many chemical reactions could be facilitated using only the functional groups that are found in proteins, the large percentage or intracellular reactions require use of cofactors, varying from single metal ions to relatively large molecules like numerous coenzymes, nucleotides and their derivatives, dinucleotides or hemes. Quite often these large cofactors become important not only for the catalytic function of the enzyme but also for the structural stability of it, as those are buried deep in the enzyme.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2023

Gluon transverse-momentum-dependent distributions from large-momentum effective theory

We demonstrate that gluon transverse-momentum-dependent parton distribution functions (TMDPDFs) can be extracted from lattice calculations of appropriate Euclidean correlations in large-momentum effective theory (LaMET). Based on perturbative calculations of gluon unpolarized and helicity TMDPDFs, we present a matching formula connecting them and their LaMET counterparts, where the latter are renormalized in a scheme facilitating lattice calculations and converted to the $\overline{MS}$ scheme. The hard matching kernel is given up to one-loop level. We also show that the perturbative result is independent of the prescription used for the pinch-pole singularity in the relevant correlations. Our results offer a guidance for the extraction of gluon TMDPDFs from lattice simulations, and have the potential to greatly facilitate perturbative calculations of the hard matching kernel.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Host-specific and tissue-dependent orchestration of microbiome community structure in traditional rice paddy ecosystems

Abstract Background and aim Rice and duckweed are two monocotyledonous plants that naturally coexist in paddy fields. While the presence of duckweed in paddy fields significantly improves rice productivity, the interplay between soil microbes and the two plant hosts in this agroecosystem remains unexplored. Methods We compared the bacterial community structure between duckweed, rice and soil from multiple rice paddies. We also isolated bacteria from these communities and characterized their modes of bacterial colonization and plant growth-promotion using model plants. Results Our data indicate that host-specific and tissue-dependent factors reproducibly orchestrate the bacterial community structure associated with their plant hosts. This is corroborated by results from culture-dependent approaches in which the dominant genus Pantoea isolated from rice aerial tissues can strongly attach and colonize gnotobiotic duckweed in spite of the low representation of this bacterial genus in the natural duckweed microbiome. Our study identified a core of 254 bacterial taxa that are consistently found in all rice and duckweed tissue samples from rice paddy fields. Furthermore, characterizing auxin-producing bacteria isolates from both plant species identified potential plant growth-promoting bacteria that may improve growth for both duckweed and rice in paddy fields. Conclusions Results from this work provide evidence for the importance of the host tissue and species context in determining plant colonization by microbes in the paddy field system. The resources generated in this study could facilitate the agronomic deployment of microbes for more sustainable rice production.

Agriculture↗
DOE OSTI2025

New capabilities for rapid depletion analysis of pebble-bed reactors in SCALE

The SCALE Leap-In for Cores at Equilibrium (SLICE) method leverages capabilities available in the SCALE modeling and simulation suite to facilitate rapid estimation of equilibrium core inventories for flowing-pebble reactor systems in support of a variety of fuel cycle applications. New capabilities that compliment the SLICE method have been developed for the ORIGAMI interface to ORIGEN in SCALE to facilitate rapid depletion calculations for flowing-pebble systems. New features include a more generalized and flexible means of specifying interpolation dimensions, the ability to evaluate pebbles moving through user-defined “axial zones” in each of the pebble’s multiple passes through the core, and the treatment of differential velocities across radial channels (representing both pebble-to-pebble and wall-to-pebble friction effects). ORIGAMI thus provides an efficient user interface to define a pebble’s path and irradiation histories of its multiple passes through the core to calculate the pebble’s time-dependent inventories, which can be useful in various applications domains such as safeguards, criticality safety, and disposal analyses. The consistency of new ORIGAMI approach was verified against the solution obtained using the SLICE method with ORIGEN-ARP, showing excellent agreement.

Skutnik, Steven E. [Oak Ridge National Laboratory ↗
DOE OSTI2025

Machine learning informed rational design of high entropy double perovskite oxide universal air/steam electrodes for solid oxide electrochemical cells

Due to their high efficiency and versatility, solid oxide electrochemical cells (SOCs) are poised to play a significant role in future energy conversion and storage applications. In recent years, SOCs have bifurcated into two distinct categories: traditional oxygen-ion conducting SOCs that typically operate from ∼650—850 °C and the more recent proton-conducting ceramic (PCC) SOCs that typically operate from ∼400—650 °C. Current performance and lifetime of both oxygen-ion conducting SOCs and PCCs is primarily limited by the air/steam electrode, which facilitates the oxygen reduction reaction (ORR) during fuel cell operation and must also facilitate the oxygen evolution reaction (OER) during electrolysis operation. Here, we present a newly designed high-entropy double perovskite oxide suitable as a universal ORR/OER electrode for both oxygen-ion conducting SOCs and PCCs. Machine learning methods are applied to identify chemical descriptors for highly catalytic high-entropy double perovskite oxides (AA’B 2 O 6 ) across a large compositional space. Based on the machine-learning guidance, we ultimately converge on Ba 0.9 Cs 0.1 (Ca 0.2 Gd 0.2 La 0.2 Pr 0.2 Sr 0.2 )Co 1.5 Fe 0.5 O 6 (CsBaHEO) as a universal air/steam electrode. Structure stabilization is accomplished by an equimolar five-cation high-entropy composition on the A’-site, while cesium substitution on the A-site enhances the electrical conductivity and leads to a higher oxygen vacancy concentration. This material exhibits versatility and high performance in reversible oxygen-ion SOCs, reversible PCCs, and also large-scale tubular PCCs. For example, the CsBaHEO-based PCC reaches 1018 mW∙cm −2 at 600°C, while a large-scale tubular PCC using CsBaHEO for electrolysis achieves a hydrogen production rate of 21.314 ML∙min −1 at 600 °C.

Cell↗
DOE OSTI2025

Elucidating the factors controlling the methanol synthesis from CO 2 on ZnPd-ZnO/TiO 2 catalysts prepared by direct/inverse impregnation

The direct hydrogenation of CO 2 to methanol over supported ZnPd intermetallic catalysts remains a challenge due to the complex nature of the active sites, which are highly dependent on both the dispersion of ZnPd intermetallics and their proximity to ZnO. This study investigates the effect of the Pd and Zn incorporation order on methanol synthesis over TiO 2 -supported ZnPd catalysts. Catalysts were prepared via direct (Pd/Zn), inverse (Zn/Pd), and co-impregnation (Pd+Zn) methods using anatase TiO 2 as the support. Comprehensive characterization by XRD, HRTEM, CO-DRIFTS and XPS revealed that the formation of small and crystalline intermetallic β-ZnPd particles and their interaction with ZnO/ZnO x depends on the sequence of Pd and Zn incorporation. It was found that, under the reaction conditions, the ZnO x species plays a critical role in facilitating the formation of the intermetallic ZnPd through the interactions between Pd and ZnO x . In addition, ZnO x species have also been shown to modulate key catalytic properties, such as CO 2 activation and methanol selectivity. Specifically, the ZnPd/Pd surface ratio, determined by Pd dispersion and proximity to ZnO/ZnO x , was shown to determine the methanol production from CO 2 directly or via a CO intermediate. The Pd/Zn catalyst showed superior selectivity due to the in-situ formation of intermetallic species facilitated by Pd-ZnO x interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗