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Results for “CADMIUM SULFIDES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Tailoring electron transfer pathway for photocatalytic N 2 -to-NH 3 reduction in a CdS quantum dots-nitrogenase system

The combination of abiotic photosensitizers with purified enzymes in a biohybrid system offers a promising pathway to utilizing light to accomplish challenging chemical transformations and provides insights into the rational photocatalytic system design for efficient solar-to-chemical energy conversion. In this work, we demonstrate a hybrid photocatalytic system for ammonia production from N2 by combining cadmium sulfide quantum dots (CdS QDs) and Mo-nitrogenase from Azotobacter vinelandii, composed of the iron protein (FeP) and the molybdenum-iron protein (MoFeP). Photoexcited electrons from the CdS QD are delivered by an electron transfer mediator through the FeP to the catalytic MoFeP. The complete system was optimized for the ligand on the CdS QDs, mediators, and reaction conditions. The best results were achieved with β-mercaptoethanol as a QD ligand. The mediator test revealed that 1,1'-bis(3-sulfonatopropyl)-4,4'-bipyridinium (SPr)2V (-0.4 V vs. NHE) supports the reduction of protons and N 2 to H 2 and ammonia catalyzed by nitrogenase. However, in the presence of 1,1'-trimethylene-2,2'-bipyridinium TQ (-0.54 V vs. NHE) as a mediator, nitrogenase catalysis resulted in remarkably more products. The UV-vis and in situ potentiometric studies revealed that better performance with TQ is achieved due to the significantly more negative solution potential allowing for efficient reduction of FeP. As a result, the quantum yield for conversion of absorbed photons to ammonia attains 16%, far exceeding that of previously reported nitrogenase-based systems. This work reveals the importance of tuning the electron transfer pathways in photocatalytic systems and illustrates a potent strategy for efficient electronic coupling of a photosensitizer and an N 2 reduction catalyst.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Scale and rate in CdS pressure-induced phase transition

Here, we describe recent efforts to improve our predictive modeling of rate-dependent behavior at, or near, a phase transition using molecular dynamics simulations. Cadmium sulfide (CdS) is a well-studied material that undergoes a solid-solid phase transition from wurtzite to rock salt structures between 3 and 9 GPa. Atomistic simulations are used to investigate the dominant transition mechanisms as a function of orientation, size and rate. We found that the final rock salt orientations were determined relative to the initial wurtzite orientation, and that these orientations were different for the two orientations and two pressure regimes studied. The CdS solid-solid phase transition is studied, for both a bulk single crystal and for polymer-encapsulated spherical nanoparticles of various sizes.

42 ENGINEERING↗
DOE OSTI2023

Light-Induced Decoupling of Electronic and Magnetic Properties in Manganites

The strongly correlated material La 0.7 ⁢Sr 0.3 ⁢Mn⁢O 3 (LSMO) exhibits metal-to-insulator and magnetic transition near room temperature. Although the physical properties of LSMO can be manipulated by strain, chemical doping, temperature, or magnetic field, they often require large external stimuli. Further, to include additional flexibility and tunability, we developed a hybrid optoelectronic heterostructure that uses photocarrier injection from cadmium sulfide (Cd⁢ S) to an LSMO layer to change its electrical conductivity. LSMO exhibits no significant optical response; however, the Cd ⁢S/LSMO heterostructures show an enhanced conductivity, with a resistance drop of about 37%, at the transition temperature under light stimuli. This enhanced conductivity in response to light is comparable to the effect of a 9 T magnetic field in pure LSMO. Surprisingly, the optical and magnetic responses of Cd⁢ S/LSMO heterostructures are decoupled and exhibit different effects when both stimuli are applied. This unexpected behavior shows that heterostructuring strongly correlated oxides may require a new understanding of the coupling of physical properties across the transitions and provide the means to implement new functionalities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Coupling strongly correlated electron systems to a tunable electronic reservoir

Here, we study the effect of coupling an electronic reservoir to a Hubbard model and to a dimer Hubbard model. This is motivated by recent experiments on the effect of illumination on the insulator-metal transition in a vanadium oxides and photoconductive cadmium sulfide heterostructure. We model the system as an electronic reservoir hybridized to the correlated system. We assume that the light intensity controls the hybridization coupling strength. We find that the light intensity acts similarly as the temperature in the weak interaction regime. This is consistent with the role played by electronic reservoirs in out-of-equilibrium systems. In contrast, qualitative differences appear at strong coupling. We show that modeling the V 2 ⁢O 3 compound with a Hubbard model, our results describe qualitatively well the observed illumination-driven suppression of the insulator-metal transition. In contrast, in the DHM results fail to capture the mild suppression observed in the case of VO 2 . This indicates that the lattice may play an important role in this case.

Materials Science↗
DOE OSTI2021

Classification of Semiconductors Using Photoluminescence Spectroscopy and Machine Learning

Photoluminescence spectroscopy is a nondestructive optical method that is widely used to characterize semiconductors. In the photoluminescence process, a substance absorbs photons and emits light with longer wavelengths via electronic transitions. This paper discusses a method for identifying substances from their photoluminescence spectra using machine learning, a technique that is efficient in making classifications. Neural networks were constructed by taking simulated photoluminescence spectra as the input and the identity of the substance as the output. Here, six different semiconductors were chosen as categories: gallium oxide (Ga 2 O 3 ), zinc oxide (ZnO), gallium nitride (GaN), cadmium sulfide (CdS), tungsten disulfide (WS 2 ), and cesium lead bromide (CsPbBr 3 ). The developed algorithm has a high accuracy (>90%) for assigning a substance to one of these six categories from its photoluminescence spectrum and correctly identified a mixed Ga 2 O 3 /ZnO sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

LDRD 226360 Final Project Report: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis

This report is the final documentation for the one-year LDRD project 226360: Simulated X-ray Diffraction and Machine Learning for Optimizing Dynamic Experiment Analysis. As Sandia has successfully developed in-house X-ray diffraction tools for study of atomic structure in experiments, it has become increasingly important to develop computational analysis methods to support these experiments. When dynamically compressed lattices and orientations are not known a priori, the identification requires a cumbersome and sometimes intractable search of possible final states. These final states can include phase transition, deformation and mixed/evolving states. Our work consists of three parts: (1) development of an XRD simulation tool and use of traditional data science methods to match XRD patterns to experiments; (2) development of ML-based models capable of decomposing and identifying the lattice and orientation components of multicomponent experimental diffraction patterns; and (3) conducting experiments which showcase these new analysis tools in the study of phase transition mechanisms. Our target material has been cadmium sulfide, which exhibits complex orientation-dependent phase transformation mechanisms. In our current one-year LDRD, we have begun the analysis of high-quality c-axis CdS diffraction data from DCS and Thor experiments, which had until recently eluded orientation identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1963

The Explorer XVI Micrometeoroid Satellite: Description and Preliminary Results for the Period December 16, 1962 Through January 13, 1963

Explorer XVI (1962 Beta Chi l) data that have been analyzed for the period between December 16, 1962 (launch date), and January 13, 1963, indicate that the orbit achieved was close to the predicted orbit. Ten punctures of annealed 0.001-inch-thick beryllium-copper have been used to determine a puncture rate of 0.035 per square foot per day in this material. One puncture of a 0.002-inch-thick sample has also occurred in this period. A tentative evaluation of the puncture rate for the 0.001-inch beryllium-copper in terms of the rate for an equivalent thickness of aluminum has been attempted, and the result has been compared with two different puncture rate estimates. The three micrometeoroid impact detecting systems are operating. Counting rates for the high- and low-sensitivity systems were close to anticipated values near the end of one week. Two of the 0.001-inch-steel-covered grid detectors have been punctured, but none of the 0.003- or 0.006-inch-steel-covered grid detectors have indicated punctures. One of the cadmium sulfide cells indicates three punctures of the 0.00025-inch Mylar cover. None of the 0.002- or 0.003-inch-copper-wire cards have indicated a break in the period covered. Telemetry temperatures were initially higher than expected although they remained well within operating limits. Sensor temperatures have remained within the expected bounds.

Micrometeoroid↗
NASA NTRS1967

Guidance and control research

Guidance and control research on solid state triodes, evaporated thin film cadmium sulfide photodectors, and reduction of plasma maintenance voltage with magnetic field

MAGNETIC FIELD↗