Do you want to publish a course? Click here

Strain relaxation during the layer by layer growth of cubic CdSe onto ZnSe

61   0   0.0 ( 0 )
 Added by Osvaldo de Melo
 Publication date 2019
  fields Physics
and research's language is English




Ask ChatGPT about the research

A detailed reflection high-energy electron diffraction analysis shows relevant features of the lattice parameter relaxation of CdSe thin films grown in a layer-by-layer mode onto ZnSe. In situ investigations of different azimuths show a clear lattice parameter oscillation in the 110 azimuth. The lattice parameter has a minimum value ~similar to that of ZnSe! during Se exposure steps, and a higher and increasing lattice parameter during Cd exposure steps. The behavior is ascribed to the formation of CdSe islands during Cd exposure steps. The cumulative effect in CdSe exposure steps is considered to be a consequence of a decrease in the island size with the number of cycles. Actual plastic deformation does occur after 5 ML.



rate research

Read More

Understanding surface dynamics during epitaxial film growth is key to growing high quality materials with controllable properties. X-ray photon correlation spectroscopy (XPCS) using coherent x-rays opens new opportunities for in situ observation of atomic-scale fluctuation dynamics during crystal growth. Here, we present the first XPCS measurements of 2D island dynamics during homoepitaxial growth in the layer-by-layer mode. Analysis of the results using two-time correlations reveals a new phenomenon - a memory effect in island nucleation sites on successive crystal layers. Simulations indicate that this persistence in the island arrangements arises from communication between islands on different layers via adatoms. With the worldwide advent of new coherent x-ray sources, the XPCS methods pioneered here will be widely applicable to atomic-scale processes on surfaces.
Strain engineering has arisen as a powerful technique to tune the electronic and optical properties of two-dimensional semiconductors like molybdenum disulfide (MoS2). Although several theoretical works predicted that biaxial strain would be more effective than uniaxial strain to tune the band structure of MoS2, a direct experimental verification is still missing in the literature. Here we implemented a simple experimental setup that allows to apply biaxial strain through the bending of a cruciform polymer substrate. We used the setup to study the effect of biaxial strain on the differential reflectance spectra of 12 single-layer MoS2 flakes finding a redshift of the excitonic features at a rate between -40 meV/% and -110 meV/% of biaxial tension. We also directly compare the effect of biaxial and uniaxial strain on the same single-layer MoS2 finding that the biaxial strain gauge factor is 2.3 times larger than the uniaxial strain one.
We have succeeded in growing epitaxial and highly stoichiometric films of EuO on yttria-stabilized cubic zirconia (YSZ) (001). The use of the Eu-distillation process during the molecular beam epitaxy assisted growth enables the consistent achievement of stoichiometry. We have also succeeded in growing the films in a layer-by-layer fashion by fine tuning the Eu vs. oxygen deposition rates. The initial stages of growth involve the limited supply of oxygen from the YSZ substrate, but the EuO stoichiometry can still be well maintained. The films grown were sufficiently smooth so that the capping with a thin layer of aluminum was leak tight and enabled ex situ experiments free from trivalent Eu species. The findings were used to obtain recipes for better epitaxial growth of EuO on MgO (001).
Germanium is emerging as the substrate of choice for the growth of graphene in CMOS-compatible processes. For future application in next generation devices the accurate control over the properties of high-quality graphene synthesized on Ge surfaces, such as number of layers and domain size, is of paramount importance. Here we investigate the role of the process gas flows on the CVD growth of graphene on Ge(100). The quality and morphology of the deposited material is assessed by using microRaman spectroscopy, x-ray photoemission spectroscopy, scanning electron and atomic force microscopies. We find that by simply varying the carbon precursor flow different growth regimes - yielding to graphene nanoribbons, graphene monolayer and graphene multilayer - are established. We identify the growth conditions yielding to a layer-by-layer growth regime and report on the achievement of homogeneous monolayer graphene with an average intensity ratio of 2D and G bands in the Raman map larger than 3.
Process optimization of photovoltaic devices is a time-intensive, trial and error endeavor, without full transparency of the underlying physics, and with user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach that identifies the root cause(s) of underperformance with layer by-layer resolution and reveals alternative optimal process windows beyond global black-box optimization. Our Bayesian-network approach links process conditions to materials descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency), using a Bayesian inference framework with an autoencoder-based surrogate device-physics model that is 100x faster than numerical solvers. With the trained surrogate model, our approach is robust and reduces significantly the time consuming experimentalist intervention, even with small numbers of fabricated samples. To demonstrate our method, we perform layer-by-layer optimization of GaAs solar cells. In a single cycle of learning, we find an improved growth temperature for the GaAs solar cells without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above baseline and traditional black-box optimization methods.
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا