7 research outputs found
Significant Phonon Drag Enables High Power Factor in the AlGaN/GaN Two-Dimensional Electron Gas
In typical thermoelectric energy harvesters and sensors, the Seebeck effect
is caused by diffusion of electrons or holes in a temperature gradient.
However, the Seebeck effect can also have a phonon drag component, due to
momentum exchange between charge carriers and lattice phonons, which is more
difficult to quantify. Here, we present the first study of phonon drag in the
AlGaN/GaN two-dimensional electron gas (2DEG). We find that phonon drag does
not contribute significantly to the thermoelectric behavior of devices with
~100 nm GaN thickness, which suppress the phonon mean free path. However, when
the thickness is increased to ~1.2 m, up to 32% (88%) of the Seebeck
coefficient at 300 K (50 K) can be attributed to the drag component. In turn,
the phonon drag enables state-of-the-art thermoelectric power factor in the
thicker GaN film, up to ~40 mW m K at 50 K. By measuring the
thermal conductivity of these AlGaN/GaN films, we show that the magnitude of
the phonon drag can increase even when the thermal conductivity decreases.
Decoupling of thermal conductivity and Seebeck coefficient could enable
important advancements in thermoelectric power conversion with devices based on
2DEGs
Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching
Crystalline materials used in technological applications are often complex
assemblies composed of multiple phases and differently oriented grains. Robust
identification of the phases and orientation relationships from these samples
is crucial, but the information extracted from the diffraction condition probed
by an electron beam is often incomplete. We therefore have developed an
automated crystal orientation mapping (ACOM) procedure which uses a converged
electron probe to collect diffraction patterns from multiple locations across a
complex sample. We provide an algorithm to determine the orientation of each
diffraction pattern based on a fast sparse correlation method. We test the
speed and accuracy of our method by indexing diffraction patterns generated
using both kinematical and dynamical simulations. We have also measured
orientation maps from an experimental dataset consisting of a complex
polycrystalline twisted helical AuAgPd nanowire. From these maps we identify
twin planes between adjacent grains, which may be responsible for the twisted
helical structure. All of our methods are made freely available as open source
code, including tutorials which can be easily adapted to perform ACOM
measurements on diffraction pattern datasets.Comment: 14 pages, 7 figure
Robust design of semi-automated clustering models for 4D-STEM datasets
Materials discovery and design require characterizing material structures at the nanometer and sub-nanometer scale. Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM) resolves the crystal structure of materials, but many 4D-STEM data analysis pipelines are not suited for the identification of anomalous and unexpected structures. This work introduces improvements to the iterative Non-Negative Matrix Factorization (NMF) method by implementing consensus clustering for ensemble learning. We evaluate the performance of models during parameter tuning and find that consensus clustering improves performance in all cases and is able to recover specific grains missed by the best performing model in the ensemble. The methods introduced in this work can be applied broadly to materials characterization datasets to aid in the design of new materials
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Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching.
Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets
Recommended from our members
Decoupling electron and phonon transport in single-nanowire hybrid materials for high-performance thermoelectrics.
Organic-inorganic hybrids have recently emerged as a class of high-performing thermoelectric materials that are lightweight and mechanically flexible. However, the fundamental electrical and thermal transport in these materials has remained elusive due to the heterogeneity of bulk, polycrystalline, thin films reported thus far. Here, we systematically investigate a model hybrid comprising a single core/shell nanowire of Te-PEDOT:PSS. We show that as the nanowire diameter is reduced, the electrical conductivity increases and the thermal conductivity decreases, while the Seebeck coefficient remains nearly constant-this collectively results in a figure of merit, ZT, of 0.54 at 400 K. The origin of the decoupling of charge and heat transport lies in the fact that electrical transport occurs through the organic shell, while thermal transport is driven by the inorganic core. This study establishes design principles for high-performing thermoelectrics that leverage the unique interactions occurring at the interfaces of hybrid nanowires
Significant Phonon Drag Enables High Power Factor in the AlGaN/GaN Two-Dimensional Electron Gas
In typical thermoelectric energy harvesters and sensors, the Seebeck effect is caused by diffusion of electrons or holes in a temperature gradient. However, the Seebeck effect can also have a phonon drag component, due to momentum exchange between charge carriers and lattice phonons, which is more difficult to quantify. Here, we present the first study of phonon drag in the AlGaN/GaN two-dimensional electron gas (2DEG). We find that phonon drag does not contribute significantly to the thermoelectric behavior of devices with ∼100 nm GaN thickness, which suppresses the phonon mean free path. However, when the thickness is increased to ∼1.2 μm, up to 32% (88%) of the Seebeck coefficient at 300 K (50 K) can be attributed to the drag component. In turn, the phonon drag enables state-of-the-art thermoelectric power factor in the thicker GaN film, up to ∼40 mW m–1 K–2 at 50 K. By measuring the thermal conductivity of these AlGaN/GaN films, we show that the magnitude of the phonon drag can increase even when the thermal conductivity decreases. Decoupling of thermal conductivity and Seebeck coefficient could enable important advancements in thermoelectric power conversion with devices based on 2DEGs