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Register a new userAn open-source platform to study uniaxial stress effects on nanoscale devices
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We present an automatic measurement platform that enables the characterization of nanodevices by electrical transport and optical spectroscopy as a function of uniaxial stress. We provide insights into and detailed descriptions of the mechanical device, the substrate design and fabrication, and the instrument control software, which is provided under open-source license. The capability of the platform is demonstrated by characterizing the piezo-resistance of an InAs nanowire device using a combination of electrical transport and Raman spectroscopy. The advantages of this measurement platform are highlighted by comparison with state-of-the-art piezo-resistance measurements in InAs nanowires. We envision that the systematic application of this methodology will provide new insights into the physics of nanoscale devices and novel materials for electronics, and thus contribute to the assessment of the potential of strain as a technology booster for nanoscale electronics.
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Accessible machine learning algorithms, software, and diagnostic tools for energy-efficient devices and systems are extremely valuable across a broad range of application domains. In scientific domains, real-time near-sensor processing can drastically improve experimental design and accelerate scientific discoveries. To support domain scientists, we have developed hls4ml, an open-source software-hardware codesign workflow to interpret and translate machine learning algorithms for implementation with both FPGA and ASIC technologies. We expand on previous hls4ml work by extending capabilities and techniques towards low-power implementations and increased usability: new Python APIs, quantization-aware pruning, end-to-end FPGA workflows, long pipeline kernels for low power, and new device backends include an ASIC workflow. Taken together, these and continued efforts in hls4ml will arm a new generation of domain scientists with accessible, efficient, and powerful tools for machine-learning-accelerated discovery.
The recently predicted topological magnetoelectric effect and the response to an electric charge that mimics an induced mirror magnetic monopole are fundamental attributes of topological states of matter with broken time reversal symmetry. Using a SQUID-on-tip, acting simultaneously as a tunable scanning electric charge and as ultrasensitive nanoscale magnetometer, we induce and directly image the microscopic currents generating the magnetic monopole response in a graphene quantum Hall electron system. We find a rich and complex nonlinear behavior governed by coexistence of topological and nontopological equilibrium currents that is not captured by the monopole models. Furthermore, by utilizing a tuning fork that induces nanoscale vibrations of the SQUID-on-tip, we directly image the equilibrium currents of individual quantum Hall edge states for the first time. We reveal that the edge states that are commonly assumed to carry only a chiral downstream current, in fact carry a pair of counterpropagating currents, in which the topological downstream current in the incompressible region is always counterbalanced by heretofore unobserved nontopological upstream current flowing in the adjacent compressible region. The intricate patterns of the counterpropagating equilibrium-state orbital currents provide new insights into the microscopic origins of the topological and nontopological charge and energy flow in quantum Hall systems.
Pressure alters the physical, chemical and electronic properties of matter. The development of the diamond anvil cell (DAC) enables tabletop experiments to investigate a diverse landscape of high-pressure phenomena ranging from the properties of planetary interiors to transitions between quantum mechanical phases. In this work, we introduce and utilize a novel nanoscale sensing platform, which integrates nitrogen-vacancy (NV) color centers directly into the culet (tip) of diamond anvils. We demonstrate the versatility of this platform by performing diffraction-limited imaging (~600 nm) of both stress fields and magnetism, up to pressures ~30 GPa and for temperatures ranging from 25-340 K. For the former, we quantify all six (normal and shear) stress components with accuracy $<0.01$ GPa, offering unique new capabilities for characterizing the strength and effective viscosity of solids and fluids under pressure. For the latter, we demonstrate vector magnetic field imaging with dipole accuracy $<10^{-11}$ emu, enabling us to measure the pressure-driven $alphaleftrightarrowepsilon$ phase transition in iron as well as the complex pressure-temperature phase diagram of gadolinium. In addition to DC vector magnetometry, we highlight a complementary NV-sensing modality using T1 noise spectroscopy; crucially, this demonstrates our ability to characterize phase transitions even in the absence of static magnetic signatures. By integrating an atomic-scale sensor directly into DACs, our platform enables the in situ imaging of elastic, electric and magnetic phenomena at high pressures.
We aim to provide engineers with an introduction to the non-equilibrium Greens function (NEGF) approach, which provides a powerful conceptual tool and a practical analysis method to treat small electronic devices quantum mechanically and atomistically. We first review the basis for the traditional, semiclassical description of carriers that has served device engineers for more than 50 years. We then describe why this traditional approach loses validity at the nanoscale. Next, we describe semiclassical ballistic transport and the Landauer-Buttiker approach to phase coherent quantum transport. Realistic devices include interactions that break quantum mechanical phase and also cause energy relaxation. As a result, transport in nanodevices are between diffusive and phase coherent. We introduce the non equilbrium Greens function (NEGF) approach, which can be used to model devices all the way from ballistic to diffusive limits. This is followed by a summary of equations that are used to model a large class of layered structures such as nanotransistors, carbon nanotubes and nanowires. An application of the NEGF method in the ballistic and scattering limits to silicon nanotransistors is discussed.
Abstract The transport of nutrients or signal constituents that stimulate growth of bone tissue is supposed to be affected by a static mechanical load. It follows from basic thermodynamical principles that constituents causing volumetric change are dragged along the gradients of hydrostatic stress. The present preliminary study examines the behaviour of iodine present in the medullary cavity of a bovine long bone exposed to mechanical load. A section of the bone is x-ray scanned with the static load present, with and without the iodine. The resulting distribution in a selected 2D plane is numerically evaluated using a discrete Radons inverse transform. The result suggests that iodine is a useful constituent with a good attenuation effect on the x-ray beam and clearly reveals the temporal distribution of its transport through the bone. It further result shows some indication that stress does affect the iodine distribution.
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