Despite all the evident benefits of miniaturized particulate matter (PM) sensors, an inherent drawback exists in the uncertainty and validity of the measurement, which is closely related to the discrete nature of particulates suspended in air. The miniaturization of these devices not only leads to a smaller footprint for the devices themselves but also to a smaller volume of air being sampled. Even if a perfect measurement system is assumed, an uncertainty lies in assigning a supposedly representative particle concentration value to an environment due to the inherent variability of PM concentrations on small scales. This stems from the fact that particles are stochastically distributed in the air, leading to a non-uniform concentration for arbitrarily small volumes. Consequently, an uncertainty exists according to counting statistics, as the number of investigated particles in a small air sample is also low. Depending on the metric, the uncertainty may be augmented, as a small number of particles cannot accurately capture the distribution of particle sizes, especially since the size distribution extends over several orders of magnitude. This distribution related uncertainty is relevant for surface and mass related metrics in addition to the uncertainty resulting from counting statistics. We detected a minor impact from the distribution of the particle mass density, which contributes to the uncertainty for mass-related metrics, such as PM1, PM2.5 and PM10.We investigated the expected measurement uncertainty by analytical means and concluded that the distribution of particle sizes, the sample size and the ambient particle concentration significantly affect the measurement uncertainty for the range of conditions considered. To the best of our knowledge, this uncertainty has not been discussed in the current literature.
The Improved Inter Integrated Circuit (I3C) interface is a scalable, medium-speed, utility and control bus interface designed for connecting peripherals to an application processor. It is a backward-compatible successor to the I2C interface with increased speed, additional functionalities and improved energy efficiency. The work presented in this paper supports the early adoption of the I3C interface at the industry level by establishing a validation methodology of the timing parameters of the I3C interface and by setting up appropriate digital design workflows used in implementing I3C interface in Systems-on-Chip (SoC). The timing validation methodology is based on a Hardware-inLoop (HIL) topology, while the design workflows are represented by two I3C-based SoC examples: the autonomous I3C target and the temperature sensor integrated in ARM Cortex-M0 periphery with I3C Target interface.
In this work, we present a significant step toward in vivo ophthalmic optical coherence tomography and angiography on a photonic integrated chip. The diffraction gratings used in spectral-domain optical coherence tomography can be replaced by photonic integrated circuits comprising an arrayed waveguide grating. Two arrayed waveguide grating designs with 256 channels were tested, which enabled the first chip-based optical coherence tomography and angiography in vivo three-dimensional human retinal measurements. Design 1 supports a bandwidth of 22 nm, with which a sensitivity of up to 91 dB (830 µW ) and an axial resolution of 10.7 µm was measured. Design 2 supports a bandwidth of 48 nm, with which a sensitivity of 90 dB (480 µW ) and an axial resolution of 6.5 µm was measured. The silicon nitride-based integrated optical waveguides were fabricated with a fully CMOS-compatible process, which allows their monolithic co-integration on top of an optoelectronic silicon chip. As a benchmark for chip-based optical coherence tomography, tomograms generated by a commercially available clinical spectral-domain optical coherence tomography system were compared to those acquired with on-chip gratings. The similarities in the tomograms demonstrate the significant clinical potential for further integration of optical coherence tomography on a chip system.
Defects in the gate oxide give rise to bias temperature instability (BTI), which is considered a serious threat to the device reliability of ultrascaled MOSFETs. Extrapolating the device degradation over the operational lifetime, therefore, requires detailed knowledge about the distributions of defects causing BTI. Typically, BTI degradation is modeled by calibrating a predefined defect parameter distribution, such as normally distributed defect bands, by employing measure-stress-measure (MSM) sequences at various temperatures. Here, we present the Effective Single Defect Decomposition (ESiD), a novel method for a semiautomated extraction of defect parameters from MSM experiments which does not require any prior assumptions about their distributions. This technique decomposes the MSM sequences into contributions from dominant effective single-defects and constructs a defect parameter distribution that reproduces the experimental data with high accuracy. We validate this new method by comparing its results to density functional theory (DFT) predictions and single-defect characterizations.
Single-mode organic solid-state lasers with direct emission into an optical waveguide are attractive candidates for cost-efficient coherent light sources employed in photonic lab-on-a-chip biosensors. Here, we present a combination of a dye-doped organic solid-state distributed feedback laser with a highly sensitive optical waveguide Mach-Zehnder interferometer on a silicon nitride photonic platform. This organic-hybrid laser allows for optical pumping with a laser diode in an alignment tolerant manner, which facilitates applications in point-of-care diagnostics. The sensitivity to bulk refractive index changes and the concentration dependent binding of streptavidin on a polyethyleneimine-biotin functionalized surface was studied to demonstrate the practicability of this cost-efficient coherent light source for optical waveguide biosensors.
