Whole genome sequencing on next-generation instruments provides an unbiased way to identify the organisms present in complex metagenomic samples. However, the time-to-result can be protracted because of fixed-time sequencing runs and cumbersome bioinformatics workflows. This limits the utility of the approach in settings where rapid species identification is crucial, such as in the quality control of food-chain components, or in during an outbreak of an infectious disease. Here we present What′s in my Pot? (WIMP), a laboratory and analysis workflow in which, starting with an unprocessed sample, sequence data is generated and bacteria, viruses and fungi present in the sample are classified to subspecies and strain level in a quantitative manner, without prior knowledge of the sample composition, in approximately 3.5 hours. This workflow relies on the combination of Oxford Nanopore Technologies′ MinION ™ sensing device with a real-time species identification bioinformatics application.

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The frequency response of a pressure transducer is influenced by the natural resonance of the sensor structure, the spatial resolution of the sensor due to its diaphragm size, the sensor packaging, signal conditioning and mounting at the measurement location. The resonance of the sensor and aerodynamically-driven resonances related to the sensor packaging and/or mounting, specifically, can distort dynamic pressure measurements within the range of greatest interest (10Hz–20kHz), typically resulting in erroneous amplification. Historically, correcting for such errors within the frequency response of a pressure transducer or measurement system has been challenging, because such errors are hard to quantify with unknown resonant frequencies and damping factors (quality factors). However, with the ability to fully characterize resonant frequencies that lie within 10Hz–50kHz using a previously demonstrated dynamic pressure characterization methodology, it is possible to apply electrical filtering to substantially extend the flat (0±2dB) frequency response of a transducer before any digital signal conversion. In this work, we present a real-time frequency response compensation scheme that uses electrical filtering to correct for aerodynamically driven packaging or mounting related resonances while at the same time preventing signal distortion caused by the sensor resonances. The compensation extends the useable, flat amplitude bandwidth of the transducer while also correcting the phase response to maintain constant time delay over the extended bandwidth. This real-time frequency response correction scheme can be similarly used to compensate for chip resonances, which can limit the frequency response in applications such as shock and blast testing. A theoretical model of the frequency response correction methodology is presented. We additionally present temperature dependent experimental results that compare the frequency response with and without the correction scheme. These results demonstrate that the usable bandwidth of pressure transducers can be increased when real time, analog frequency response correction is applied. This work shows that if the frequency response of a transducer is well characterized, advanced signal conditioning can be implemented to substantially extend the flat bandwidth of the transducer without changes to the sensor, packaging or mounting.

Accurate static and dynamic pressure measurements in liquids, such as fuel, oil, and hydraulic fluid, are critical to the control and health monitoring of turbomachinery and aerospace systems. This work presents a theoretical and experimental study of the frequency response of pressure transducers and pressure measurement systems in liquid media. First, we theoretically predict the frequency response of pressure transducers based upon a lumped-parameter model. We then present a liquid-based dynamic pressure calibration test apparatus that validates this model by performing several critical measurements. This system first uses a vibrating liquid column to dynamically calibrate and experimentally determine the frequency response of a test pressure transducer, measurement system or geometry. Second, this calibration system experimentally extracts the bulk modulus of the fluid and the percent of entrained and/or dissolved air by volume. Bulk modulus is determined by measuring the speed of sound within the liquid and through static pressure loading while measuring the deflection of the liquid column. Bulk modulus and the entrained/dissolved gas content within the liquid greatly impact the observed frequency response of a pressure transducer or geometry. Gases, such as air, mixed or dissolved into a fluid can add substantial damping to the dynamic response of the fluid measurement system, which makes measurement of the bulk modulus and entrained and/or dissolved air critical for accurate measurement of the frequency response of a system when operating with a liquid media. All experimental results are compared to theoretical predictions.

Silicon micro-machined piezoresistive based pressure transducers are often used to make high frequency dynamic pressure measurements. The spectral or frequency response of these microelectromechanical systems (MEMS) is a function of the natural resonance of the sensor structure, sensor size, sensor packaging, signal conditioning and transducer mounting in the desired measurement location. The advancement of MEMS micro-fabrication, which has reduced sensor size dramatically, and the high elastic modulus of silicon have allowed the natural resonance of these devices to range from 100kHz to several MHz [1]. As a result, packaging and mounting at the point of measurement are the major factors that determine the flat (0dB) frequency response envelope of the transducer, which is typically quantified by a transfer function. The transfer function quantifies the difference both in magnitude and phase between an input signal and a measured signal in the frequency domain. The dynamic response of pressure transducers has historically been estimated via a unit step input in pressure created through a shock tube test that excites the high natural resonance of the chip. Unfortunately, these tests are less effective at accurately quantifying the frequency response of the transducer in the domain of greatest interest (DC-20kHz), specifically the bandwidth over which the response is flat (0dB). In this work, we present a test methodology using a speaker-driven dynamic pressure calibration setup for experimentally determining the transfer function of a pressure transducer from 1–50kHz. The test setup is validated using capacitive-based microphones with claimed flat spectral characteristics well beyond 50kHz. Using this test setup, we present experimental spectral response results for low-pressure miniature MEMS piezoresistive pressure transducers over the frequency range of 1–50kHz and qualitatively compare these results to traditional shock tube tests. The transducers characterized have been manufactured with several different standard sizes and front-end configurations.

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There is a need to measure static and dynamic conditions in many gas turbine applications, in particular for combustion instabilities, such as those in the afterburner. The DC and low frequency components are typically used for conventional engine control, while the high frequency data is essential for acoustic screech and rumble diagnostics and control. This paper presents a static-dynamic piezoresistive pressure transducer that measures low amplitude, dynamic pressure perturbations superimposed on top of a high pressure through the implementation of low pass mechanical structures. The transducer, which is capable of operating at ultra-high temperatures and in harsh environments, consists of a static piezoresistive pressure transducer, which measures the large pressures on the order of 200psi and greater, and an ultrasensitive, dynamic piezoresistive pressure transducer which captures small, high frequency pressure oscillations on the order of a few psi. The heightened sensitivity in high pressure environments is achieved by filtering the measured pressure of high frequency content through an innovative low pass mechanical filter structure. The large static pressures passed by the low-pass mechanical filter structures are routed to the backside of the dynamic pressure sensor, which results in both the front and the back of the dynamic sensor being exposed to the large pressures within the environment. Therefore, the large static pressures cancel out, and the dynamic sensor only senses the low magnitude, high frequency pressure perturbations. This dual sensor, static-dynamic pressure transducer reproduces pressure signals with sensitivity far higher than any single high pressure transducer available today. The dual sensor, static-dynamic transducer meets the pressure sensing specification of numerous applications including, but not limited to, the following: the optimization of turbine operation, turbine design and testing, the detection of the onset of rotating stall and surge in turbine compressors, and combustion instabilities. This paper describes a six element model of the static-dynamic transducer’s low-pass mechanical filtering structures. The paradigm is derived from first-principles of fluid motion in acoustic ducts with viscous dissipation. A dynamic pressure source is used to verify the model and its operation. Finally, a transfer function characterization of a fully operational static-dynamic pressure transducer over a wide bandwidth is presented. Based upon the analytical and experimental results, the static-dynamic pressure transducer will make it possible for turbine users and manufacturers to implement ultra-sensitive pressure monitoring to reduce compressor and combustion instabilities [1] [2].