Correction: Enabling direct microcalorimetric measurement of metabolic activity and exothermic reactions onto microfluidic platforms via heat flux sensor integration.

[This corrects the article DOI: 10.1038/s41378-023-00525-z.].

Experimental In Vitro Microfluidic Calorimetric Chip Data towards the Early Detection of Infection on Implant Surfaces.

Heat flux measurement shows potential for the early detection of infectious growth. Our research is motivated by the possibility of using heat flux sensors for the early detection of infection on aortic vascular grafts by measuring the onset of bacterial growth. Applying heat flux measurement as an infectious marker on implant surfaces is yet to be experimentally explored. We have previously shown the measurement of the exponential growth curve of a bacterial population in a thermally stabilized laboratory environment. In this work, we further explore the limits of the microcalorimetric measurements via heat flux sensors in a microfluidic chip in a thermally fluctuating environment.

An in vitro demonstration of a passive, acoustic metamaterial as a temperature sensor with mK resolution for implantable applications.

Wireless medical sensors typically utilize electromagnetic coupling or ultrasound for energy transfer and sensor interrogation. Energy transfer and management is a complex aspect that often limits the applicability of implantable sensor systems. In this work, we report a new passive temperature sensing scheme based on an acoustic metamaterial made of silicon embedded in a polydimethylsiloxane matrix. Compared to other approaches, this concept is implemented without additional electrical components in situ or the need for a customized receiving unit. A standard ultrasonic transducer is used for this demonstration to directly excite and collect the reflected signal. The metamaterial resonates at a frequency close to a typical medical value (5 MHz) and exhibits a high-quality factor. Combining the design features of the metamaterial with the high-temperature sensitivity of the polydimethylsiloxane matrix, we achieve a temperature resolution of 30 mK. This value is below the current standard resolution required in infrared thermometry for monitoring postoperative complications (0.1 K). We fabricated, simulated, in vitro tested, and compared three acoustic sensor designs in the 29-43 °C (~302-316 K) temperature range. With this concept, we demonstrate how our passive metamaterial sensor can open the way toward new zero-power smart medical implant concepts based on acoustic interrogation.

Finite element-based feasibility study on utilizing heat flux sensors for early detection of vascular graft infections.

Aortic vascular graft infections have high morbidity and mortality rate, however, patients often do not show symptoms. Continuous implant surface monitoring will allow for early detection of infections on implant surfaces, which allows for antibiotic treatment prior to biofilm formation. We explore the possibility of using heat flux sensors mounted on an aortic vascular graft to sense the localized heat production at the onset of infectious growth. We apply Finite Element Model simulations to demonstrate changes of the heat transfer coefficient depending on different pulsatile flow parameters. We determine various differences, the main influence being the distance travelled from the inlet of the simulation with the highest heat transfer coefficient closest to the inlet and decreasing along the direction of travel of the fluid. The determined range of heat transfer coefficients of 200 to 4800 W/m2 was applied to a second simulation of the thermal environment of the implant. We determined the heat transfer efficiency of the aortic graft system depending on different graft materials and thicknesses. We are further able to determine that the early detection of infection is possible by comparing the simulated amount of heat flux produced locally with the resolution of a commercial heat flux sensor.

Enabling direct microcalorimetric measurement of metabolic activity and exothermic reactions onto microfluidic platforms via heat flux sensor integration.

All biological processes use or produce heat. Traditional microcalorimeters have been utilized to study the metabolic heat output of living organisms and heat production of exothermic chemical processes. Current advances in microfabrication have made possible the miniaturization of commercial microcalorimeters, resulting in a few studies on the metabolic activity of cells at the microscale in microfluidic chips. Here we present a new, versatile, and robust microcalorimetric differential design based on the integration of heat flux sensors on top of microfluidic channels. We show the design, modeling, calibration, and experimental verification of this system by utilizing Escherichia coli growth and the exothermic base catalyzed hydrolysis of methyl paraben as use cases. The system consists of a Polydimethylsiloxane based flow-through microfluidic chip with two 46 µl chambers and two integrated heat flux sensors. The differential compensation of thermal power measurements allows for the measurement of bacterial growth with a limit of detection of 1707 W/m3, corresponding to 0.021OD (2 ∙ 107 bacteria). We also extracted the thermal power of a single Escherichia coli of between 1.3 and 4.5 pW, comparable to values measured by industrial microcalorimeters. Our system opens the possibility for expanding already existing microfluidic systems, such as drug testing lab-on-chip platforms, with measurements of metabolic changes of cell populations in form of heat output, without modifying the analyte and minimal interference with the microfluidic channel itself.

Building an interdisciplinary program of cardiovascular research at the Swiss Federal Institute of Technology- the ETHeart story.

In this backstory, researchers from Swiss Federal Institute of Technology (ETH Zurich) who initiated an interdisciplinary program to generate innovative solutions for different cardiovascular diseases, such as myocardial infarction, valvular replacement, and movement-based rehabilitation therapy, discuss the benefits and challenges of interdisciplinary research.

High-speed identification of suspended carbon nanotubes using Raman spectroscopy and deep learning.

The identification of nanomaterials with the properties required for energy-efficient electronic systems is usually a tedious human task. A workflow to rapidly localize and characterize nanomaterials at the various stages of their integration into large-scale fabrication processes is essential for quality control and, ultimately, their industrial adoption. In this work, we develop a high-throughput approach to rapidly identify suspended carbon nanotubes (CNTs) by using high-speed Raman imaging and deep learning analysis. Even for Raman spectra with extremely low signal-to-noise ratios (SNRs) of 0.9, we achieve a classification accuracy that exceeds 90%, while it reaches 98% for an SNR of 2.2. By applying a threshold on the output of the softmax layer of an optimized convolutional neural network (CNN), we further increase the accuracy of the classification. Moreover, we propose an optimized Raman scanning strategy to minimize the acquisition time while simultaneously identifying the position, amount, and metallicity of CNTs on each sample. Our approach can readily be extended to other types of nanomaterials and has the potential to be integrated into a production line to monitor the quality and properties of nanomaterials during fabrication.

Rheology of rounded mammalian cells over continuous high-frequencies.

Understanding the viscoelastic properties of living cells and their relation to cell state and morphology remains challenging. Low-frequency mechanical perturbations have contributed considerably to the understanding, yet higher frequencies promise to elucidate the link between cellular and molecular properties, such as polymer relaxation and monomer reaction kinetics. Here, we introduce an assay, that uses an actuated microcantilever to confine a single, rounded cell on a second microcantilever, which measures the cell mechanical response across a continuous frequency range ≈ 1-40 kHz. Cell mass measurements and optical microscopy are co-implemented. The fast, high-frequency measurements are applied to rheologically monitor cellular stiffening. We find that the rheology of rounded HeLa cells obeys a cytoskeleton-dependent power-law, similar to spread cells. Cell size and viscoelasticity are uncorrelated, which contrasts an assumption based on the Laplace law. Together with the presented theory of mechanical de-embedding, our assay is generally applicable to other rheological experiments.

Nano-opto-electro-mechanical switches operated at CMOS-level voltages.

Combining reprogrammable optical networks with complementary metal-oxide semiconductor (CMOS) electronics is expected to provide a platform for technological developments in on-chip integrated optoelectronics. We demonstrate how opto-electro-mechanical effects in micrometer-scale hybrid photonic-plasmonic structures enable light switching under CMOS voltages and low optical losses (0.1 decibel). Rapid (for example, tens of nanoseconds) switching is achieved by an electrostatic, nanometer-scale perturbation of a thin, and thus low-mass, gold membrane that forms an air-gap hybrid photonic-plasmonic waveguide. Confinement of the plasmonic portion of the light to the variable-height air gap yields a strong opto-electro-mechanical effect, while photonic confinement of the rest of the light minimizes optical losses. The demonstrated hybrid architecture provides a route to develop applications for CMOS-integrated, reprogrammable optical systems such as optical neural networks for deep learning.

Advances in NO2 sensing with individual single-walled carbon nanotube transistors.

The charge carrier transport in carbon nanotubes is highly sensitive to certain molecules attached to their surface. This property has generated interest for their application in sensing gases, chemicals and biomolecules. With over a decade of research, a clearer picture of the interactions between the carbon nanotube and its surroundings has been achieved. In this review, we intend to summarize the current knowledge on this topic, focusing not only on the effect of adsorbates but also the effect of dielectric charge traps on the electrical transport in single-walled carbon nanotube transistors that are to be used in sensing applications. Recently, contact-passivated, open-channel individual single-walled carbon nanotube field-effect transistors have been shown to be operational at room temperature with ultra-low power consumption. Sensor recovery within minutes through UV illumination or self-heating has been shown. Improvements in fabrication processes aimed at reducing the impact of charge traps have reduced the hysteresis, drift and low-frequency noise in carbon nanotube transistors. While open challenges such as large-scale fabrication, selectivity tuning and noise reduction still remain, these results demonstrate considerable progress in transforming the promise of carbon nanotube properties into functional ultra-low power, highly sensitive gas sensors.

Signal-to-noise ratio in carbon nanotube electromechanical piezoresistive sensors.

The signal-to-noise ratio (SNR) of piezoresistive transducers based on carbon nanotube field effect transistors (CNFETs) is an essential yet unexplored performance metric. Here, we show that the SNR of CNFET piezoresistors made of small band gap semiconducting SWNTs (SGS-SWNTs) depends strongly on the gate bias voltage. The SNR is found by combining low frequency 1/f noise with the piezoresistive signal. We find that SGS-CNFET piezoresistors are best operated at device off-state, where strain resolution is maximal.