Recent Progress in Micro- and Nanotechnology-Enabled Sensors for Biomedical and Environmental Challenges

Abstract

Micro- and nanotechnology-enabled sensors have made remarkable advancements in the fields of biomedicine and the environment, enabling the sensitive and selective detection and quantification of diverse analytes. In biomedicine, these sensors have facilitated disease diagnosis, drug discovery, and point-of-care devices. In environmental monitoring, they have played a crucial role in assessing air, water, and soil quality, as well as ensured food safety. Despite notable progress, numerous challenges persist. This review article addresses recent developments in micro- and nanotechnology-enabled sensors for biomedical and environmental challenges, focusing on enhancing basic sensing techniques through micro/nanotechnology. Additionally, it explores the applications of these sensors in addressing current challenges in both biomedical and environmental domains. The article concludes by emphasizing the need for further research to expand the detection capabilities of sensors/devices, enhance sensitivity and selectivity, integrate wireless communication and energy-harvesting technologies, and optimize sample preparation, material selection, and automated components for sensor design, fabrication, and characterization.

Keywords: biomedical; environmental; microtechnology; nanotechnology; sensors.

Figure 2

Resistive, capacitive, and resistive pulsing sensors. (A) The device can be transformed from conductive to non conductive Electrical and dielectric results of nanocomposites of MWNTs and PDMS with various weight fractions. When W(MWNT) = 8.03%, transformation occurs due to tensile strain. (B) Schematic showing the integrated R-C strain sensor and characterization method and the performance of the R-C sensor. Reprinted (adapted) with permission from [52]. Copyright 2020 American Chemical Society. (C) Capacitive pressure sensor based on porous Ecoflex-multiwalled carbon nanotube composite (PEMC) structures, with a sensitivity (6.42 and 1.72 kPa $\times {10}^{-1}$ in a range of 0–2 and 2–10 kPa, respectively) due to the synergetic effect of the porous elastomer and the percolation of carbon nanotube fillers. The figure shows a 3D model of a constructed prosthetic arm with an integrated robot finger for grasping movements; an LED is attached to the index finger to gauge the pressure sensed by the PEMC-based pressure sensor embedded into the thumb. Demonstration of the grasping abilities of the robot finger for a soft material (top 4 insets), and a hard material (plastic ball; bottom 4 insets), for both cases i-iv: Demonstrate progressive and reversible increase of capacitance as a function of robot finger force. Reprinted (adapted) with permission from [67]. Copyright 2020 American Chemical Society. (D) A low-cost and high-throughput multi-use resistive pulse sensor (RPS) produced through additive manufacturing demonstrated the ability to selectively detect and characterize both microplastics (shed from tea bags) and two algae species. Reprinted (adapted) with permission from [55]. Copyright 2020 American Chemical Society.

Figure 3

Thermoelectric sensing and electrochemical sensing. (A) Wearable thermoelectric generators (TEGs) are attracting interest due to their ability to self-power these electronic devices or sensors by harvesting human body heat. Wang et al. developed a numerical model to investigate the performance of wearable TEGs on the curved human wrist. Reprinted from [74] with permission from Elsevier Copyright (2017). (B) Combining microfluidics and laser-engraved fabrication methods, Yang et al. developed a wearable sensor for sensitive detection of uric acid and tyrosine in sweat. Reprinted from [34] with permission from Elsevier Copyright (2020).

Figure 4

Optical sensing and electromagnetic wave technology. (A–C) Single-cell analysis using a dual-functional nanoprobe based on dopant-driven plasmonic oxides, which enables the identification of a single THP-1 (related to leukemia) cells from peripheral blood mononuclear cells (PBMCs) and human embryonic kidney cells from human macrophage cells based on their surface-enhanced Raman spectroscopy (SERS) patterns. (B,C) (I) Cells are coated with PO (plasmonic oxide) via incubation. (II) Illustration (left) and optical image (right) of the PO-coated cells infused into a microfluidic chip and settled separately in the small grooves (highlighted in red). Reprinted from [108] with permission from Elsevier Copyright (2022). (D) Millimeter-wave technology. Schematic of the developed ultra-wideband millimeter-wave imaging system for real-time in vivo skin cancer imaging, achieving an overall synthetic bandwidth of 98 GHz. At each scanning step, two sub-band antennas are placed in front of the target, transmit their signals in their respective sub-band frequency ranges, and record the backscattered signals. Reprinted from [110] under Creative Commons Attribution 4.0 International License Copyright (2022). (E) Metamaterial-inspired biosensors using THz detection and a label-free biosensing approach for molecular classification of glioma cells. A metamaterial biosensor consisting of cut wires and split-ring resonators is used to realize polarization-independent electromagnetically induced transparency (EIT) at THz frequencies. The theoretical sensitivity of the biosensor was evaluated up to 496.01 GHz/RIU. The measured results indicated that mutant and wild-type glioma cells can be distinguished directly by observing variations in both the EIT resonance frequency and magnitude at any cell concentration without antibody introduction. Reprinted from [111] with permission from Elsevier Copyright (2022).

Figure 5

Biosignals (A) and bioinspired sensing (B). (Aa,Ab) Flexible and stretchable sensor platforms of biosignals for glucose, electrocardiogram, and body temperature. (Ac) Recorded ECG signals using the proposed ECG sensor and magnified view clearly showing PQRST waveforms. (Ad) ECG signal measured from the patch sensor attached to the chest of a human subject, compared to the signal from conventional gel-type electrodes. Reprinted from [135] under Creative Commons Attribution 4.0 International License Copyright (2021). (B) Bioinspired sensing. Biological and artificial mechanoreceptors. (Ba) Biological mechanoreceptors convert specific types of external pressure stimuli into receptor potentials. The soma of the mechanoreceptor integrates potentials and generates electrical impulses. The coded pressure information is ultimately sent to the brain for further processing. (Bb) The artificial mechanoreceptor is composed of a micro-pyramidal polypyrrole resistive pressure sensor and a NbOx volatile memristor. The output electrical spikes can be processed effectively by a pulse-coupled neural network (PCNN). (Bc) Schematic illustration of the tactile perception process in humans (left) and in the artificial mechanoreceptor system enhanced by the PCNN (right). Reprinted from [138] with permission from ACS Copyright (2021), American Chemical Society.

Figure 6

Biomedical challenges. Infectious diseases (A–D) and NCDs (E,F). (A–D) Illustration of the RapidPlex multisensor telemedicine platform. (A) Schematic illustration of the SARS-CoV-2 RapidPlex multisensor telemedicine platform for detection of SARS-CoV-2 viral proteins, antibodies (IgG and IgM), and inflammatory biomarker C-reactive protein (CRP). Data can be wirelessly transmitted to a mobile user interface. WE, working electrode; CE, counter electrode; RE, reference electrode. (B) Mass-producible laser-engraved graphene sensor arrays. (C) Photograph of a disposable and flexible graphene array. (D) Image of a SARS-CoV-2 RapidPlex system with a graphene sensor array connected to a printed circuit board for signal processing and wireless communication. Reprinted from [150] with permission from Elsevier Copyright (2020). NCDs—(E,F) Nanosensors able to detect biomarkers in blood, urine, or saliva that indicate the presence of a cardiovascular diseases, such as troponin, D-dimers, brain natriuretic peptide (BNP), and cardiac troponin I (cTnI). Reprinted from [159] with permission from ACS Copyright (2021), American Chemical Society.

Figure 7

Biomedical challenges. Antibiotic resistance (A–C) and aging population (D–G). For antibiotic resistance (A–C), microfluidics has been successfully applied. Pathogen identification and antimicrobial susceptibility testing (AST) from urine samples were achieved within 30 min, allowing the detection of 16S rRNA from single bacterial cells encapsulated in picoliter droplets and enabling the molecular identification of uropathogenic bacteria directly from urine in as little as 16 min. Moreover, in-droplet single-bacterial measurements of 16S rRNA provide a surrogate for AST, shortening the exposure time to 10 min for gentamicin and ciprofloxacin. Reprinted (adapted) from [36] under the terms of the Creative Commons CC BY license. (D–G) The aging population will push the development of smart implants. A new wireless inductive proximity sensor system enabled the early detection of implant loosening with high precision. Reprinted (adapted) with permission from [178]. (E–G) Development of a smart knee implant utilizing triboelectric energy harvesters for self-powering load sensors. Reprinted (adapted) with permission from [179].

Figure 8

Environmental challenges. (A) Eutrophication: Excess nutrients from human activities accumulate in water, causing disproportionate growth of algae and aquatic plants. (B) A low-cost and low-power turbidity sensing technique using Paired Emitter–Detector Diodes (PEDDs) adhering to the ISO 7027 turbidity sensing standard, enabling cost-effective and efficient environmental deployments of IoT sensors. Adapted from [186] under an open-access Creative Commons CC BY 4.0 license. (C) A flexible respiration sensor integrated into a face mask. (Ca) Schematic diagram of monitoring human breath by utilizing manganite oxide respiration sensor. (Cb) The wireless mode and (Cc) the wired mode of LSMO/Mica sensors used in human breath monitoring. (Cd) The obtained data are used for further processing and analysis. Reprinted from [190] under the terms of the Creative Commons CC-BY license.

Figure 9

(A) Climate-smart forestry utilizes a comprehensive network of sensors interconnected through IoT to monitor forest conditions in real time, providing early warning signals of ecosystem regime shifts. (B) Light Detection and Ranging (LiDAR) and Radio Detection and Ranging (RADAR) technologies enable the highly accurate detection of vegetation canopy components and subcanopy topography, as demonstrated by a LiDAR system’s point cloud slice. The figure shows a slice of a point cloud acquired by a LiDAR system, with points colored by return number (red, first return; green, second return; blue, third return), evidencing the two-layered structure of a forest. Reprinted (adapted) with permission from [202]. (C) Flushable ultrahigh-frequency (UHF)-RFID-based sensors, address sewer blockages and illicit connections, offering an easy-to-operate, high-throughput, accurate, and low-cost solution. Field trials in Auckland, New Zealand, validated the feasibility of UHF-RFID sensors for digital water management. Adapted with permission from referenced sources [206].

Figure 1

Schematic illustrating various sensing techniques and micro/nanotechnology approaches that enhance their performance in terms of specificity and sensitivity, enabling the development of new technologies to address upcoming biomedical and environmental challenges. The innermost circle shows fundamental sensing techniques, such as resistive sensing, capacitive sensing, piezoelectric sensing, optical sensing, acoustic sensing, and electrochemical sensing. The middle circle represents reported micro- and nanotechnology advances, including nanoparticles, nanomaterials, microfluidics, and MEMS. These technologies, together with the Internet of Things (IoT), are currently being applied to the fundamental techniques to enhance their performance. The outermost circle shows biomedical (blue) and environmental (green) challenges where these technologies are being applied.