Human Breath Research Articles

H-CoFe2O4/Ti3C2Tx/BNC Hybrid Aerogels with Modulation Impedance Matching for Electromagnetic Wave Absorption and Health Monitoring.

Given the limitations of single-function electromagnetic wave-absorbing materials (EWAMs) in meeting the evolving demands of complex usage scenarios, there is a growing need for structure-function integrated composites that offer a combination of microwave absorption, human monitoring, and thermal insulation. This study successfully synthesized two-dimensional (2D) Ti3C2Tx MXene via selective etching of Al from the Ti3AlC2 MAX phase. By introducing MXene into a composite of hydroxylated CoFe2O4 nanoparticles (h-CFO NPs) and bacterial nanocellulose (BNC) to modulate the electromagnetic performance of the EWAMs. The optimized electromagnetic parameters and three-dimensional (3D) porous structure achieve enhanced impedance matching of the wave absorber. The h-CFO/BNC/MXene (h-CFO@CM73) hybrid aerogel demonstrates superior electromagnetic wave absorption (EMWA) performance due to the synergistic effects of conductive loss, magnetic loss, interfacial polarization, and dipole polarization, where a minimum reflection loss (RLmin) of -32.66 dB at a thickness of 4.5 mm, an effective absorption bandwidth (EAB) of 10.70 GHz within the test range, and an EMWA efficiency reaching up to 99.92% were realized. Moreover, the hybrid aerogel presents sensitive sensing capabilities, detecting human joint movements, breathing, and vocalizations. Additionally, the developed hybrid aerogels exhibit commendable thermal insulation and infrared camouflage properties. Consequently, the fabricated multifunctional hybrid aerogel has excellent potential for monitoring care of infants, children, and pregnant women.

Synthesis and Characterization of Proton-Conductive [GO-CoFe2O4@γ-Fe2O3] Nanocomposites Series for Impedimetric Olfaction of Clinically Relevant VOCs in Simulated Human Breath.

Synthesis and Characterization of Proton-Conductive [GO-CoFe2O4@γ-Fe2O3] Nanocomposites Series for Impedimetric Olfaction of Clinically Relevant VOCs in Simulated Human Breath.

Moisture electricity generation based self-powered humidity sensor for smart agriculture

With the rapid development of smart agriculture, it is of great significance to monitor soil moisture through humidity sensors to maintain suitable soil environmental conditions and improve crop yield and quality. This study reports a self-powered humidity sensor (SPHS) based on moisture electricity generation, which was designed by using a humidity-sensitive composite film composed of polystyrene sulfonic acid: polyvinyl alcohol doped LiCl as the electrolyte layer and combined with copper and aluminum electrodes. The SPHS easily adsorbs and diffuses water molecules in humid environment, and relies on the principles of ion diffusion and electrochemical reaction to realize the sensing of soil moisture, without the external power source, and with good reliability and durability. The SPHS can spontaneously generate current response over a relative humidity (RH) range of 33 %–91 %, with a current response of 2.6 μA at 33 % RH and up to 76.1 μA at 91 % RH, which provides excellent RH-current linear response characteristics (R2 = 0.988). SPHS can be successfully applied in the field of human wearable devices, such as integration into masks for human breathing monitoring, as well as having excellent application potential in contactless human-computer interfaces. By integrating smart sensing technology and IoT communication technology, a smart agricultural environment sensing system was built in conjunction with SPHS for in-situ monitoring of soil moisture, ambient temperature, and light intensity to achieve real-time monitoring of the farmland environment, which promotes the development of agricultural production in the direction of intelligence, efficiency, and sustainability.

Human Daily Breathing Monitoring via Analysis of CSI Ratio Trajectories for WiFi Link Pairs on the I/Q Plane.

The measurement of human breathing is crucial for assessing the condition of the body. It opens up possibilities for various intelligent applications, like advanced medical monitoring and sleep analysis. Conventional approaches relying on wearable devices tend to be expensive and inconvenient for users. Recent research has shown that inexpensive WiFi devices commonly available in the market can be utilized effectively for non-contact breathing monitoring. WiFi-based breathing monitoring is highly sensitive to motion during the breathing process. This sensitivity arises because current methods primarily rely on extracting breathing signals from the amplitude and phase variations of WiFi Channel State Information (CSI) during breathing. However, these variations can be masked by body movements, leading to inaccurate counting of breathing cycles. To address this issue, we propose a method for extracting breathing signals based on the trajectories of two-chain CSI ratios on the I/Q plane. This method accurately monitors breathing by tracking and identifying the inflection points of the CSI ratio samples' trajectories on the I/Q plane throughout the breathing cycle. We propose a dispersion model to label and filter out CSI ratio samples representing significant motion interference, thereby enhancing the robustness of the breathing monitoring system. Furthermore, to obtain accurate breathing waveforms, we propose a method for fitting the trajectory curve of the CSI ratio samples. Based on the fitted curve, a breathing segment extraction algorithm is introduced, enabling precise breathing monitoring. Our experimental results demonstrate that this approach achieves minimal error and significantly enhances the accuracy of WiFi-based breathing monitoring.

Optimal human respiratory simulation for exhaled gas based on CFD method.

Human breathing is crucial for studying indoor environments and human health. Computational Fluid Dynamics (CFD) is a key tool for simulating human respiration. To enhance the accuracy of CFD simulations and reduce computation time, a new simulation strategy for human respiration is proposed in this paper. The effects of steady versus unsteady boundary conditions on simulation results were examined. For the unsteady boundary, sinusoidal exhalation velocities and non-inhalation gas were assumed, while the steady boundary involved constant velocities during both exhalation and inhalation phases. The jet center trajectory under different boundary conditions was analyzed and compared with experimental data. Additionally, variations in pollutant dispersion near the mouth under the two boundary conditions were discussed. Furthermore, the paper compared the calculation accuracy, calculation time and memory occupied by a single turbulence model or switching flow character models in human respiration simulation. Differences in exhaled gas vorticity and jet penetration depth across different flow models were identified. Finally, combined with the non-iterative algorithm, the optimal strategy of human respiration simulation was proposed. Results show that under the comprehensive consideration of calculation accuracy, calculation time and memory occupancy, using sinusoidal expiratory boundary conditions combined with the PISO algorithm, with the RNG k-ε model during expiratory phase, and switching into the laminar flow during inspiratory phase, is the optimal strategy of simulating human breathing.

Restoring brain connectivity by phrenic nerve stimulation in sedated and mechanically ventilated patients.

In critically ill patients, deep sedation and mechanical ventilation suppress the brain-diaphragm-lung axis and are associated with cognitive issues in survivors. This exploratory crossover design study investigates whether phrenic nerve stimulation can enhance brain activity and connectivity in six deeply sedated, mechanically ventilated patients with acute respiratory distress syndrome. Our findings indicate that adding phrenic stimulation on top of invasive mechanical ventilation in deeply sedated, critically ill, moderate acute respiratory distress syndrome patients increases cortical activity, connectivity, and synchronization in the frontal-temporal-parietal cortices. Adding phrenic stimulation on top of invasive mechanical ventilation in deeply sedated, critically ill, moderate acute respiratory distress syndrome patients increases cortical activity, connectivity, and synchronization. The observed changes resemble those during diaphragmatic breathing in awake humans. These results suggest that phrenic nerve stimulation has the potential to restore the brain-diaphragm-lung crosstalk when it has been shut down or impaired by mechanical ventilation and sedation. Further research should evaluate the clinical significance of these results.

Effects of particulate air pollution on BPDE-DNA adducts, telomere length, and mitochondrial DNA copy number in human exhaled breath condensate and BEAS-2B cells

Traffic-related particulate matter (PM) and polycyclic aromatic hydrocarbons (PAHs) have been linked to respiratory diseases and cancer risk in humans. Genomic damage, including benzo[a]pyrene diolepoxide (BPDE)-DNA adducts as well as alterations in telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN) are associated with respiratory diseases. This study aimed to investigate the association between exposure to traffic-related particulate pollutants and genomic damage in exhaled breath condensate (EBC) in human subjects and a bronchial epithelial cell line (BEAS-2B). Among the 60 healthy recruited subjects, residents living in high-traffic-congested areas were exposed to higher concentrations of PM2.5 (1.66-fold, p < 0.01), UFPs (1.79-fold, p < 0.01), PM2.5-PAHs (1.50-fold, p < 0.01), and UFPs-PAHs (1.35-fold, p < 0.05), than those in low-traffic-congested areas. In line with increased exposure to particulate air pollution, the high-traffic-exposed group had significantly increased BPDE-DNA adducts (1.40-fold, p < 0.05), TL shortening (1.24-fold, p < 0.05), and lower mtDNA-CN (1.38-fold, p < 0.05) in EBC. The observations in the human study linking exposure to PM2.5, UFPs, PM2.5-PAHs, and UFPs-PAHs with the aforementioned biological effects were confirmed by an in vitro cell-based study, in which BEAS-2B cells were treated with diesel exhaust particulate matter (DEP) containing fine and ultrafine PM and PAHs. Increased BPDE-DNA adducts levels, shortened TL, and decreased mtDNA-CN were also found in treated BEAS-2B cells. The shortened TL and decreased mtDNA-CN were in part mediated by decreased transcript levels of hTERT, and SIRT1, which are involved in telomerase activity and mitochondrial biogenesis, respectively. These results suggest that exposure to traffic-related particulate pollutants can cause genomic instability in respiratory cells, which may increase the health risk of respiratory diseases and the development of cancer.

Validation of a sensor system for the measurement of breath ammonia using selected-ion flow-tube mass spectrometry

The measurement of trace breath gases is of growing interest for its potential to provide non-invasive physiological information in health and disease. While instrumental techniques such as selected-ion flow-tube mass spectrometry (SIFT-MS) can achieve this, these are less suitable for clinical application. Sensitive sensor-based systems for breath ammonia could be more widely deployed, but have proven challenging to develop. This work demonstrates the sequential analytical validation of an electrochemical impedance-based sensor system for the measurement of ammonia in breath using SIFT-MS. Qualitative and relative responses between the two methods were comparable, although there were consistent differences in absolute concentration. When tested in artificial breath ammonia, sensors had a relative impedance sensitivity of 3.43 × 10-5ppbv-1for each breath in the range of 249-1653 ppbv (r2= 0.87,p< 0.05). When correlated with SIFT-MS using human breath (n= 14), ammonia was detected in the range of 100-700 ppbv (r= 0.78,p< 0.001), demonstrating acceptable sensitivity, reproducibility and dynamic range for clinical application.

Projection to latent structures regression and its application to Mach–Zehnder interferometer optical fiber sensors for acetone detection

The techniques of multivariate analysis methods as prediction models open a new vision to the analysis of applied data. The method used in this work was projection to latent structures regression, which is a regression method that uses the latent variables generated by calculating the linear relationship between the dependent and independent variables giving them equal importance and thus obtaining the maximum variance and correlation of these variables. This method was applied to optical fiber sensors for acetone detection. It is important to detect acetone because it is a biomarker of diabetes mellitus. The sensor was fabricated with two cascaded long-period fiber gratings (LPFG) with a 515 µm grating period and separated 1 cm to form a Mach–Zehnder interferometer (MZI). Clinical studies for the diagnosis of diabetes are usually invasive, the development of these sensors proposes a new non-invasive option through the detection of acetone in human breath whose concentrations are in the order of 1.25–2.5 ppm. To study the response of the sensors to acetone, different sensing films, such as polydimethylsiloxane (PDMS), polymethyl methacrylate, Apiezon L and Apiezon T were used, which have a good affinity to this compound. Spectral changes in the transmission spectrum of the MZI were obtained due to the modes interference together with an increment of the sensitivity, since the interaction between the acetone concentration and the sensing film provokes a change in the effective index of the cladding, which in turn is amplified by the LPFGs separation. The analysis showed that the best results were obtained for the sensor with PDMS as sensing film, with the lowest limit of detection, 1.7 ppm using 4 latent structures.

Ultrasensitive Acetone Gas Sensor Based on a K/Sn-Co3O4 Porous Microsphere for Noninvasive Diabetes Diagnosis.

The detection of acetone in human exhaled breath is crucial for the noninvasive diagnosis of diabetes. However, the direct and reliable detection of acetone in exhaled breath with high humidity at the parts per billion level remains a great challenge. Here, an ultrasensitive acetone gas sensor based on a K/Sn-Co3O4 porous microsphere was reported. The sensor demonstrates a detection limit of up to 100 ppb, along with excellent repeatability and selectivity. Remarkably, without the removal of water vapor from exhaled breath, the sensor can accurately distinguish diabetic patients and healthy individuals according to the difference in acetone concentrations, demonstrating its great potential for diabetes diagnosis. The enhanced sensitivity of the sensor is attributed to the increased oxygen adsorption on the material surface due to K/Sn codoping and the stronger coadsorption of Sn-K atoms to acetone molecules. These findings shed light on the mechanisms underlying the sensor's improved performance.

Rapid-response, low-detection-limit, positive-negative air pressure sensing: GaN chips integrated with hydrophobic PDMS films

Despite the importance of positive and negative pressure sensing in numerous domains, the availability of a single sensing unit adept at handling this dual task remains highly limited. This study introduces a compact optical device capable of swiftly and precisely detecting positive and negative pressures ranging from −35 kPa to 35 kPa. The GaN chip, which serves as a core component of the device, is monolithically integrated with light-emitting and light-detecting elements. By combining a deformable PDMS film coated with a hydrophobic layer, the chip can respond to changes in optical reflectance induced by pressure fluctuations. The integrated sensing device has low detection limits of 4.3 Pa and −7.8 Pa and fast response times of 0.14 s and 0.22 s for positive and negative pressure variations, respectively. The device also demonstrates adaptability in capturing distinct human breathing patterns. The proposed device, characterized by its compactness, responsiveness, and ease of operation, holds promise for a variety of pressure-sensing applications.

Application of V2O5 screen printed sensor for acetone

Vanadium pentoxide has gathered significant attention among transition metal oxide semiconductors over the years due to its applications in various fields. It is a non-stoichiometric and promising material for gas sensing, optoelectronic, microelectronic and electrochemical devices. Vanadium pentoxide has excellent properties including good thermoelectric characteristics, strong chemical and thermal durability, wide optical band gap and multiple valences. These properties make it an excellent choice for the fabrication of innovative electronic devices and functional materials that can work in their intended conditions. Acetone is a hazardous and easily ignited gas that finds extensive applications as a solvent, chemical intermediary, medication and cosmetic. There are several volatile organic compounds (VOCs) inhaled by the people. Acetone is the most volatile of the VOCs and is frequently utilized in industries and laboratories as an organic solvent or chemical intermediary. The normal range of acetone for human breathing is 300ppb – 900ppb. The excess inhalation causes biliousness, indolence and drowsiness of the nervous system as well as irritation of the eyes and respiratory system. The majority of acetone detection methods rely on table top instruments like Mass Spectrometry with Gas Chromatography or Proton Transfer Reaction which are bulky and costly too. In view of this, the present work is focused to detect acetone via chemo-resistive sensing method. We have fabricated screen printed Vanadium pentoxide electrode to sense acetone. The sensitivity was found to be increased with gas concentration. This shows that vanadium pentoxide could be good sensor for acetone detection. The advantage of this sensor is its ease of operation and economy for large scale utilization.

SiO2-capped ZnO quantum dot based highly sensitive optical fiber humidity sensor with potential applications in human breath monitoring and voice print recognition

This article describes the development and characterization of an optical fiber humidity sensor employing intensity modulation via the evanescent wave (EW) absorption technique. For the development of the sensor, SiO2-capped ZnO quantum dot (QDs) thin film is synthesized over the decladded portion of plastic cladding silica (PCS) fiber via the sol-gel method. A thorough experimental investigation was conducted by varying the thickness of the sensing film to optimize the sensor’s response. The sensing probe with optimized film thickness of 891 nm demonstrates a linear response over 30.5%–92.5%RH with an enhanced sensitivity of 46.2 mV/%RH (0.0138RH−1). Very fast response and recovery times of 2 s and 2.5 s are observed during humidification and dehumidification for the optimized sensing probe. The maximum resolution recorded during the short stability test is ±0.12%RH. Additionally, the proposed sensor demonstrates a very high degree of repeatability, reversibility, and stability. The proposed sensor has also been tested for human breath monitoring and voice print recognition. The result shows the sensor is able to detect minute humidity fluctuations in exhaled air during breathing and speaking.

Fabrication of Au-decorated V2O5 based sensor for ultra trace level detection of ammonia in an environment resembling human exhaled breath

Ammonia stands out as a significant breath biomarker for kidney-related diseases. Here we present the fabrication of a gold (Au) decorated V2O5 based sensor designed for detecting ammonia at parts per billion (ppb) level. The V2O5 particles were synthesized by thermal decomposition of ammonium metavanadate (NH4VO3) instead of using tedious and expansive synthesis routes. The product of the thermal decomposition of NH4VO3 was characterized utilizing various analytical techniques. Then this product (V2O5) was used for gas sensing study as original and when decorated with gold. The V2O5 based sensor, decorated with gold (Au) for a duration of 10 s, exhibits favorable characteristics including a linear response range spanning 50–5000 ppb, heightened sensitivity, stability, and remarkable resistance to humidity within the range of 50–90 % relative humidity (RH). Remarkably, the sensor demonstrates insensitivity towards higher concentrations of possible interfering liquid vapors. The sensor exhibits response and recovery times of 36 s and 300 s, respectively, in the presence of 1000 ppb ammonia and has the potential for accurately detecting and quantifying ammonia in an environment resembling human exhaled breath. The sensing device based on this material will be a valuable tool for clinical applications.

Facile synthesis of silver and copper modified graphitic carbon nitride for volatile organic compounds sensing

Volatile organic compounds (VOCs) pose significant health risks when inhaled or ingested in large quantities. Metal oxide-based solid-state gas sensors are commonly utilized for VOCs detection, including methanol, however their high operating temperature and selectivity are both biggest challenges. In this context, graphitic carbon nitride (g-C3N4) has emerged as a promising alternative for VOCs sensing due to its superior sensing properties. In this work, Cu and Ag doped g-C3N4 was synthesized via the polycondensation method for VOCs sensing applications. All the samples showed a selective response to methanol at room temperature. Notably, the Ag/g-C3N4 sensor exhibited a significantly enhanced response (~27.5) compared to both undoped g-C3N4 (~3.58) and Cu/g-C3N4 (~9.82) sensors towards 200 ppm methanol. The Ag/C3N4 based sensor showed rapid response (21 s) and recovery (17 s) times, along with excellent short-term and long-term stability. It was found that Ag/C3N4 sensor exhibited a good response to humidity levels ranging from 9 % to 93 % RH, without any significant variation observed when deposited on the ceramic and flexible polyimide substrates. Further, considering its practical applicability, the Ag/C3N4 sensor showed successful detection of alcohol in human breath, highlighting its potential for real-world applications.

Long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic mask with a Janus-structured all-natural fiber network for personal healthcare

Conventional disposable surgical masks have become an integral part of our daily lives, however, present a limited filtration efficiency, brief operative lifespan, and inability to degrade naturally, bringing a heavy burden to the environment. Moreover, these masks cannot efficaciously eliminate bacteria, potentially causing secondary and cross infections among users, thereby failing to curb the spread of infectious diseases. Herein, a fire-new, long-lifespan, biodegradable, self-disinfecting, and gas-sensing electronic-mask is nano-engineered with a Janus-structured all-natural fiber network (SA-CPN) constructed from animal-collagen and plant-fibers. SA-CPN demonstrates exceptional filtration performance (99.9%) for PM2.5 and maintains outstanding filtration efficiency after 10 test-cycles or 32 h in high-humidity conditions. SA-CPN exhibits robust antibacterial origins for extended periods, with antibacterial rates of 98.30%, 99.36%, and 98.11% against P aeruginosa, S aureus, and E coli, respectively, and can effectively filter airborne bacterial aerosols. Moreover, SA-CPN achieves real-time detection of ammonia concentrations, effectively identifying ammonia levels in exhaled human breath and external environments, and monitoring the human respiratory rate, potentially identifying underlying health conditions. The directional water vapor transmission capability of SA-CPN improves comfort when wearing. Notably, SA-CPN can fully biodegrade within 5 h under enzyme action. The proposed multifunctional electronic mask, featuring biocompatibility, biodegradability, self-disinfection, and ammonia sensing capabilities, holds significant promise in personal medical protective equipment for health monitoring and disease prevention.

A gold nano-urchin-decorated quasi-freestanding graphene-based humidity sensor with enhanced responsivity and a wide relative humidity detection range for real-time applications

Excellent humidity response and detection threshold are essential attributes of a humidity sensor. In this study, quasi-freestanding graphene (QFSG) was grown epitaxially on vicinal silicon carbide via thermal annealing, followed by decoration with hydrophilic gold nano-urchins (AuNUs). The resulting humidity sensor consistently achieved highly effective non-contact humidity-sensing performance, which can be used to monitor breathing and skin moisture. The proposed humidity sensor demonstrated a non-linear response of ∼119.98 % over a wide relative humidity detection range of 4–96 % at a frequency of 1 kHz, outperforming a QFSG-only humidity-sensing device (∼11.92 % and 22–84 % relative humidity, respectively). This 10-fold increase in humidity response and wider detection range is attributed to the hydrophilicity and plasmonic behavior of the AuNUs. It also demonstrated transient impedance response/recovery time of 4.5 and 3.0 s, respectively; low hysteresis of 3.6 %; and stability over 25 days, which are key factors for effective humidity sensing. The fast response and sensitivity of the AuNUs/QFSG humidity sensor made it possible to test for various real-time monitoring applications such as human breathing and non-contact proximity testing.

Recent Progress on Perovskite Materials for VOC Gas Sensing.

Volatile organic compound (VOC) gases are highly hazardous to human health, and their presence in the human breath plays an indispensable role for the early diagnosis of various diseases (cancer, renal failure, etc.). In recent times, perovskite materials have shown notable performance in the detection of VOC gases with high accuracy, fast response, recovery time, selectivity, and sensitivity, owing to their unique crystallographic structures and excellent optoelectronic properties. In this Review, we look at recent reports on perovskite-based sensors and their sensing performance toward VOC gases. Here, we focus on the sensing mechanisms of two types of perovskite materials, metal halide and metal oxide perovskites, and explain the differences in their crystal structures. We also discuss the common preparation methods used by researchers for the synthesis of these perovskite materials. Further, we elucidate various important factors influencing the sensing performance of perovskite-based sensors, such as doping, defects, morphology, temperature, humidity, and light. We conclude with the future prospects and challenges related to these perovskite-based sensors toward the detection of VOC gases.

Respiratory rate monitoring based on all-fiber strain-induced humidity sensor

In this paper, an agarose coated-fiber Bragg grating (AG-FBG) based respiratory rate (RR) sensor for evaluating respiratory function and health status by all-fiber strain-induced humidity-sensitive material is proposed and experimentally demonstrated. The variation of the environment humidity leads to changes in the film morphology of AG, i.e., expansion and contraction, which impose strains on FBG to dynamically shift the central wavelength. In the experiment, the average sensitivity of the proposed AG-FBG-based RR sensor is 23.6 pm/%RH in the range of 30 %RH–90 %RH. Under the monitoring of a commercial FBG demodulator with a wavelength resolution of 1 pm, rich human breathing information is collected. The RR monitoring under different human postures and breathing patterns are respectively measured. In one breathing cycle, the response time and recovery time are 778 ms and 762 ms, respectively. The proposed sensor is simple and low-cost, shows easy signal demodulation, stable signal wavelength variation, and high repeatability, which has potential applications in vital signs monitoring and medical treatment.

Utilization of Ultraviolet C Light-Emitting Diodes for the Deactivation of SARS-CoV-2 in Human Breath

Ultraviolet light has a long track record when it comes to use for deactivating harmful microorganisms. With recent developments in LED technology in terms of generating electromagnetic waves from this specific spectral range, new applications have emerged. In this study, the possibility of constructing an effective miniature UV barrier for deactivating the SARS-CoV-2 virus in both exhaled and inhaled air is investigated. Our findings demonstrate that utilizing commonly available UVC diodes operating at the wavelength of 275 nm makes it possible to attain an adequate level of deactivation that fulfills the standards specified for commercial devices. Full Text: PDF References N.G. Reed, "The History of Ultraviolet Germicidal Irradiation for Air Disinfection", Public Health Rep. 125(1), 15 (2010) CrossRef S. Oliveira De Souza, A. Cardoso, A. Sales, C. Sarmento, F. D'errico, "Effectiveness of a UVC air disinfection system for the HVAC of an ICU", Eur. Phys. J. Plus 137, 37 (2022), CrossRef N. Trivellin et al., "UV-Based Technologies for SARS-CoV2 Inactivation: Status and Perspectives", Electronics 10, 4 (2021), CrossRef R. S. Bergman, "Germicidal UV Sources and Systems", Photochem. Photobiol. 97(3), 466 (2021), CrossRef M. Shatalov, R. Jain, T. Saxena, A. Dobrinsky, M. Shur, "Chapter Two - Development of Deep UV LEDs and Current Problems in Material and Device Technology", Semiconductors and Semimetals 96, 45 (2017). CrossRef W. Kowalski, Ultraviolet Germicidal Irradiation Handbook UVGI for Air and Surface Disinfection, 1 (2009), CrossRef P. Sobotka, M. Przychodzki, K. Uściło, T.R. Woliński, M. Staniszewska, "Effect of Ultraviolet Light C (UV-C) Radiation Generated by Semiconductor Light Sources on Human Beta-Coronaviruses’ Inactivation", Materials 15(6), 2302 (2022), CrossRef Y. Gerchman, H. Mamane, N. Friedman, M. Mandelboim, "UV-LED disinfection of Coronavirus: Wavelength effect", J. Photochem. Photobiol. B Biol. 212, 112044 (2020), CrossRef R.M. Mariita, J.W. Peterson, "Not all wavelengths are created equal: disinfection of SARS-CoV-2 using UVC radiation is wavelength-dependent", Access Microbiology 3(11), 1 (2021), CrossRef Polio laboratory manual, 4th ed., World Health Organization 2004. DirectLink J.V. Maizel, D.O. White, M.D. Scharff, "The polypeptides of adenovirus: I. Evidence for multiple protein components in the virion and a comparison of types 2, 7A, and 12", Virology 36(1), 115 (1968), CrossRef H. Inagaki, A. Saito, H. Sugiyama, T. Okabayashi, S. Fujimoto, "Rapid inactivation of SARS-CoV-2 with deep-UV LED irradiation", Emerging Microbes and Infections 9(1), 1744 (2020), CrossRef