Search

Colorimetric gas detectors have been widely applied in many fields such as environmental sciences, industrial hygiene, process control, forensic science and indoor air quality monitoring. They have a history of about 100 years and include devices such as gas detector tubes and paper-based gas detectors. The sensitivity and selectivity of the colorimetric gas detector are relatively high compared to other types of gas detectors such as semiconductor, catalytic combustion and electrochemical gas detectors. Detection of gas concentration can be performed by the naked eye in some colorimetric gas detectors. These methods do not require an electrical power source and are simple, so they are suitable for field operations. This review introduces the history and provides a general overview of the development in the research of colorimetric gas detectors. Recently, the sensitivity and selectivity of colorimetric gas detectors have improved. New materials such as enzymes or particles with a large surface area have been utilized to improve selectivity and sensitivity. Moreover, new gas detectors without toxic materials have been developed to reduce the environmental load. At present, there is a rapid development of IoT sensors in many industrial fields, which might extend the applications of colorimetric gas detectors in the near future.

With characters of low cost, portability, easy disposal, and high accuracy, as well as bulky reduced laboratory equipment, paper-based sensors are getting increasing attention for reliable indoor/outdoor onsite detection with nonexpert operation. They have become powerful analysis tools in trace detection with ultra-low detection limits and extremely high accuracy, resulting in their great popularity in medical detection, environmental inspection, and other applications. Herein, we summarize and generalize the recently reported paper-based sensors based on their application for mechanics, biomolecules, food safety, and environmental inspection. Based on the biological, physical, and chemical analytes-sensitive electrical or optical signals, extensive detections of a large number of factors such as humidity, pressure, nucleic acid, protein, sugar, biomarkers, metal ions, and organic/inorganic chemical substances have been reported via paper-based sensors. Challenges faced by the current paper-based sensors from the fundamental problems and practical applications are subsequently analyzed; thus, the future directions of paper-based sensors are specified for their rapid handheld testing.

In this study, we describe a monolithic and fully integrated paper-based device for the simultaneous detection of three prognostic biomarkers in saliva. The pattern of the proposed multiplexed device is designed with a central sample deposition zone and three identical arms, each containing a pre-treatment and test zone. Its one-step fabrication is realized by CO2 laser cutting, providing remarkable parallelization and rapidity (ca. 5 s/device). The colorimetric detection is based on the sensitive and selective target-induced reshaping of plasmonic multibranched gold nanoparticles, which exhibit a clear spectral shift (and blue-to-pink color change) in case of non-physiological concentrations of the three salivary biomarkers. A rapid and multiplexed naked-eye or smartphone-based readout of the colorimetric response is achieved within 10 min. A prototype kit for POCT testing is also reported, providing robustness and easy handling of the device.

Each year, a large amount of waste paper (WP) is generated in Japan, and due to the change in lifestyle with the COVID-19 pandemic, the WP collection and recycling system in Japan faces new challenges. Although the government of Japan has installed WP collection systems, the efficiency of these traditional WP collection systems is too low, and this causes inconvenience to the governments, residents, and other stakeholders. On the other hand, some recycling companies in Japan are trying to establish a nontraditional WP collection system by setting their own WP collection stations in cooperative supermarkets. Yet, the efficiency of this new system has not been clarified. This research aims to investigate the current status, operational characteristics, and the role of recycling companies’ WP collection stations in the Japanese WP collection system. By performing trade area analysis and stepwise OLS regression, this research will evaluate WP collection stations’ efficiency. Moreover, this research will also discuss how the new WP collection system improves WP collection efficiency and residents’ convenience. The results show that WP collection stations efficiency is particularly high in large supermarkets with many parking spaces and long business hours, as well as in areas with many families with children. Recycling companies’ WP collection system could create a system, which can satisfy resident, government, and recycling company interests at the same time.

The development of diagnostic tools for measuring a wide spectrum of target analytes, from biomarkers to other biochemical parameters in biological fluids, has experienced a significant growth in the last decades, with a good number of such tools entering the market. Recently, a clear focus has been put on miniaturized wearable devices, which offer powerful capabilities for real-time and continuous analysis of biofluids, mainly sweat, and can be used in athletics, consumer wellness, military, and healthcare applications. Sweat is an attractive biofluid in which different biomarkers could be noninvasively measured to provide rapid information about the physical state of an individual. Wearable devices reported so far often provide discrete (single) measurements of the target analytes, most of them in the form of a yes/no qualitative response. However, quantitative biomarker analysis over certain periods of time is highly demanded for many applications such as the practice of sports or the precise control of the patient status in hospital settings. For this, a feasible combination of fluidic elements and sensor architectures has been sought. In this regard, this paper shows a concise overview of analytical tools based on the use of capillary-driven fluidics taking place on paper or fabric devices integrated with solid-state sensors fabricated by thick film technologies. The main advantages and limitations of the current technologies are pointed out together with the progress towards the development of functional devices. Those approaches reported in the last decade are examined in detail.

The fabrication of low-cost, flexible, and recyclable electronic devices has been the focus of many research groups, particularly for integration in wearable technology and the Internet of Things (IoT). In this work, porous zinc oxide (ZnO) nanostructures are incorporated as a UV sensing material into the composition of a sustainable water-based screen-printable ink composed of car-boxymethyl cellulose (CMC). The formulated ink is used to fabricate flexible and foldable UV sensors on ubiquitous office paper. The screen-printed CMC/ZnO UV sensors operate under low voltage (≤2 V) and reveal a stable response over several on/off cycles of UV light exposure. The devices reach a response current of 1.34 ± 0.15 mA and a rise and fall time of 8.2 ± 1.0 and 22.0 ± 2.3 s, respectively. The responsivity of the sensor is 432 ± 48 mA W−1, which is the highest value reported in the literature for ZnO-based UV sensors on paper substrates. The UV-responsive devices display impressive mechanical endurance under folding, showing a decrease in responsivity of only 21% after being folded 1000 times. Their low-voltage operation and extreme folding stability indicate a bright future for low-cost and sustainable flexible electronics, showing potential for low-power wearable applications and smart packaging. publishersversion published

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.

Despite the potential in fabrication of microfluidic paper-based analytical devices (μPADs) for point-of-care testing (POCT) kits, the development of simple, accurate, and rapid devices with higher sensitivity remains challenging. Here, we report a novel method for 3D-μPAD fabrication with enclosed channels using vat photopolymerization to avoid fluid evaporation. In detail, height of the enclosed channels was adjusted from 0.3 to 0.17 mm by varying the UV exposure time from 1 to 4 s for the top barrier, whereas the exposure time for the bottom and side barriers was fixed. As a result, sample flow in the enclosed channels of 3D-μPADs showed lesser wicking speed with very scant evaporation compared to that in the hemi channels in the 3D-μPADs. The stoppage of evaporation in the enclosed channels significantly improved the gray intensity and uniformity in the detection zone of the 3D-μPADs, resulting in as low as 0.3 mM glucose detection. Thus 3D-μPADs with enclosed channels showed enhanced sensitivity compared to the 3D-μPADs with hemi channels when dealing with a small volume sample. Our work provides a new insight into 3D-μPAD design with enclosed channels, which redefines the methodology in 3D printing.

The disruptive force of the COVID-19 pandemic is lessening in power and plans are being made for the postcrisis period, among which increasing the sustainability of higher education is of significant importance. The study aims at establishing students’ existing environment-related routines during their home confinement, as a basis for applying green measures to campus living once academic life is resumed with the physical presence of students. The collected data rely on self-reported information provided by 816 students from Politehnica University of Timisoara (Romania), collected via an online, anonymous survey. The novelty of the approach is that household environment-related routines are investigated during a crisis period, with the possibility to build upon the results to implement tailored measures to encourage or diminish environmentally relevant consumption by young, highly skilled individuals. The students display a moderate awareness of environmental issues and indicate consumption routines that may be steered towards an increased sustainability-conscious campus life, through the combined intervention of the university, city administration, and stakeholder involvement. The findings are used to explore the possible directions for action towards increasing or contributing to the territorial sustainability in the socio-ecological context of Timisoara, the largest university city in the western part of Romania via educational, managerial and policy interventions.

This paper reports on the manufacture of ZnO nanoparticles (ZnO NPs) from Prosopis juliflora leaf extracts. Various methods of characterization were used, including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), and transmission electron microscope TEM. ZnO NPs has a hexagonal wurtzite structure with a preferred orientation of 101 planes, according to XRD. The functional groups found in ZnO NPs isolated from leaves are responsible for the FT-IR peaks that correspond to them. The morphology of the produced nanoparticles is a sphere-like form, as shown in the SEM pictures. TEM examination revealed ZnO NPs with a size of 50–55 nm. These ZnO NPs were used to remediate pollutants in paper mill effluents, and they were able to remove 86% of the organic pollutants from the sample at 0.05 mg/L dose and reduce 89% of the organic pollutants during a 5-h reflex time. Meanwhile, for the photocatalysis of paper mill effluents, it has been noted that COD was removed by 74.30%, 63.23%, and 57.96% for the first, second, and third cycles, respectively.

We present a rotational terahertz imaging system for inline nondestructive testing (NDT) of press sleeves for the paper industry during fabrication. Press sleeves often consist of polyurethane (PU) which is deposited by rotational molding on metal barrels and its outer surface mechanically processed in several milling steps afterwards. Due to a stabilizing polyester fiber mesh inlay, small defects can form on the sleeve’s backside already during the initial molding, however, they cannot be visually inspected until the whole production processes is completed. We have developed a fast-scanning frequenc-modulated continuous wave (FMCW) terahertz imaging system, which can be integrated into the manufacturing process to yield high resolution images of the press sleeves and therefore can help to visualize hidden structural defects at an early stage of fabrication. This can save valuable time and resources during the production process. Our terahertz system can record images at 0.3 and 0.5 THz and we achieve data acquisition rates of at least 20 kHz, exploiting the fast rotational speed of the barrels during production to yield sub-millimeter image resolution. The potential of automated defect recognition by a simple machine learning approach for anomaly detection is also demonstrated and discussed.

Altres ajuts: Agència per a la Competitivitat de l'Empresa de la Generalitat de Catalunya by FEDER funds, Institució Catalana de Recerca i Estudis Avançats, and ERDF funds In this paper, an organic, fully recyclable and eco-friendly 20-bit inkjet-printed chipless RFID tag is presented. The tag operates in the near field and is implemented by means of chains of resonant elements. The characterization and manufacturing process of the tag, printed with a few layers of a commercial organic ink on conventional paper substrate (DIN A4), are presented, and tag functionality is demonstrated by reading it by means of a custom-designed reader. The tags are read by proximity (through the near field), by displacing them over a resonator-loaded transmission line, and each resonant element (bit) of the tag is interrogated by a harmonic signal tuned to the resonance frequency. The coupling between the reader line and the resonant elements of the tag produce and amplitude modulated (AM) signal containing the identification (ID) code of the tag.

Photography-based photometry is a technique developed to perform high throughput UV photometric analysis without instrumental detectors in resource-limited settings. Its principle relies on the illumination of a sample with UV irradiation and then capturing the transmitted irradiation on a photosensitive paper surface. Therefore, the photosensitive surface acts as a detector for the determination of the concentration of analytes in the sample. This work aims to investigate the optimum photosensitive paper coatings for capturing the transmitted UV irradiation. To this end, photosensitive coatings based on silver, iron, and dichromate salts were tested using three assays of pharmaceutical and biochemical interest. The results from both calibrations, using standard solutions and the application in real samples, show that photosensitive coatings based on iron salts provide the best results. Importantly, the detection limits and the linear range of the calibration curves were better than those obtained with standard photometry. Based on these findings, cyanotype green papers, are proposed as optimum detectors for photography-based photometry. This finding simplifies the operation of the technique enabling the fabrication of prototype readers for analytical assays performed in resource limited settings, point-of-need applications or in the field.

Heterozygous familial hypercholesterolaemia (FH) is among the most common genetic metabolic lipid disorders characterised by elevated low-density lipoprotein cholesterol (LDL-C) levels from birth and a significantly higher risk of developing premature atherosclerotic cardiovascular disease. The majority of the current pediatric guidelines for clinical management of children and adolescents with FH does not consider the impact of genetic variations as well as characteristics of vascular phenotype as assessed by recently developed non-invasive imaging techniques. We propose a combined integrated approach of cardiovascular (CV) risk assessment and clinical management of children with FH incorporating current risk assessment profile (LDL-C levels, traditional CV risk factors and familial history) with genetic and non-invasive vascular phenotyping. Based on the existing data on vascular phenotype status, this panel recommends that all children with FH and cIMT ≥0.5 mm should receive lipid lowering therapy irrespective of the presence of CV risk factors, family history and/or LDL-C levels Those children with FH and cIMT ≥0.4 mm should be carefully monitored to initiate lipid lowering management in the most suitable time. Likewise, all genetically confirmed children with FH and LDL-C levels ≥4.1 mmol/L (160 mg/dL), should be treated with lifestyle changes and LLT irrespective of the cIMT, presence of additional RF or family history of CHD.

Food safety issues caused by pesticide residue have exerted far-reaching impacts on human daily life, yet the available detection methods normally focus on surface residue rather than pesticide penetration to the internal area of foods. Herein, we demonstrated gold nanoparticle (AuNP)-immersed paper imprinting mass spectrometry imaging (MSI) for monitoring pesticide migration behaviors in various fruits and vegetables (i.e., apple, cucumber, pepper, plum, carrot, and strawberry). By manually stamping food tissues onto AuNP-immersed paper, this method affords the spatiotemporal visualization of insecticides and fungicides within fruits and vegetables, avoiding tedious and time-consuming sample preparation. Using the established MSI platform, we can track the migration of insecticides and fungicides into the inner region of foods. The results revealed that both the octanol-water partition coefficient of pesticides and water content of garden stuffs could influence the discrepancy in the migration speed of pesticides into food kernels. Taken together, this nanopaper imprinting MSI is poised to be a powerful tool because of its simplicity, rapidity, and easy operation, offering the potential to facilitate further applications in food analysis. Moreover, new perspectives are given to provide guidelines for the rational design of novel pesticide candidates, reducing the risk of food safety issues caused by pesticide residue.

This editorial deals with the most cited papers published in the years 2018–2019 in the section “Polymer Theory and Simulation” of the journal Polymers. They are mainly regular research articles, but two reviews are also present in this analysis. The main topics appear related to (nano)composites, entangled polymers, ring polymers, nanotubes, polyelectrolytes, brushes and polymers at interfaces. The most used simulation methods are molecular dynamics, Brownian dynamics, and Monte Carlo, with the only exception being a paper dealing with metamaterials. The evolution of the fraction of publications falling into one of these fields over the past 50 years is visualized in Figure 1. Figure 2 shows the same data differently, so that the focus is on the qualitative rather than quantitative evolution within areas of research. In the following, and inline with the spirit of this short editorial we are going to review the most cited works in the order of their number of citations, rather than by discipline. [...]

Flying insect detection, identification, and counting are the key components of agricultural pest management. Insect identification is also one of the most challenging tasks in agricultural image processing. With the aid of machine vision and machine learning, traditional (manual) identification and counting can be automated. To achieve this goal, a particular data acquisition device and an accurate insect recognition algorithm (model) is necessary. In this work, we propose a new embedded system-based insect trap with an OpenMV Cam H7 microcontroller board, which can be used anywhere in the field without any restrictions (AC power supply, WIFI coverage, human interaction, etc.). In addition, we also propose a deep learning-based insect-counting method where we offer solutions for problems such as the “lack of data” and “false insect detection”. By means of the proposed trap and insect-counting method, spraying (pest swarming) could then be accurately scheduled.

I have the honor of writing this editorial note on the top 5 cited papers published in 2018 in the section of Biocatalysis of the Catalyst journal [...]

This is a memorial paper for Prof [...]

Attention to the environment and its problems has undergone unprecedented growth in recent years [...]