National Metrology Centre

Surmounting the inhomogeniety issue of gas sensors and realizing their reproducible ppb-level gas sensing are highly desirable for widespread deployments of sensors to build networks in applications of industrial safety and indoor/outdoor air quality monitoring. Herein, a strategy is proposed to substantially improve the surface homogeneity of sensing materials and gas sensing performance via chip-level pyrolysis of as-grown ZIF-L (ZIF stands for zeolitic imidazolate framework) films to porous and hierarchical zinc oxide (ZnO) nanosheets. A novel approach to generate adjustable oxygen vacancies is demonstrated, through which the electronic structure of sensing materials can be fine-tuned. Their presence is thoroughly verified by various techniques. The sensing results demonstrate that the resultant oxygen vacancy-abundant ZnO nanosheets exhibit significantly enhanced sensitivity and shortened response time toward ppb-level carbon monoxide (CO) and volatile organic compounds encompassing 1,3-butadiene, toluene, and tetrachloroethylene, which can be ascribed to several reasons including unpaired electrons, consequent bandgap narrowing, increased specific surface area, and hierarchical micro-mesoporous structures. This facile approach sheds light on the rational design of sensing materials via defect engineering, and can facilitate the mass production, commercialization, and large-scale deployments of sensors with controllable morphology and superior sensing performance targeted for ultratrace gas detection.

Additive manufacturing (commonly known as 3D printing) is defined as a family of technologies that deposit and consolidate materials to create a 3D object as opposed to subtractive manufacturing methodologies. Fused deposition modeling (FDM), one of the most popular additive manufacturing techniques, has demonstrated extensive applications in various industries such as medical prosthetics, automotive, and aeronautics. As a thermal process, FDM may introduce internal voids and pores into the fabricated thermoplastics, giving rise to potential reduction on the mechanical properties. This paper aims to investigate the effects of the microscopic pores on the mechanical properties of material fabricated by the FDM process via experiments and micromechanical modeling. More specifically, the three-dimensional microscopic details of the internal pores, such as size, shape, density, and spatial location were quantitatively characterized by X-ray computed tomography (XCT) and, subsequently, experiments were conducted to characterize the mechanical properties of the material. Based on the microscopic details of the pores characterized by XCT, a micromechanical model was proposed to predict the mechanical properties of the material as a function of the porosity (ratio of total volume of the pores over total volume of the material). The prediction results of the mechanical properties were found to be in agreement with the experimental data as well as the existing works. The proposed micromechanical model allows the future designers to predict the elastic properties of the 3D printed material based on the porosity from XCT results. This provides a possibility of saving the experimental cost on destructive testing.

Spoof plasmon surfaces consisting of linear arrays of subwavelength grooves are proposed as a novel platform for THz sensing. The tightly confined spoof plasmons, coupled via an Otto prism setup, are sensitive to the refractive index of the dielectric filling the grooves. Phase jumps at spoof plasmon resonances are used as a readout response for refractive index sensing. An overall sensitivity of 0.49 THz RIU−1 with figures-of-merit as high as 49 are achieved.

Abstract (a) Note on previously recorded values of the refractive index of air. For many centuries astronomers have recognized the effect that the refraction of the earth’s atmosphere has upon observations of the positions of celestial bodies. From the time of Tycho Brahe, when astronomical technique became sufficiently refined for the purpose, attempts have been made to apply corrections for the deviation of light in its passage through the earth’s atmosphere, and ultimately, in 1805, Delambre (1806) determined, by comparing a large number of astronomical observations, a value of the refractive index of atmospheric air for white light. The first accurate laboratory determination was made about the same time by Biot and Arago (1806), who measured the deviation of white light passing through air enclosed in a hollow glass prism. In 1857 Jamin (1857 b) made his original application of the methods of interferometry to the measurement of the refractive index of a gas. The increased accuracy obtainable by the use of the principle of the Jamin refractometer enabled Ketteler (1865) to determine the refractive indices of air for the red, yellow and green lines in the visible spectra of lithium, sodium and thallium respectively, and thus to make some of the earliest measurements of the dispersion of air.

In recent years, there has been growing interest in using precipitable water vapor (PWV) derived from global positioning system (GPS) signal delays to predict rainfall. However, the occurrence of rainfall is dependent on a myriad of atmospheric parameters. This paper proposes a systematic approach to analyze various parameters that affect precipitation in the atmosphere. Different ground-based weather features such as Temperature, Relative Humidity, Dew Point, Solar Radiation, PWV along with Seasonal and Diurnal variables are identified, and a detailed feature correlation study is presented. While all features play a significant role in rainfall classification, only a few of them, such as PWV, Solar Radiation, Seasonal, and Diurnal features, stand out for rainfall prediction. Based on these findings, an optimum set of features are used in a data-driven machine learning algorithm for rainfall prediction. The experimental evaluation using a 4-year (2012-2015) database shows a true detection rate of 80.4%, a false alarm rate of 20.3%, and an overall accuracy of 79.6%. Compared to the existing literature, our method significantly reduces the false alarm rates.

Convective heat transfer can be enhanced by changing flow geometry and/or by enhancing thermal conductivity of the fluid. This study proposes simultaneous passive heat transfer enhancement by combining the geometry effect utilizing nanofluids inflow in coils. The two nanofluid suspensions examined in this study are: water-Al2O3 and water-CuO. The flow behavior and heat transfer performance of these nanofluid suspensions in various configurations of coiled square tubes, e.g., conical spiral, in-plane spiral, and helical spiral, are investigated and compared with those for water flowing in a straight tube. Laminar flow of a Newtonian nanofluid in coils made of square cross section tubes is simulated using computational fluid dynamics (CFD)approach, where the nanofluid properties are treated as functions of particle volumetric concentration and temperature. The results indicate that addition of small amounts of nanoparticles up to 1% improves significantly the heat transfer performance; however, further addition tends to deteriorate heat transfer performance.

In this paper, we show that broadband spectral data can be experimentally extracted from corrugated metallic surfaces consisting of a linear array of subwavelength grooves supporting tightly confined spoof plasmons. Using a combination of the scattering edge coupling method and short-time Fourier transform, we are able to discern the group velocity characteristics of a spoof plasmon pulse, which in turn allows for the extraction of broadband dispersion data from 0.4 to 1.44 THz in a single measurement. Refractive index sensing of various fluids is demonstrated at microliter volume quantities by monitoring changes in not only the dispersion relation but also the frequency-dependent attenuation of the spoof plasmons. This gives information about both the real and imaginary part of the refractive index of an analyte, indicating the potential for spoof plasmon surfaces to fully characterize substances in the terahertz regime. Lastly, we show that the strong electromagnetic field confinement near the effective spoof plasmon frequency allows for surface-enhanced absorption spectroscopy, demonstrated here with α-lactose monohydrate powder. This allows us to take a more spectroscopic approach to THz sensing whereby substances can be uniquely identified by their spectral fingerprints. The enhanced light–matter interactions that occur in the vicinity of the spoof plasmon surface allow for a more efficient use of the limited power of current terahertz sources. Together with the ability to integrate spoof plasmon surfaces with microfluidics and to freely design its electromagnetic properties, we believe that these surfaces can be a very versatile platform on which chip-scale terahertz sensing can be performed.

Microstrip line (MLIN)-based glucose sensors have been used for noninvasive glucose monitoring. However, the current MLIN-based solutions do not provide enough sensitivity. The reason for this is that they rely on the fringing field of an MLIN that leads to a shallow penetration depth and thus low sensitivity. In this paper, we propose a sensitive MLIN-based glucose sensor using the main field. The idea is illustrated using the following three steps. Step 1 is sensing the glucose level by using the main field, which uses the material under test (MUT) as the substrate of an MLIN terminated with a load; Step 2 is identifying the contribution of different parameters and different components of parameters to sensitivity, which leads to Step 3, in which different parameters and/or different components of parameters are crosschecked for sensing. Two frequency bands, 100 to 500 MHz and 1.4 to 1.9 GHz, were investigated. In Step 1, the main field configuration was compared with its fringing field counterpart. It is shown that the proposed MLIN configuration presents an average sensitivity of 1.8×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> dB/(mg/dL) in terms of the reflection coefficient that is more than 10 times higher than that of its counterpart. In Step 2, different components of the reflection coefficient and the input impedance of the proposed configuration were examined, and their diverse contributions to the sensitivity were shown, which allows crosschecking to improve sensing accuracy. This was successfully shown in Step 3, in which algorithms for crosschecking were proposed, and the sensing accuracy was examined. In terms of the optimal sensing frequency band, 1.4 to 1.9 GHz shows higher sensitivity than 100 to 500 MHz, where the molecules may interact the most with the waves. This implies that the interaction between a wave and the sensing structure with the MUT contributes more to sensitivity than the direct interaction between the wave and the MUT. The radiofrequency safety of the proposed configuration was examined by checking the specific absorption rate of the MUT with the proposed structure. This paper offers a new avenue for the development of an MLIN-based noninvasive glucose sensor for continuous monitoring with high sensitivity in the near future. It can be used both as a single sensor and in a multiple-sensor glucose monitoring system.

In this paper, a simple algorithm is proposed to perform the nowcasting of rainfall in the tropical region. The algorithm applies global positioning system-derived precipitable water vapor (PWV) values and its second derivative for the short-term prediction of rainfall. The proposed algorithm incorporates the seasonal dependency of PWV values for the prediction of a rain event in the coming 5 min based on the past 30 min of PWV data. This proposed algorithm is based on the statistical study of four-year PWV and rainfall data from a station in Singapore and is validated using two-year independent data for the same station. The results show that the algorithm can achieve an average true detection rate and a false alarm rate of 87.7% and 38.6%, respectively. To analyze the applicability of the proposed algorithm, further validations are done using one-year data from one independent station from Singapore and two-year data from one station from Brazil. It is shown that the proposed algorithm performs well for both the independent stations. For the station from Brazil, the average true detection and false alarm rates are around 84.7% and 37%, respectively. All these observations suggest that the proposed algorithm is reliable and works well with a good detection rate.

To study the impact of personal carbon trading (PCT) mechanism on the economy and reliability of the power distribution system operation, this paper proposes an orderly charging and discharging strategy for electric vehicles (EVs) that integrates a dynamic update mechanism of charging tariff and carbon revenue, taking into account the travel characteristics of EVs and users’ willingness to respond. First, the probability density of the travel time parameters for EVs is calculated based on an improved kernel density estimation method. Second, the carbon emissions at each stage of the lifecycle of electric vehicles are calculated using a life cycle assessment approach (LCA), and a model for electric vehicle carbon quota and carbon revenue is constructed. Then, based on the net load data of the power distribution system, a dynamic updating model for the pricing of ordered charging and discharging is established. Finally, with the objective of reducing the dispatching cost for electric vehicle users and stabilizing the load fluctuation of the power distribution network, an optimization model for electric vehicle charging and discharging load dispatching is constructed. Based on the dynamic charging and discharging tariff information and state of charge (SOC) at the time of access to the grid, an evaluation model of the economic benefits of EV participation in orderly regulation is constructed. The response willingness of electric vehicle users to the dispatching strategy is inferred using the fuzzy logic control algorithm. The simulation results validate the effectiveness of this dispatching strategy in reducing the dispatching cost for EV users and stabilizing the net load fluctuation of the power distribution system. Furthermore, it is observed that as carbon prices increase, the optimization dispatching effect becomes more pronounced.

10.1080/21663831.2019.1601645

NRC publication: Yes

In this Letter, we propose general optimization methods to design broadband high-efficiency grating couplers for planar waveguides. We attribute the coupling bandwidth to the mismatch of effective indices between the diffracted beam and the actual grating structure around the operation wavelength for fiber to waveguide excitation. The coupling bandwidth formula is deduced. A simple parameter-separate optimization procedure is proposed for general layered grating couplers for high coupling efficiency. Using our principle, we optimized a grating coupler for a horizontal slot waveguide operating at wavelength 1.55 μm for TM polarization. The grating coupler has 1 dB bandwidth of 60 nm and coupling efficiency of 65% with incident light from single-mode optical fiber (SMF) at 8°.

In this study, we present a traceable method for determining the counting efficiency of optical particle size spectrometers (OPSS), also known as aerosol spectrometers. The primary standard consists of an aerosol generation setup, a vertical flow tube for particle homogenization and a reference optical particle counter. The OPSS under testing and the reference optical particle counter sample aerosol simultaneously through specially designed isokinetic sampling probes at number concentrations ranging from 0.5 cm−3 up to several hundred particles per cm3 (depending on the particle size). Calibration in terms of particle size relies by convention on the use of certified PS (polystyrene) spheres in the size range 100 nm - 10 μm. Here, the counting efficiency profiles of two commonly used OPSS, namely the Model 3330 OPS (TSI Inc., USA) and the 11-D monitor (Grimm GmbH, Germany) are presented for the first time and discussed within the context of the ISO 21501–1:2009 and 21501–4:2018 standards on the calibration of OPSS for indoor/outdoor measurements and optical particle counters (OPC) for clean rooms applications, respectively. We believe that this study can help manufacturers improve the design of their instruments, contribute to the further development of relevant national and international standards and pave the way for a standardised and traceable calibration of OPSS units installed at air quality monitoring stations and industrial/workplace environments.

We report an efficient and low-loss polarization rotator based on mode evolution using horizontal slot waveguide. The device is fabricated using complementary metal–oxide–semiconductor compatible processes, which allows monolithic integration with active drive electronics and other photonic components. A rotator fabricated with 100 μm transition length provides a high extinction ratio &amp;gt;14 dB for both transverse-magnetic (TM)-transverse-electric (TE) and TE-TM rotation. The excess loss of the device is &amp;lt;1 dB for both rotations as etching of the bottom Si waveguide is prevented. The device also exhibits a uniform rotation response over C+L band wavelength range of 1530-1600 nm.

In this paper, a simplified latitude and day-of-year (DoY)-based model is proposed for the retrieval of precipitable water vapor (PWV) from global positioning system (GPS) signal. Conventionally, PWV, the total amount of water in a vertical column of a unit cross-sectional area, is estimated from the GPS signal delay and a dimensionless conversion factor PI. This PI value is found to rely on a water vapor weighted mean temperature (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> ) value which varies widely across the day, month, and year for different regions. It is, therefore, both time specific and site specific. Analysis of the PI value and its effect on the retrieved PWV from the data obtained for tropical, subtropical, and temperate regions show that although the PI value is time and site specific, the change in the median value of PI for different years is minimal and is dependent only on factors like the latitude coordinates of the particular site and the DoY. Therefore, using the data obtained from 174 different sites, a latitude-coordinate and DoY-based PI value model for the retrieval of PWV is proposed in this paper. The proposed model has been successfully validated using data from different databases: the International GNSS Service Global Positioning System National Aeronautics and Space Administration (IGS GPS NASA) database, the International GNSS Service Global Positioning System Global Geodetic Observing System (IGS GPS GGOS) database, and the very-long-baseline interferometry (VLBI) database. Results show strong agreement between PWV values calculated using the proposed model and those calculated using the temperature dependent models with 99%, 98%, and 93% of error within ±1 mm for IGS GPS NASA, IGS GPS GGOS, and VLBI databases, respectively. Moreover, the proposed model allows for the ease of PWV retrieval, which is useful in meteorological studies and also applicable in satellite communications.

The extreme precision of optical atomic clocks has led to an anticipated redefinition of the second by the International System of Units. Furthermore, accuracies pushing the boundary of 1 part in 10 18 and beyond will enable new applications, such as in geodesy and tests of fundamental physics. The 1 S 0 to 3 D 1 optical transition in 176 Lu + has exceptionally low sensitivity to external perturbations, making it suitable for practical clock implementations with inaccuracy at or below 10 −18 . Here, we perform high-accuracy comparisons between two 176 Lu + references using correlation spectroscopy. A comparison at different magnetic fields is used to obtain a quadratic Zeeman coefficient of −4.89264(88) Hz/mT for the reference frequency. With a subsequent comparison at low field, we demonstrate agreement at the low 10 −18 level, statistically limited by the averaging time of 42 hours. The evaluated uncertainty in the frequency difference is 9 × 10 −19 and the lowest reported in comparing independent optical references.

A 3-μm-long ultrasmall surface plasmon polariton-effect-based transverse-magnetic (TM) mode to transverse-electric (TE) mode polarization rotator was demonstrated both theoretically and experimentally. Effective polarization rotation with 11-dB polarization extinction ratio (PER) was achieved in fabricated devices. The insertion loss at the transition region was about 11 dB.

3D printing of a tailor-designed support architecture with a tunable electrochemically active surface area for improving catalyst loading contributions to catalytic activity.

The optimal allocation of energy storage capacity is an important issue for integrated energy systems (IES). To reduce the impact of volatility and intermittency of renewable energy sources, the impact of volatility needs to be smoothed out by rational allocation of energy storage. To address the above issues, this paper proposes a method for the optimal allocation of source storage capacity considering integrated demand response(IDR). Firstly, the basic mechanism of IES based on energy hub(EH) is constructed, and the model and coupling relationship of equipment components in the system are introduced. The IDR model is built to optimize the load curve according to the real-time market tariff scheme, and then the confidence interval method is used to analyze the scenery uncertainty in IES and determine the scenery output curve under different confidence levels. On this basis, a bi-level optimization model is built that takes into account both source and storage capacity allocation and operational optimization. The upper-level planning model takes into account the uncertainty of wind power and photovoltaic output, and solves the allocation scheme of energy storage intending to minimize the total planning cost; the lower-level operation optimization model takes into account the output constraints of each unit and optimizes the output of the equipment to minimize the operation cost. Finally, it is verified that considering IDR can reasonably optimize the allocation of the system’s source storage capacity and reduce the system’s investment and operating costs.