Simple Configuration Research Articles

Sustainable, eco-friendly, and cost-effective energy generation based on coffee grounds for self-powered devices and alarm systems

The Internet of Things (IoT) requires non-pollution energy sources to power small electronic devices. These energy sources can be harvested using triboelectric nanogenerators formed by lightweight and eco-friendly components. Herein, we develop a novel triboelectric layer of coffee grounds for a triboelectric nanogenerator with ability to harvest the vibration energy and transform it into electrical energy. This layer of coffee grounds has a simple electromechanical configuration that simplifies the collocation of the nanogenerator on irregular topologies of vibration sources. This device uses sustainable and eco-friendly components, achieving a stable electromechanical behavior close to 22500 operating cycles. With a load resistance of 39.97 MΩ, our device can generate an output power density of 75.48 mWm−2 under vibration of 3 g at 25 Hz. This device lighted 116 blue commercial LEDs and powered a thermohydrometer and a digital chronometer. Furthermore, an emergency alarm button with Arduino was implemented using the nanogenerator. The proposed device can be used to generate low-cost sustainable energy for applications in IoT devices.

High energy density picoliter-scale zinc-air microbatteries for colloidal robotics.

The recent interest in microscopic autonomous systems, including microrobots, colloidal state machines, and smart dust, has created a need for microscale energy storage and harvesting. However, macroscopic materials for energy storage have noted incompatibilities with microfabrication techniques, creating substantial challenges to realizing microscale energy systems. Here, we photolithographically patterned a microscale zinc/platinum/SU-8 system to generate the highest energy density microbattery at the picoliter (10-12 liter) scale. The device scavenges ambient or solution-dissolved oxygen for a zinc oxidation reaction, achieving an energy density ranging from 760 to 1070 watt-hours per liter at scales below 100 micrometers lateral and 2 micrometers thickness in size. The parallel nature of photolithography processes allows 10,000 devices per wafer to be released into solution as colloids with energy stored on board. Within a volume of only 2 picoliters each, these primary microbatteries can deliver open circuit voltages of 1.05 ± 0.12 volts, with total energies ranging from 5.5 ± 0.3 to 7.7 ± 1.0 microjoules and a maximum power near 2.7 nanowatts. We demonstrated that such systems can reliably power a micrometer-sized memristor circuit, providing access to nonvolatile memory. We also cycled power to drive the reversible bending of microscale bimorph actuators at 0.05 hertz for mechanical functions of colloidal robots. Additional capabilities, such as powering two distinct nanosensor types and a clock circuit, were also demonstrated. The high energy density, low volume, and simple configuration promise the mass fabrication and adoption of such picoliter zinc-air batteries for micrometer-scale, colloidal robotics with autonomous functions.

Assessing the performance of three experimental methods to investigate air path inside wall assemblies

Air leakages in buildings’ envelopes can lead to an over-consumption of energy and to additional issues such as moisture damage and poor indoor environment. The leakage air flow rate is usually assessed at the building scale using a pressurization test and leakage locations are commonly detected by infrared thermography or smoke. However, little is known about the air paths within wall assemblies, despite the need for detailed experimental data to validate numerical models for the coupled heat, moisture and pollutants transfers. One of the reasons is the difficulty to find adapted and robust experimental methods.In this paper, three experimental laboratory approaches are tested on simple light-wall assembly configurations: the implementation of three-dimensional grids of thermocouples and relative humidity sensors within the wall, and the use of a micro-particle tracer. The results are compared with each other as well as with numerical simulations.It was found that thermocouple grid has limited intrusiveness, good accuracy and response time but results are subject to flow fluctuations. Moreover, heat capacity and conductive transfer within materials complicate the correlation between heat and air transfers. Humidity sensors grid avoids the latter issue but is intrusive, overestimating air dispersion. The micro-particle tracer has the advantage of being non-intrusive and less impacted by flow fluctuations but its ability to track the air flow is strongly linked with the insulation filtration properties and the flow velocity. Overall this method seems to provide the best results but it is also the most complex and time-consuming one.

Bio-inspired colorful selective solar absorber

Solar energy is widespread and easily accessible which make it the most promising renewable energy to solve energy crisis. As the ubiquitous distribution of selective solar absorbers (SSAs) employed in architecture and street, their substantially contributions to mitigate environment pollution and facilitate daily energy consumption are important; however, its implementation has been largely limited to poor color display and unideal cost-efficiency. Here, we develop a bio-inspired selective solar absorber (Bio-SSA) for use as an aesthetic compatible photothermal convector based on SiO2/W/SiO2/Cu resonant absorption cavity and two-dimension photonic crystal (PC), in which the solar absorption and infrared (IR) emissivity are 81.1 % and 0.17 with 7 different color display all in one. The calculated theoretically saving of year-round electricity energy up to maximum 1598 KWh when implemented in high altitude regions in China. Such Bio-SSA enjoys low-cost and simple configuration can further been utilized in large-scale and path a new way for architecture integratable solar energy system.

Double-link-failure-tolerant shared protection for fully coupled/half-split switchable point-to-multipoint coherent optical systems

Beyond 5G, the next-generation wireless communication standard requires an optical communication network with a more reliable point-to-multipoint system. A highly reliable, futuristic point-to-multipoint coherent optical system must update wavelength-division-multiplexing-based passive optical networks to a more disaster-resistant architecture that can switch between bypass and backup links. We propose, to our knowledge, a novel link-pair shared protection that can respond locally to double-link failures that result from a significant disaster. We validate the high availability of several network configurations, assuming a double-link disconnection, can be obtained irrespective of the transmission distance of the feeder fiber. We experimentally demonstrate link-pair shared protection with bidirectional wavelength pre-assignment for two of the four feeder fiber failures and validate a penalty of less than 2 dB for double-link failures. Furthermore, we prove that reconnection can be performed with a penalty of at most 2 dB in an experiment with shared protection with a single-link broadcast-and-select function that can manage partial double-link failures using a simple configuration.

A laminar spray group combustion experiment (LSGCE) with in situ image diagnostic methods and image analysis algorithms.

Spray combustion is important for different engines. The understanding of spray combustion should be further promoted especially in the non-dilute region, and there is lack of well-defined spray experiments. In this study, an experimental platform was developed. Using this platform, a cylindrical quasi-laminar spray can be formed and ignited by a thin and straight hot wire, making it a simple configuration. Two image diagnostic methods were also developed to capture in situ microscopic droplet images and macroscopic droplet-flame images synchronously. Different image analysis algorithms were developed to obtain droplet statistics (diameter, velocity, and number density) and flame information (size, location, and flame propagation speed) from the raw images. The design, diagnostic methods, and image analysis methods are detailedly presented. This experimental platform can cover a wide range of operating conditions, with Gig in a range of 0.01-0.06 and temperature in a range from room temperature to 1400K. In addition, this platform is small in size and is capable of further implanting into a ground-based microgravity facilitaty. The whole experimental system can be applied in spray ignition and combustion studies and can provide legitimate data for further model development.

Photo-Assisted Rechargeable Metal Batteries: Principles, Progress, and Perspectives.

The utilization of diverse energy storage devices is imperative in the contemporary society. Taking advantage of solar power, a significant environmentally friendly and sustainable energy resource, holds great appeal for future storage of energy because it can solve the dilemma of fossil energy depletion and the resulting environmental problems once and for all. Recently, photo-assisted energy storage devices, especially photo-assisted rechargeable metal batteries, are rapidly developed owing to the ability to efficiently convert and store solar energy and the simple configuration, as well as the fact that conventional Li/Zn-ion batteries are widely commercialized. Considering many puzzles arising from the rapid development of photo-assisted rechargeable metal batteries, this review commences by introducing the fundamental concepts of batteries and photo-electrochemistry, followed by an exploration of the current advancements in photo-assisted rechargeable metal batteries. Specifically, it delves into the elucidation of device components, operating principles, types, and practical applications. Furthermore, this paper categorizes, specifies, and summarizes several detailed examples of photo-assisted energy storage devices. Lastly, it addresses the challenges and bottlenecks faced by these energy storage systems while providing future perspectives to facilitate their transition from laboratory research to industrial implementation.

Compact planar 28/60‐GHz wideband MIMO antenna for 5G‐enabled IoT devices

SummaryThis work presents a compact two‐element multi‐input‐multi‐output (MIMO) antenna for 5G‐enabled IoT devices. The antenna operates over a wide frequency range of 24.6 to 31.4 GHz (28‐GHz band) and 57.6 to 60.2 GHz (60‐GHz band). Each MIMO element consists of an inverted L‐shaped slotted radiator with a partial ground plane. The antenna offers a peak gain of 5.45 and 5.56 dBi across two operating bands. The minimum isolation between the two ports is −26.5 dB, reaching a maximum value of over −45 dB. The investigation of MIMO metrics like “envelope correlation coefficient (ECC),” “diversity gain (DG),” “mean effective gain (MEG),” “channel capacity loss (CCL),” and “total active reflection coefficient (TARC)” also show favorable characteristics. The antenna is fabricated on a 10 × 22 × 0.503 mm3 Rogers 5880 substrate. The experimental results are in close agreement with that of the simulation results. The distinguishing features of the proposed antenna such as its compact design, simple geometrical configuration, wide operating bandwidth, low ECC, and high isolation make it a strong candidate for 5G‐enabled IoT devices.

Tapered fiber optic sensor for arterial pulse wave monitoring

Arterial pulse wave monitoring has been recognized as an effective medical diagnostic tool for various cardiovascular diseases. To overcome the barriers in traditional, complex, and expensive detection configurations, new electronic and optical sensors have been developed with their unique advantages. Particularly, various configurations of fiber-optic sensors have been proposed. This paper demonstrates the use of a tapered optical fiber structure to create a sensitive sensor that can detect carotid arterial pulse waves on the skin surface. The demonstrated fiber sensor probe utilizes an in-line Mach-Zehnder interferometer configuration and liquid-gold film coating on the sensor tip to enhance its sensitivity and demonstrate its use by encapsulating the sensor with a flexible elastomer material for detecting arterial pulse waves with a simple testing configuration. Considering the simple fabrication and high sensitivity without a complex demodulation scheme, the proposed sensor has broad implementation in biomedical health monitoring systems.

Parallel two-step spatial carrier polarized phase-shifting common-path digital holography

A zero-order term causes bad effect on the phase reconstruction of off-axis holography, which can be solved by two-step carrier phase-shifting. Therefore, a common-path digital holography is proposed by using parallel two-step spatial carrier polarized phase-shifting in a 4f optical system for quantitative phase imaging. This holography is established based on a 4f optical system by inserting a 45° tilted cube polarized beamsplitter to split the horizontal and vertical polarization components in one beam. Via intentional polarization modulation, two off-axis holograms with π/2 phase-shift can be captured in one shot, so the subtraction between two holograms would cancel out the zero-order term. The phase distribution of a thin specimen can be retrieved with enhanced quality. There are two apertures at the input plane of the 4f optical system, one for object and the other for nothing, while only one polarized cube beamsplitter is inserted into a 4f optical system. Thus, this system is common-path with strong anti-noise ability and high stability, while it also has simple optical configuration and easy optical alignment. Several experimental results would be presented to demonstrate the validity of the proposed holography.

Assessing the performance of infrared thermography and PIV methods to identify and characterize the air inlets and outlets in wall assemblies

Building airtightness is crucial for reducing energy demand in the building sector and preventing moisture damage and indoor environment quality issues. Mandatory airtightness tests are now commonly performed in many countries to quantify the total envelope leakage rate of real buildings. For a more precise diagnosis, air leakages are usually identified by infrared thermography or visualized by smoke. However, a finer analysis is also needed to characterize precisely the air flow through specific leaks. Numerical models have been developed for this purpose but experimental data are necessary to validate them. In this paper, two experimental approaches are tested on simple light-wall assembly configurations to address this need: infrared thermography (IRT) and the innovative use of particle image velocimetry (PIV) with a specific experimental set-up and protocol developed. The results are compared with each other as well as with numerical simulations. Results showed that both techniques can be applied for the experimental characterization of the air inlet/outlet of a wall assembly with different advantages and drawbacks. IRT is easy to implement, non-intrusive, possible for in-situ investigations, but the correlation between the thermographs and the air dispersion at the outlet is not straight forward due to thermal inertia and heat conduction issues. PIV gives direct results on the velocity field and enables quantitative analysis of air flow rates for various configurations, with some limitations: a difficult implementation; restrictions on the possible infiltration velocity range and difficulties to visualize the flow exactly at the interface with the wall assembly.

A high-rate, impact-driven biaxial fragmentation experiment for ductile materials

The experimental investigation of high strain rate fragmentation has generally been limited to one of two cases: analytically powerful but simple one-dimensional loading configurations, or complicated multiaxial experiments more closely approximating use applications. The former, exemplified by Mott-style ring fragmentation, promotes simple and confident analysis—forming the backbone of the field and revealing the basic nature of dynamic fragmentation in solids—but ignores some critical mechanisms in order to achieve that simplicity. The latter, while informing applications of interest such as ballistic impact, may provide limited insight and is often difficult to access diagnostically. This work presents an attempt to help bridge the gap between 1D ring expansion and 3D fragmentation experiments in the form of impact driven, high-strain-rate biaxial tensile fragmentation experiments. The impact target system consists of a thin specimen plate and a thick polymer impact buffer. The latter serves as a fluid-like medium allowing momentum transfer between an impacting projectile and a rapidly growing near-hemispherical bulge in the specimen plate. The deformation of the specimen and fragmentation pattern are observed using ultra-high-speed optical imaging as well as flash x-ray imaging, and individual fragments are recovered and characterized post-mortem. Using this method, the fragmentation behavior of 6061-T6 Aluminum is investigated at tensile strain rates exceeding 105s−1 and at higher stress triaxiality than that commonly achieved.

An optimized design of delay-and energy-efficient Booth multiplier

Multipliers are essential computation units in virtually all computing systems, including processors and numerous AI accelerator architectures. This paper presents an optimized architecture for a Booth multiplier, targeting high performance while minimizing energy consumption and area utilization. The design optimization focuses on all three multiplier stages: partial product generation, reduction, and summation. To enhance delay and energy efficiency in the partial product generation stage, we first employed a simplified configuration comprising inverters and a sign selection unit instead of complex binary-to-two's complement circuitry. Next, to achieve further delay and area efficiency at this stage, logic optimization is applied at the partial product's generation circuitry by designing Booth encoders to remove redundant logic in multiplexers circuitry. Moreover, we introduced specialized sign compressors tailored for carry-save compression in the compression stage. Compared to conventional counterparts, these compressors offered lower power consumption and reduced critical path delay with only two XOR logic gates. Finally, in the summation stage, we proposed an optimized design segment for Carry Look-Ahead Adder for the final summation stage, designed to deliver swift throughput with minimal fan-in logic gates, even in the context of high bit-width configurations. This segment is cascaded to make a 13-bit final adder for the summation stage in the proposed design. The proposed architecture undergoes ASIC-targeted synthesis in Cadence Genus employing FreePDK CMOS 45 nm process technology. Synthesized results, along with theoretical design complexity comparison, demonstrate that the proposed design surpasses state-of-the-art 8 × 8 multiplier designs by critical metrics, including delay, power consumption, area utilization, power delay product, and area delay product.

Prediction of Accident Risk Levels in Traffic Accidents Using Deep Learning and Radial Basis Function Neural Networks Applied to a Dataset with Information on Driving Events

A complex AI system must be worked offline because the training and execution phases are processed separately. This process often requires different computer resources due to the high model requirements. A limitation of this approach is the convoluted training process that needs to be repeated to obtain models with new data continuously incorporated into the knowledge base. Although the environment may be not static, it is crucial to dynamically train models by integrating new information during execution. In this article, artificial neural networks (ANNs) are developed to predict risk levels in traffic accidents with relatively simpler configurations than a deep learning (DL) model, which is more computationally intensive. The objective is to demonstrate that efficient, fast, and comparable results can be obtained using simple architectures such as that offered by the Radial Basis Function neural network (RBFNN). This work led to the generation of a driving dataset, which was subsequently validated for testing ANN models. The driving dataset simulated the dynamic approach by adding new data to the training on-the-fly, given the constant changes in the drivers’ data, vehicle information, environmental conditions, and traffic accidents. This study compares the processing time and performance of a Convolutional Neural Network (CNN), Random Forest (RF), Radial Basis Function (RBF), and Multilayer Perceptron (MLP), using evaluation metrics of accuracy, Specificity, and Sensitivity-recall to recommend an appropriate, simple, and fast ANN architecture that can be implemented in a secure alert traffic system that uses encrypted data.

Power generation system utilizing cold energy from liquid hydrogen: Integration with a liquid air storage system for peak load shaving

Liquid hydrogen (LH2) can serve as a carrier for hydrogen and renewable energy by recovering the cold energy during LH2 regasification to generate electricity. However, the fluctuating nature of power demand throughout the day often does not align with hydrogen demand. To address this challenge, this study focuses on integrating liquid air energy storage with a power generation system based on LH2 regasification. Three configurations are proposed and compared: no-storage, partial-storage, and full-storage. In the no-storage system, power is generated using recuperated Brayton cycle and two organic Rankine cycles without energy storage. In contrast, the partial-storage system offers flexible operational modes. During peak times, cold energy is utilized for power generation, while it is diverted to store liquid air during off-peak times. In the full-storage system, produced energy is partially reserved throughout the day. Thus, compared to the partial-storage system, the full-storage system boasts a simplified configuration, eliminating the need for operational mode transitions. Furthermore, its larger liquid air storage capacity maximizes the difference in power production up to 4.53 MW between on- and off-peak times. Consequently, despite its higher capital costs, the full-storage system demonstrates greater economic viability, especially when considering government subsidies.

Particle Tracking of Orientation and Velocity Of Arbitrary Shape

Dispersions or particulate systems are prevalent in numerous natural and practical applications. Characterisation of such multiphase systems usually involves measuring size, spatial location, velocity and number density, which is usually non-trivial. The 'Depth from Defocus' (DFD) technique provides an imaging-based volumetric approach for estimating the size and position of dispersed spherical particles using the blurring information from a shadowgraph image. The two-image DFD approach involves two cameras to capture simultaneous images at different degrees of blur, which, although simpler, requires a mandatory calibration procedure. This study proposes a single-image DFD technique that provides a calibration-free size estimation using theoretical functions while evaluating position requires a simple calibration. The efficacy of this technique is demonstrated for various sparse spherical dispersions, including target dots, dispersed glass beads, liquid droplets in sprays and surface bubble rupture, and pollen grains. The method further enables precise determination of the measurement volume, which is crucial, allowing for bias-free estimates of the size distribution and volume concentration. The simple optical configuration and semi-automatic calibration procedure make this method easily deployable and accessible for diverse applications. The pixelation effect on the limiting value of the degree of blur is also estimated theoretically and compared with experiments. This effect is of interest concerning any typical discrete sensor imaging system in general.

Inherently Decoupled Dc-Link Capacitor Voltage Control of Multilevel Neutral-Point-Clamped Converters

This letter derives and discusses the superiority of a simple dc-link capacitor voltage control configuration for multilevel neutral-point-clamped converters with any number of levels. The control involves n − 2 control loops regulating the difference between the voltage of neighbor capacitors. These control loops are inherently decoupled, i.e., they are independent and the control action of one loop does not affect the others. This method is proven to be equivalent to previously published approaches, with the added advantages of increased simplicity and scalability to a higher number of levels, all while imposing a lower computational burden. The good performance of such control is confirmed through simulations and experiments.

Modal–based uncertainty quantification for deterministically estimated structural parameters in low-fidelity model updating of complex connections

Modeling complex joints in structures entails significant time and effort, necessitating simplifications. Epistemic uncertainties arising from low-fidelity modeling can be quantified through probabilistic model updating. However, finding a surrogate physical model to represent simplified joint configurations poses challenges. Additionally, establishing a Bayesian formulation capable of incorporating structural parameters of connections is necessary. This study employs a validated simplifying parameterization approach for surrogate modeling of complex semi-rigid connections in a benchmark laboratory steel grid. It proposes a modal probabilistic Bayesian methodology to quantify uncertainties in the structure's joints. Three modal-based objective functions are utilized for finite element model updating. The modal properties of the structure are extracted by experimental modal analysis during an impact test, which will be utilized in the model updating process. Deterministic and probabilistic structural parameter estimations are integrated to enhance the robustness of the Bayesian technique. Furthermore, a guideline for selecting optimal hyperparameters is provided. Results demonstrate that utilizing deterministically estimated parameters as prior knowledge can facilitate and improve modal probabilistic model updating for structures with complex joints. Also, it is found that despite significant simplifications of joints, structural parameter tolerance around the maximum a posteriori estimate in surrogate models remains low.

Close roof-mounted system temperature estimation for compliance to IEC TS 63126

When photovoltaic (PV) modules are installed on rooftops, the module temperature depends primarily on the geographic location and the mounting configuration. If the mounting structure does not provide sufficient airflow in a hot environment, the 98th percentile temperature will exceed 70 °C, which according to IEC TS 63126 ED. 1, requires higher levels of thermal stability testing. However, there is no clear way to determine the temperature level needed for a particular location and system design. In this work, we identify a relationship between the module standoff to the rooftop and the module temperature and propose methods to describe a minimum standoff for typical PV modules in a simple mounting configuration installed in a given location. For more complex system designs, we show how to determine an equivalent “effective standoff” that can be applied to generic calculations. Lastly, we show measurements and calculations from several systems to demonstrate how this method could work.

The “Magnificent Seven” X-Ray Isolated Neutron Stars Revisited. I. Improved Timing Solutions and Pulse Profile Analysis

We present the first systematic X-ray pulse timing analysis of the six members of the so-called “Magnificent Seven” nearby thermally emitting isolated neutron stars (XINS) with detected pulsations. Using the extensive collection of archival XMM-Newton, Chandra, and NICER observations spanning over two decades, we obtain the first firm measurement of the spin-down rate for RX J2143.0+0654, while for the rest we improve upon previously published spin ephemerides and extend them by up to an additional decade. Five of the XINS follow steady spin-down with no indication of major anomalies in their long-term timing behavior; the notable exception is RX J0720.4−3125, for which, in addition to confirming the previously identified glitch, we detect a second spin derivative. The high-quality folded X-ray pulse profiles produced with the updated timing solutions exhibit diverse and complex morphologies, as well as striking energy dependence. These peculiarities cannot be readily explained by blackbody-like isotropic emission and simple hot-spot configurations, hinting at the presence of complex multitemperature surface heat distributions and highly anisotropic radiation patterns, such as may arise from a strongly magnetized atmospheric layer.