Device Components Research Articles

Hydrogen-assisted recycling of Nd-Fe-B magnets from the end-of-life audio products

The transition towards green and sustainable technologies has significantly increased the demand for a subset of raw materials known as critical elements. Rare earth elements with their main use in Neodymium-Iron-Boron magnets (NdFeB) play a key role in clean energy technologies including electric vehicles and wind turbine generators. They are also a key component in electronic devices including mobile phones, hard disk drives, and loudspeakers. Here, we build on previous knowledge of the recycling of NdFeB magnets from hard disk drives, using a hydrogen process called HPMS (Hydrogen Processing of Magnet Scrap). This study investigates a new scrap stream from loudspeakers, specifically from vehicles and flat-screen TVs. The extracted magnets from loudspeakers typically had grades of N30/N33 with relatively low coercivity values. The interactions of the extracted magnets with hydrogen were monitored by gravimetric and thermal analyses. The thermodynamics and kinetics of the hydrogenation reaction appear to differ significantly based on their chemical composition, chemical homogeneity, coating state, and surface condition of the magnets. Overall, the HPMS process was demonstrated to successfully produce demagnetised hydrogen decrepitated powder at room temperature under 2 bar of hydrogen, in a commercially viable timeframe (approx. 4 h). Zinc was found to be the dominant coating material which peeled away during the HPMS process. The zinc content of the NdFeB alloy powder could be reduced after the hydrogen decrepitation by sieving. The remaining level of zinc had no noticeable impact on the magnetic properties of the recycled magnets. The particle size of the recycled alloy powder could be reduced to below 7 µm by ball milling and knife milling but with an increase in the oxygen level, limiting its sintering ability. Sintered magnet from the recycled alloy powder demonstrated similar magnetic properties (Br: 1.06 T, HcJ: 1240 kA/m, and (BH)max: 220 kJ/m3) after blending with 5 wt% of NdH3, making vehicles and flat-screen TV speakers ideal sources for a recycled magnet.

Investigating the impact of band gap engineering on optoelectronic properties of tetragonal MgZrN[formula omitted] compound: A first principles study

Ternary nitrides, which consist of two metal cations and a nitrogen anion, exhibit considerable potential as innovative semiconducting materials due to their efficient conductivities and large melting temperatures. This study represents a pioneering investigation that employs density functional theory (DFT) calculations, utilizing the CASTEP code, to examine the influence of bi-axial strain on the semiconductor MgZrN2, which possesses a rocksalt tetragonal crystal structure. The primary objective is to analyze the variations in the structural and optoelectronic properties resulting from this strain. The material’s optoelectronic characteristics undergo notable changes when subjected to bi-axial strain. Indeed, when subjected to bi-axial ranging from −4% to +4%, the band gap also experiences a noticeable variation towards lower energy levels. Based on computational analysis, it has been determined that MgZrN2, a material deprived of magnetic properties, exhibits a direct band gap. To figure out the nature of bonding among the atoms in the material under discussion, Mulliken analysis and bulk electron density difference (EDD) are done as well. Mulliken analysis and EDD reveal that the ZrN bond in MgZrN2 is covalent, whereas the MgN bond is ionic. The optical absorbance of the material may be manipulated within the visible and ultraviolet spectra, and it also demonstrates a disordered nature. The compound’s optical properties indicate its suitability for implementation into components of devices designed for operation within the visible or ultraviolet (UV) parts of the electromagnetic spectrum. Furthermore, to determine the material’s suitability for solar cell applications, we compute the Spectroscopic Limited Maximum Efficiency (SLME) at bi-axial strains of −4%, 0%, and 4%. The SLME value reaches its maximum at +4% strain, equivalent to 18.7%. Undoubtedly, MgZrN2 possesses considerable potential for a wide range of solar cell applications.

Synthesis of Ultrawide Band Gap TeO2 Nanoparticles by Pulsed Laser Ablation in Liquids: Top Ablation versus Bottom Ablation.

Ultrawide band gap (UWBG) semiconductors are the future components of electronic devices due to their large energy band gap (>3.2 eV). In this article, spherical TeO2 nanoparticles, with sizes around ∼39 ± 12 and ∼29 ± 6 nm, were successfully synthesized by irradiating a pure tellurium target, totally submerged in ethanol, using a "Top-ablation" or "Bottom-ablation" synthesis protocol, respectively. Mostly, α-TeO2 nanoparticles were created (>95%) with only a small amount of γ-TeO2 nanoparticles being produced (<5%). Both colloids exhibited a ζ-potential larger than |30 mV|, indicating a stable colloidal solution. The energy band gaps of the TeO2 nanoparticles synthesized by the Top-ablation and Bottom-ablation synthesis protocols were determined to be around 5.3 and 5.8 eV, respectively. Finally, TeO2 UWBG nanoparticles were successfully synthesized using either a Top-ablation or Bottom-ablation synthesis protocol. The main advantage of the Bottom-ablation synthesis protocol is its ability to obtain smaller nanoparticles compared to that of the Top-ablation synthesis protocol.

A Numerical Analysis Based Internet of Things (IOT) and Big Data Analytics to Minimize Energy Consumption in Smart Buildings

The new wave of performant technology devices generates massive amounts of data. These devices are used in cities, homes, buildings, companies, and more. One of the reasons for digitalizing their tasks is that over the past few years, there has been an interest in reducing carbon emissions and increasing energy efficiency to create a friendly ecosystem and protect nature. One of which granted the explosion of data. After deploying these new devices, a significant increase in the use of the other face of energy to implement the components of the new devices was noticed. Above all, the interconnection of these intelligent devices is the central concept of the Internet of Things (IoT). This domain has widened the possibilities for the interconnection of building management systems (also named Smart Grids) and devices for better energy management. Furthermore, its potential is realized only after organizing and analyzing a large amount of data. Real-time management and maintenance of big data are critical to improving energy management in buildings. The benefits of big data analytics go beyond savings on electricity bills. It can provide comfort for building users and extend the life of building equipment, enhancing the value of commercial buildings. Intelligent interconnection of a building’s technical installations (lighting, heating, hot water, photovoltaic installations, etc.) not only allows for connected management of this equipment but also meets high energy efficiency criteria that indicate an increase in comfort and energy savings. With building automation, the technical installations of a building interact optimally. In this article, we will simulate an intelligent building based on the Cisco packet tracer software. To better manage the energy consumption of our project, we will focus on the processing of data in real-time, especially since we will have a massive amount of data generated by the sensors.

Supercritical CO2-Assisted Electroless Plating of Ultrahigh-Molecular-Weight Polyethylene Filaments for Weavable Device Application

This study reports on the use of supercritical CO2 (scCO2) for the metallization of ultrahigh-molecular-weight polyethylene (UHMW-PE) filaments, which are used as functional components in weavable devices. UHMW-PE is well known for its chemical and impact resistance, making it suitable for use in bulletproof clothing and shields. However, its chemical resistance poses a challenge for metallization. By utilizing scCO2 as the solvent in the catalyzation process, a uniform and defect-free layer of Ni-P is successfully deposited on the UHMW-PE filaments. The deposition rate of Ni-P is enhanced at higher temperatures during the scCO2 catalyzation. Importantly, the durability of the Ni-P-metalized UHMW-PE filaments is improved when the scCO2 catalyzation is carried out at 120 °C, as evidenced by minimal changes in electrical resistivity after a rolling test.

Research and application progress of electrochemical water softening technology in China

The issues of scaling, pipeline corrosion, and the growth of sludge, bacteria, and algae within circulating cooling water systems have been consistently limiting the enhancement of production efficiency in enterprises. The trending new electrochemical water softening technology, with its environmentally friendly, high efficiency, and low energy consumption characteristics, offers a fresh approach to addressing the stable operation of industrial circulating water systems. This paper begins by detailing the mechanisms of active scale removal, sterilization, and algae control facilitated by electrochemical water softening technology. Subsequently, it compares and analyzes the crucial core components of electrochemical devices (including the selection and preparation of anode and cathode materials, as well as the power system). Furthermore, it introduces the main types and installation modes of electrochemical equipment available in the market. Additionally, it uncovers the key factors influencing the efficiency of electrochemical descaling and validates the impact of electrochemical water softening technology on industrial circulating water systems through illustrative examples. Lastly, the paper concludes by summarizing and forecasting the future development direction of this technology.

Eco-Friendly Processing of Wool and Sustainable Valorization of This Natural Bioresource

The environmental invasion of plastic waste leads to, among other things, a reassessment of natural fibers. Environmental pollution has shown the importance of the degradability, among other properties, of the raw materials used by the textile industry or other industrial fields. Wool seems to be a better raw material than the polymers that generate large quantities of micro- and nano-plastics, polluting the soil, water, and air. However, the usual processing of raw wool involves a number of chemically very polluting treatments. Thus, sustainable procedures for making wool processing environmentally friendly have been considered, leading to the reappraisal of wool as a suitable raw material. Besides their applications for textile products (including smart textiles), new directions for the valorization of this natural material have been developed. According to the recent literature, wool may be successfully used as a thermal and phonic insulator, fertilizer, or component for industrial devices, or in medical applications, etc. In addition, the wool protein α-keratin may be extracted and used for new biomaterials with many practical applications in various fields. This review makes a survey of the recent data in the literature concerning wool production, processing, and applications, emphasizing the environmental aspects and pointing to solutions generating sustainable development.

Oxidation-resistant self-adhesive flexible transparent electrodes based on Ag–Au core-shell nanowires and heterogeneous microarchitectures

Flexible transparent electrodes (FTEs) are essential for advancing flexible electronics, energy systems, and biomedical devices. Conventional FTEs, which use silver nanowire coatings on flexible substrates, face limitations due to poor oxidation resistance and difficulties in forming reliable mechanical and electrical interconnections with other device components. In this study, we propose a versatile FTE design that integrates Ag–Au core-shell nanowires and self-adhesive microstructures into a regular grid pattern. This electrode exhibits robust self-adhesion, enabling precise mechanical and electrical contacts across various substrates without additional adhesives. The optical and electrical properties can be finely tuned by manipulating the microstructures and nanowire coatings. Notably, the electrode demonstrates remarkable oxidation resistance, even under exposure to oxidizing agents, elevated temperatures, and high-humidity environments. Our findings provide practical pathways for implementing FTEs in a wide range of emerging optoelectronic devices, leveraging their exceptional chemical and thermal stability.

Concentration of Microparticles/Cells Based on an Ultra-Fast Centrifuge Virtual Tunnel Driven by a Novel Lamb Wave Resonator Array.

The µTAS/LOC, a highly integrated microsystem, consolidates multiple bioanalytical functions within a single chip, enhancing efficiency and precision in bioanalysis and biomedical operations. Microfluidic centrifugation, a key component of LOC devices, enables rapid capture and enrichment of tiny objects in samples, improving sensitivity and accuracy of detection and diagnosis. However, microfluidic systems face challenges due to viscosity dominance and difficulty in vortex formation. Acoustic-based centrifugation, particularly those using surface acoustic waves (SAWs), have shown promise in applications such as particle concentration, separation, and droplet mixing. However, challenges include accurate droplet placement, energy loss from off-axis positioning, and limited energy transfer from low-frequency SAW resonators, restricting centrifugal speed and sample volume. In this work, we introduce a novel ring array composed of eight Lamb wave resonators (LWRs), forming an Ultra-Fast Centrifuge Tunnel (UFCT) in a microfluidic system. The UFCT eliminates secondary vortices, concentrating energy in the main vortex and maximizing acoustic-to-streaming energy conversion. It enables ultra-fast centrifugation with a larger liquid capacity (50 μL), reduced power usage (50 mW) that is one order of magnitude smaller than existing devices, and greater linear speed (62 mm/s), surpassing the limitations of prior methods. We demonstrate successful high-fold enrichment of 2 μm and 10 μm particles and explore the UFCT's potential in tissue engineering by encapsulating cells in a hydrogel-based micro-organ with a ring structure, which is of great significance for building more complex manipulation platforms for particles and cells in a bio-compatible and contactless manner.

Electrostatically controlled spin polarization in Graphene-CrSBr magnetic proximity heterostructures

The magnetic proximity effect can induce a spin dependent exchange shift in the band structure of graphene. This produces a magnetization and a spin polarization of the electron/hole carriers in this material, paving the way for its use as an active component in spintronics devices. The electrostatic control of this spin polarization in graphene has however never been demonstrated so far. We show that interfacing graphene with the van der Waals antiferromagnet CrSBr results in an unconventional manifestation of the quantum Hall effect, which can be attributed to the presence of counterflowing spin-polarized edge channels originating from the spin-dependent exchange shift in graphene. We extract an exchange shift ranging from 27 – 32 meV, and show that it also produces an electrostatically tunable spin polarization of the electron/hole carriers in graphene ranging from − 50% to + 69% in the absence of a magnetic field. This proof of principle provides a starting point for the use of graphene as an electrostatically tunable source of spin current and could allow this system to generate a large magnetoresistance in gate tunable spin valve devices.

Performance Optimization and Experimental Study of Small-Scale Potato-Grading Device

Traditional potato grading in China relies mostly on manual sorting, which is labor-intensive, time-consuming, costly, and inefficient. To enhance the operational performance of potato-grading devices, this paper focuses on optimizing the slide rail structure, which is the key component of a self-developed first-generation potato-grading device. A five-factor, three-level orthogonal experiment was designed, with the experimental factors being the height of the horizontal slide rail, angle of the first-stage inclined slide, angle of the second-stage inclined rail, chain horizontal movement speed, and conveyor belt speed. The indoor experiments were conducted using grading accuracy and grading efficiency as the experimental indicators. On the basis of the analysis of the orthogonal experiment results, two relatively optimal solutions were obtained, and validation experiments were conducted. The validation results show that when the height of the horizontal slide rail was 185 mm, the angle of the first-stage inclined rail was 4°, the angle of the second-stage inclined rail was 2.5°, the horizontal movement speed of the chain was 700 mm/s, and the movement speed of the conveyor belt was 275.60 mm/s, the performance of the movable rotating plate (MRP)-type grading device for potatoes reached its optimum. At this point, the grading accuracy was 94.88%, and the grading efficiency was 13.9477 t/h. Compared with the first-generation grading device, the optimized grading device achieved an improvement of 3.84% in grading accuracy and 12.94% in grading efficiency. The research methodology provided in this paper serves as a reference for the performance optimization of potato-grading devices.

An object detection method for catenary component images based on improved Faster R-CNN

Catenary components are an important part of electrified railways. Especially for catenary support devices, there are various types of components with significant differences in scale. According to statistical data, there is a high risk of failure for the catenary support device components during the operation of the catenary system. Therefore, in order to ensure the safe operation of the railways, it is critical to accurately locate and recognize the components in the catenary images. In this paper, we propose an improved method based on faster region-based convolutional neural networks (Faster R-CNN) framework to realize the detection and extraction of the components on the catenary support devices. Firstly, the anchor box parameters are reset using the K-means clustering method, which greatly improves the localization precision of the predicted box. Secondly, scaled exponential linear units activation function is introduced to improve the algorithm performance. Moreover, ResNet-34, the backbone of Faster R-CNN, is optimized. We design a transition structure for multi-scale filter combination convolution to avoid missing feature information and eliminate some redundant convolution structures. This modification substantially enhances the capability of the model to recognize a wide variety of component types. Finally, we conduct some control experiments comparing with single shot multibox detector and you only look once (YOLO) series (YOLOv3, YOLOv5 and YOLOv7) models. They are faster but less accurate, especially for small objects. The results show that the proposed method has better detection performance, achieving a mean average precision of 96.50% and running at 17.79 frames per second. In addition, our model has the highest average recall of 69.27%, which is 2.66% higher than the original model.

A novel calibration method for portable X-ray fluorescence analysis of printed circuit boards.

Printed circuit boards (PCBs) are the most complex and valuable component of electronic devices, but only 34% of them are recycled in an environmentally sound manner. Improving the recycling rate and efficiency requires a fast, reliable and uncostly analytical method. Although the X-ray fluorescence (XRF) shows high potential, it is often unreliable. In this study, we propose a novel XRF methodology for the elemental analysis of PCBs, using the certified reference material (CRM) to decrease uncertainty and enhance accuracy. The results show significant improvement in robustness and accuracy of portable XRF(pXRF) analyses for elements Cu, Pb, Ni, As and Au, with a relative average inaccuracy of approximately 5% compared to referenced values. The methodology validation carried out by comparing pXRF and inductively coupled plasma mass spectroscopy analyses of personal computer motherboard samples shows no statistically significant difference for elements Cu, Cr and Ag. The study shows that the calibration of pXRF by CRMs enables the necessary analysis of PCBs in an efficient and reliable manner and could be also be applied to different types of PCBs and other electronic components, batteries or contaminated soil samples.

Using Quality Function Deployment to Assess the Efficiency of Mini-Channel Heat Exchangers

This article addresses the design of a compact heat exchanger for the cooling of electronic systems. The Quality Function Deployment (QFD) method is used to identify crucial product features to improve device performance and key customer requirements. The QFD simplifies management processes, allowing modifications to device components, such as design parameters (dimensions and materials) and operating conditions (flow type and preferred temperature range). The study was applied to analyse the fundamental features of a compact heat exchanger, assessing their impact on enhancing heat transfer intensity during fluid flow through mini-channels. The thermal efficiency of the compact heat exchanger was tested experimentally. The results allow to verify the results obtained from the numerical simulations due to Simcenter STAR-CCM+. Consequently, the experimental part was reduced in favour of numerical simulations conducted using this commercial CFD software version 2020.2.1 Build 15.04.01. The numerical simulations performed with the aid of CFD showed increases in the heat transfer coefficient of up to 180% compared to the case treated as a reference. The application of the QFD matrix significantly reduces the time required to develop suitable design and material solutions and determine the operating parameters for the cooling of miniature electronic devices.

PPG-Hear: A Practical Eavesdropping Attack with Photoplethysmography Sensors

Photoplethysmography (PPG) sensors have become integral components of wearable and portable health devices in the current technological landscape. These sensors offer easy access to heart rate and blood oxygenation, facilitating continuous long-term health monitoring in clinic and non-clinic environments. While people understand that health-related information provided by PPG is private, no existing research has demonstrated that PPG sensors are dangerous devices capable of obtaining sensitive information other than health-related data. This work introduces PPG-Hear, a novel side-channel attack that exploits PPG sensors to intercept nearby audio information covertly. Specifically, PPG-Hear exploits low-frequency PPG measurements to discern and reconstruct human speech emitted from proximate speakers. This technology allows attackers to eavesdrop on sensitive conversations (e.g., audio passwords, business decisions, or intellectual properties) without being noticed. To achieve this non-trivial attack on commodity PPG-enabled devices, we employ differentiation and filtering techniques to mitigate the impact of temperature drift and user-specific gestures. We develop the first PPG-based speech reconstructor, which can identify speech patterns in the PPG spectrogram and establish the correlation between PPG and speech spectrograms. By integrating a MiniRocket-based classifier with a PixelGAN model, PPG-Hear can reconstruct human speech using low-sampling-rate PPG measurements. Through an array of real-world experiments, encompassing common eavesdropping scenarios such as surrounding speakers and the device's own speakers, we show that PPG-Hear can achieve remarkable accuracy of 90% for recognizing human speech, surpassing the current state-of-the-art side-channel eavesdropping attacks using motion sensors operating at equivalent sampling rates (i.e., 50Hz to 500Hz).

Ternary systems engineered conductive hydrogel with extraordinary strength, environmental adaptability and excellent electrochemical performances for flexible power supply devices

The easy failure, poor environmental adaptability and unsatisfactory electrochemical performances of hydrogels hinder their applications as key components of flexible power supply devices (PSDs). Herein, a PAA-based hydrogel with extraordinary strength and environmental adaptability is designed via a ternary system, consisting of the tannin-modified MXene (TA@MXene), ZnCl2-cellulose and malic acid (MA) electrolyte. The TA@MXene and ZnCl2-cellulose promote the crosslinking of hydrogel via forming multi networks, endowing the hydrogel with 1.9 MPa tensile strength and 620 % stretchability. Furthermore, the hydrogel has 38.4 mS·cm−1 conductivity, thanks to the effective ion transfer channels in the hydrogel. The MA electrolyte provides a stable pH environment via forming an acid ionization system; also, MA and the high-concentration ZnCl2 solution enhance their electrochemical performance at extreme environments. Three typical PSDs were assembled using the resultant hydrogel as electrolyte/electrode. The as-prepared supercapacitors display a high specific capacity (173.5 mAh·g−1), a superior energy density (208.2 Wh·kg−1) and outstanding capacity retention (92.1 % after 5000 cycles); flexible batteries efficiently respond to strain signals, with 0.77 V open-circuit voltage (Voc); the as-assembled TENG has a 110 V Voc (100 % stretching deformation). We present a design strategy for the construction of advanced hydrogels based a ternary system that will promote flexible PSDs towards practical use.

Overshoot‐Suppressed Memristor Array with AlN Oxygen Barrier for Low‐Power Operation in the Intelligent Neuromorphic Systems

As the demand for bio‐inspired neuromorphic systems grows, memristor has emerged as a pivotal component in artificial synaptic devices. This study delves into the advantages and limitations of the one‐transistor‐one‐resistor (1T‐1R) and 0T‐1R architectures for memory array configurations. A significant enhancement in the memristor's on/off ratio, surpassing 103, achieved by integrating both an overshoot suppression layer (OSL) and an ultra‐thin AlN oxygen barrier layer (OBL) is also reported. The concurrent insertion of an AlOx OSL is essential for manifesting the self‐compliance attribute in 4F2 memristor arrays. Evaluations of a 24 × 24 array embedded with OSL and OBL reveal a substantial reduction in retention variation. In terms of functionality, a 7.13‐fold decline in vector‐matrix multiplication error is observed, accentuating the potential of this approach for neural network synapse applications. The analog reset characteristics of the OBL memristor facilitate over 25 multilevel states. Furthermore, the adoption of nonnegative weights presents an avenue to potentially double synaptic integration density. Through simulation program with integrated circuit emphasis simulations, the necessity of nonnegative and 16‐level quantized conductance in balancing power consumption without accuracy loss at the image classification is validated.

Cross-sectional geometry effect on bending strength of gold micro-cantilever with trapezoidal cross-section

Gold is a promising material for movable components in MEMS devices by the high mass density, which allows reduction of the Brownian noise. Mechanical properties of metallic materials are known to be affected by the sample size effect. When bending test is utilized, the sample geometry effect is another factor. In this study, effects of the shape of the cross-section, or the cross-sectional geometry effect, are evaluated using micro-cantilevers with a trapezoidal cross-section. The yield stresses are ranged from 112 MPa to 185 MPa in micro-cantilevers composed of single crystalline gold, and the yield stresses varied from 372 MPa to 489 MPa in polycrystalline gold micro-cantilevers. The yield stress is found to be higher in the micro-cantilever having a smaller ratio of the top width over the bottom width, which demonstrates the cross-sectional geometry effect. Also, the cross-sectional geometry effect is more significant in the polycrystalline micro-cantilevers.

Highest fusion performance without harmful edge energy bursts in tokamak

The path of tokamak fusion and International thermonuclear experimental reactor (ITER) is maintaining high-performance plasma to produce sufficient fusion power. This effort is hindered by the transient energy burst arising from the instabilities at the boundary of plasmas. Conventional 3D magnetic perturbations used to suppress these instabilities often degrade fusion performance and increase the risk of other instabilities. This study presents an innovative 3D field optimization approach that leverages machine learning and real-time adaptability to overcome these challenges. Implemented in the DIII-D and KSTAR tokamaks, this method has consistently achieved reactor-relevant core confinement and the highest fusion performance without triggering damaging bursts. This is enabled by advances in the physics understanding of self-organized transport in the plasma edge and machine learning techniques to optimize the 3D field spectrum. The success of automated, real-time adaptive control of such complex systems paves the way for maximizing fusion efficiency in ITER and beyond while minimizing damage to device components.

Advancements in printed components for proton exchange membrane fuel cells: A comprehensive review

Proton Exchange Membranes (PEM) are a promising technology for fuel cells and electrolyzer cells, in line with societal goals for clean and sustainable fuel conversion and generation, respectively, in a vast field of applications. PEM fuel cell (PEMFC) technology has an important advantage for energy conversion applications, because it requires a lower operating temperature and is lighter and more compact than other technologies, which makes it ideal for portable and transportation applications. However, open issues remain to be addressed for PEMFC that hinder their widespread adoption, both on the technical side, such as too high operational temperature range, cell efficiency, and long-term stability, as well as on the industrial side with implementation issues, material and device component availability, and cost. PEM technology research usually focuses on the synthesis of novel materials such as non-noble metal catalysts and non-halogenated membranes. In parallel, developing high-throughput and cost-effective manufacturing methods for components, in particular Membrane Electrode Assembly (MEA), can also lift an important barrier to their mass production, thus contributing to the same goals and securing industrial provision. From this perspective, printing technologies such as spray coating, inkjet printing, and screen printing have emerged as promising approaches with the required precision and scalability. This review covers recent advancements and developments in advanced PEMFC technology manufacturing, with a focus on 2D printing methodologies to fabricate some or all of the MEA components. Leveraging these techniques as simplified large-area manufacturing methods for PEM technology can become a more viable and industrially attractive solution. This work presents a comparison study addressing the key progress indicators both in process and in characterization to build a working framework in which both scientists, engineers and manufacturers can collaborate toward the industrial implementation of this emergent field.