Hyundai Motor Group (South Korea)

Abstract The use of plastics in the automotive industry is increasing due to their versatility, light weight and affordability. To improve their sustainability credentials, incorporation of recycled content is desired, driven by recent European Union mandates for 25% recycled content for automotive plastics. Current methods to quantify recycled content, however, are imprecise and could promote fraud. This paper extends a method to quantify recycled content in packaging plastics using a fluorescent brightener, 4,4′‐bis(2‐benzoxazolyl)stilbene (BBS), to automotive‐grade polymers. BBS aggregates above threshold concentrations to exhibit aggregation‐induced enhanced emission (AIEE). This study investigates whether fluorescence emission, lifetime and colour analyses can be used to quantify recycled content in four automotive plastics with different chemical structures, matrices or fillers. Quantification using BBS AIEE was most successful for semicrystalline polymers with minimal additives (polyamide‐6 and polyamide‐6,6), with high confidence correlations between fluorescence emission and lifetime measurements and recycled content. Detection was suppressed in amorphous polycarbonates and filled polypropylenes, suggesting this quantification technique may be application‐limited. These new insights into quantifying recycled content in automotive plastics point to both opportunities and limitations for fluorescence‐based techniques in assuring a more circular world. © 2026 The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The efficiency and economic feasibility of proton exchange membrane water electrolysis (PEMWE) for clean hydrogen production are closely linked to advancements in porous transport layer (PTL) technology. This work introduces an innovative triple-layer PTL designed to improve catalyst utilization, structural stability, and mass transport in PEMWE. By incorporating a strategically engineered graded porous structure and an ultra-high porosity backing layer, the triple-layer PTL enhances performance while being fabricated through a cost-effective process. Comprising a microporous layer (MPL), an interlayer, and a highly porous backing layer, the triple-layer design improves interfacial contact with the catalyst layer, as verified by digital twin analysis using X-ray microscope. The combination of a graded porous structure and an ultra-high porosity backing layer facilitates efficient oxygen transport, greatly increasing the availability of reactants at the reaction sites, as confirmed by numerical simulation. Electrochemical performance evaluation demonstrates that the triple-layer PTL significantly reduces overpotentials, thereby enhancing system efficiency and lowering costs, underscoring its potential as a viable solution for a sustainable future.

Abstract Optoelectronic synapses have attracted considerable attention for emulating biological visual perception by enabling the recognition of complex visual stimuli, including spatial patterns and multicolor information. Despite significant progress, the realization of multicolor classification with simple and scalable device architecture remains a fundamental challenge, requiring strategies that overcome the limitations of conventional device configurations. Here, a scalable van der Waals heterostructure device is presented that enables multicolor optoelectronic processing by vertically integrating solution‐processed molybdenum disulfide (MoS 2 ) as a light‐absorbing layer and single‐walled carbon nanotubes (SWCNTs) as a semiconducting channel. Unlike conventional complex architectures, such as serially connected synaptic devices and optical‐sensors, the approach employs an electronically disconnected but interactive MoS 2 layer to facilitate photon‐modulated carrier doping in the adjacent SWCNTs channel. This configuration enables bi‐directional photocurrent behavior under different wavelength illumination, essential for emulating the retina's chromatic adaptation while maintaining a structurally simple and scalable design. Leveraging this unique bi‐directional photoresponse, an optical neural network framework is integrated that independently processes distinct spectral information, enabling highly efficient multicolor pattern classification. This synergistic strategy is essential for realizing scalable optoelectronic synapses, as evidenced by a classification accuracy of 92.0%, offering a promising platform for next‐generation vision systems.