The metal organic framework (MOF) MIP-177(Ti) is under the spotlight for its robust photo-response and stability. This MOF can be synthesized in forms: MIP-177(Ti)-LT (LT: low temperature) and MIP-177(Ti)-HT (HT: high temperature). The MIP-177(Ti)-LT version comprises of Ti₁₂O₁₅ units interconnected by 3,3′,5,5′-tetracarboxydiphenylmethane (mdip) ligands and interconnecting formate groups. Upon high temperature treatment, MIP-177(Ti)-LT loses its formate groups, thus rearranging into a continuous 1-D chain of Ti₆O₉ units leading to the MIP-177(Ti)-HT. Based on this 1-D connected structure, one should expect a higher catalytic activity of MIP-177(Ti)-HT. Nevertheless, the hydrogen evolution reaction photoactivity assessment clearly indicates the opposite. Combining transient IR measurements (TRIR), TAS and DFT/TD-DFPT calculations unveils the reasons for this situation. The TRIR measurements evidence that the photoinduced electrons are located in the inorganic part, while the holes are in the mdip ligand. The longer lifetime of MIP-177(Ti)-LT is mapped onto a slower decay of the Ti–O related peaks. A reversible change in the coordination of the carboxylate groups from a bidentate to a monodentate coordination is observed only in MIP-177(Ti)-LT. Complementary DFT and TD-DFPT simulations demonstrate a higher electron delocalization on the inorganic part for MIP-177(Ti)-LT (hence, enhanced mobility and slower recombination), thus explaining its superior photocatalytic activity.

The increasing global energy demand necessitates the development of sustainable electrochemical energy technologies. Anion-exchange membrane fuel cells (AEMFCs) present a promising alternative to proton-exchange membrane fuel cells (PEMFCs) due to their ability to utilize platinum-group metal (PGM)-free catalysts, which significantly reduce costs and resource dependency. In this work, we prepare various PGM-free catalysts for the oxygen reduction reaction (ORR) via an ionothermal synthesis using cyclodextrin and magnesium nitrate. The synthesis conditions were optimized and the electrocatalysts were investigated with both physical and electrochemical characterization techniques. The catalysts’ ORR performance was assessed using rotating disk electrode (RDE) measurements and single-cell AEMFC tests. The optimized FeNC-CD3 catalyst exhibited a half-wave potential of 0.90 V vs RHE in 0.1 M KOH in the RDE test and a peak power density of 599 mW cm⁻² in an AEMFC, showcasing its potential as a viable alternative to conventional Pt-based cathode catalysts. This work highlights the critical role of hierarchical porosity in enhancing the ORR activity and paves the way for the development of cost-effective and efficient AEMFC technology.

The growth of ultrathin layers of oxides by atomic layer deposition (ALD) is well documented for oxide substrates such as SiO₂, Bi₂O₃, Al₂O₃, in which oxygen is the only negatively charged atom. In contrast, the knowledge regarding ALD growth on substrates containing other negatively charged atoms, such as halogens, is quite limited. The commonly used bismuth oxyhalide (BiOX) family of materials are characterised by a low density of surface hydroxyls, required for the initiation of thermal ALD growth of oxides, thus hampering the ability to grow ultrathin layers of oxides on their surface. This restriction becomes even more severe if the process has to be performed at low temperatures. In this work, we show that high quality Al₂O₃ can be grown on bismuth oxyhalide materials by low temperature ALD, upon performing UV-ozone surface pretreatment. The effect of pretreatment on the BiOX photocatalysts was studied by wettability measurements and FTIR. The coating conformality was monitored by both XPS and via the ability of the ultrathin layers to suppress the photocatalytic activity of the substrates. The capability to form dense, conformal aluminium oxide layers on BiOX substrates opens a door for low-temperature preparation of organic–inorganic hybrid devices on such and similar compounds.

This study investigates the hypothesis that modified shellac nanoparticles (NPs) can effectively stabilize Pickering emulsions. Shellac, a natural polyester resin derived from the secretion of insects, was chemically modified using Jeffamine® M600 and Jeffamine® ED2003 to produce two NP types: Sh-M600 and Sh-ED2003, with sizes ranging from 127 to 183 nm. These NPs were used to stabilize oil-in-water emulsions with isopropyl myristate (IPM). Stability tests revealed that Sh-M600-stabzlized emulsions (up to 40 % oil) remained stable for 6 months, while Sh-ED2003-stabilized emulsions were stable with up to 65 % oil content, even under accelerated conditions. Cryo-SEM imaging confirmed NP accumulation at the oil-water interface, corroborated by reduced interfacial tension in the presence of NP. Adsorption energy calculations demonstrated the superior stabilization capacity of Sh-ED2003 NPs over Sh-M600 NPs. Rheological analysis further supported these findings, showing consistently higher viscosity viscosities for Sh-ED2003-stabilized emulsions across all oil percentages, attributed to the higher molecular weight of its modifier. Collectively, this study demonstrates the effectiveness of tailored shellac NPs in stabilizing robust emulsions, offering potential applications in food, pharmaceuticals, and agriculture.

This paper describes the first implementation of a flipped, one-week workshop on heat integration that was taught in Spring 2024 to the 3rd Year cohort of 138 students in Chemical Engineering at Imperial College, London. The “flipped” workshop consisted of three online lessons that cover the core materials on pinch design of heat exchanger networks, which the students were required to complete ahead of each of the corresponding three face-to-face class meetings, which focused on problem-solving exercises largely carried out by the students themselves. The paper describes the teaching methodology applied, presents and analyses the results of a survey conducted to assess the students’ perceptions and degree of satisfaction with the workshop. Learning outcomes relevant to the workshop topic, that is, the ability to design and optimize heat exchanger networks in realistic plant-wide settings, are also presented and compared to those of previous years. The main conclusion is that the short workshop format can successfully achieve the learning objectives, even for relatively large class sizes. Evidently, this workshop can be taught effectively in this concentrated form provided that the workshop participants are given access to the online lessons in advance of the class exercises.

The resistance of polymers to solvents is a critical property for their integration into applications such as medical devices, energy storage, and membranes. Sequential infiltration synthesis (SIS) is a promising technique for enhancing the chemical stability of polymers, minimizing their solvent dissolution, through vapor phase-based growth of inorganic materials within the polymers. SIS is effective in polymers with functional groups that are reactive with SIS precursors, such as polymethylmethacrylate (PMMA), but is ineffective in polymers that lack reactive groups, such as polystyrene (PS). By combining these two materials as a random copolymer (P(S-r-MMA)), polystyrene-based materials may be modified with SIS according to the functional group density, which scales with methacrylate (MMA) concentration. Herein, we use various compositions of random copolymers to explore how solvent resistance is affected by SIS cycles and functional group density. A series of P(S-r-MMA) samples were modified with one or five SIS cycles using trimethylaluminum and water, then exposed to liquid and vapor toluene environments. Changes to film mass and appearance were monitored with a quartz crystal microbalance (QCM), infrared spectroscopy, and optical microscopy. We found that a single SIS cycle led to mass and thickness retention as high as ∼70% with increasing MMA content, indicating the presence of inorganic crosslinks. With five SIS cycles, films with as little as ~10% MMA and above it had near complete thickness retention, in agreement with lower growth rates in a high number of cycles, evidenced by in situ QCM measurements. This demonstrates the role of diffusion barriers in SIS processes. Thus, a combination of crosslinking and transport resistance led to tunable solvent resistance according to the number of SIS cycles and the MMA content of the copolymer.

Atomic layer deposition (ALD) is a versatile technique for engineering the surfaces of porous polymers, imbuing the flexible, high-surface-area substrates with inorganic and hybrid material properties. Previously reported enhancements include fouling resistance, electrical conductance, thermal stability, photocatalytic activity, hydrophilicity, and oleophilicity. However, there are many poorly understood phenomena that introduce challenges in applying ALD to porous polymers. In this paper, we address five common challenges and ways to overcome them: (1) entrapped precursor, (2) embrittlement, (3) film fracture, (4) deformation, and (5) pore collapse. These challenges are often interrelated and can exacerbate one another. To investigate these phenomena, we applied various ALD chemistries to porous polymers including polyethersulfone, polysulfone, polyvinylidene fluoride, and polycarbonate track-etched membranes. Reaction-diffusion modeling revealed why certain precursors and processing conditions result in embrittling subsurface material growth, entrapment of unreacted precursors, and nongrowth. We quantify the limits of ALD processing temperatures that are dictated by thermal expansion mismatch and can lead to fractured ALD films. The results herein allow us to make recommendations to avoid, mitigate, or overcome the difficulties encountered when performing ALD and plasma-enhanced ALD on porous polymers. We intend this article to serve as a “lessons learned” guide informed by previous experience to provide a better understanding of the difficulties and limitations of ALD on porous polymers and knowledge-based guidelines for successful depositions. This knowledge can accelerate future research and help experimentalists navigate and troubleshoot as they expose porous polymers to reactive precursor vapors.

Biomimetic nanoparticles (BNPs), which integrate biologically active materials such as cell membrane proteins, represent an emerging class of nanoparticles with therapeutic potential. However, the controlled release of these nanoparticles from hydrogels remains challenging due to their relatively large size compared to the hydrogel mesh size, which hinders diffusion. This research aimed to fabricate a dissolvable hydrogel platform incorporating novel BNPs for controlled release and to evaluate its therapeutic effects. Specifically, we developed a procedure for the fabrication of synergetic hydrogel using two soluble polysaccharides, namely konjac glucomannan (KGM) and kappa-carrageenan (KCAR), at low temperatures that preserve the BNPs' biological functionality. The physical, mechanical, and rheological properties of these hydrogels, as well as the controlled release of BNPs, were characterized. The results demonstrate the self-healing and shear-thinning properties of the hydrogels. Using potassium ions as a physical cross-linker improved the hydrogel's mechanical properties and allowed the tuning of the BNPs' release rate. Additionally, in vitro tests in an inflammation model showed that the BNPs containing hydrogel reduced tumor necrosis factor-alpha (TNF α) cytokine levels without significantly affecting cell viability. This novel hydrogel platform offers a promising approach for the tunable controlled release of BNPs, with potential applications for inflammation and other therapeutic models.

Breath analysis offers a non-invasive approach to modern diagnostics by capturing volatile organic compounds (VOCs) in exhaled breath. However, current breath analysis technologies face challenges like humidity sensitivity, high costs, and biodegradable solutions, limiting their scalability and environmental sustainability. This study presents a paper-based, biodegradable, humidity-insensitive electronic nose (e-nose) sensor array integrated into a face mask for real-time breath analysis. The sensors, coated with hydrophobic polymer coating, ensure robust insensitivity to humidity, enabling reliable detection of VOCs even in high-moisture environments. The mask-integrated e-nose facilitates real-time breath monitoring for applications such as alcohol consumption tracking and respiratory health assessment. For the latter, Tuberculosis (TB) detection is selected as a representative use case, achieving 89% accuracy in disease diagnosis and recovery monitoring using a pre-trained deep-learning model. The fully-biodegradable paper-based sensor naturally degrades in soil within months, underscoring its eco-friendly design and suitability for disposable health monitoring. This work introduces a sustainable, user-friendly approach to breath analysis with potential applications in non-invasive disease detection and personalized healthcare monitoring.

Interleukin-6 (IL-6) plays a pivotal role in the inflammatory response of diabetic wounds, providing critical insights for clinicians in the development of personalized treatment strategies. However, the low concentration of IL-6 in biological samples, coupled with the presence of numerous interfering substances, poses a significant challenge for its rapid and accurate detection. Herein, we present a dual-mode microfluidic platform integrating electrochemical (EC) and surface-enhanced Raman spectroscopy (SERS) to achieve the timely and highly reliable quantification of IL-6. Efficient binding between IL-6 and antibody-conjugated SERS nanoprobes is obtained through a square-wave micromixer with nonleaky obstacles, forming sandwich immunocomplexes with IL-6 capture antibodies on the working electrode in the detection area, enabling acquisition of both EC and SERS signals. This microfluidic platform demonstrates excellent selectivity and sensitivity, with detection limits of 0.085 and 0.047 pg/mL for EC and SERS modes, respectively. Importantly, by incorporating a neural network (NN) with a self-attention (SA) mechanism to evaluate the relative weights of data from both modes, the platform achieves a quantitative accuracy of up to 99.8% across a range of 0.05–1000 pg/mL, demonstrating significant performance at low concentrations. Moreover, the NN-enhanced dual-mode microfluidic platform effectively detects IL-6 in diabetic wound exudates with results that align closely with clinical data. This integrated dual-mode microfluidic platform offers promising potential for the rapid and accurate detection of cytokines.