We present a simplified, thermodynamically consistent model of the phase separation of a binary fluid mixture under the effects of a conservative volume force that drives fluid flow. Enforcing conservation of mass provides advection–diffusion equations for the concentrations of the individual components. We propose Darcy-type laws for the velocity and flux of each component, that ensure a nonincreasing free energy functional consistent with the second law of thermodynamics in an isothermal setting. The model is closed by prescribing a free energy in accordance with the Cahn–Hilliard and Flory–Huggins theories. A linear stability analysis of the unforced model yields the range of initial concentrations for which instability occurs and the linear growth rate of perturbations, which are numerically confirmed. We provide fully nonlinear numerical solutions to the model in the specific case of a silicone oil–water mixture, where the conservative force is generated by gravity, or by a surface acoustic wave (SAW) propagating through the underlying substrate. In agreement with recent experimental results, we find that increasing the SAW amplitude or decreasing the SAW attenuation length speeds up total phase separation. This provides a proof-of-principle for modeling phase separation due to the effects of a SAW, within the limitations of our model.

Undetected in many patients, hypertrophic cardiomyopathy (HCM) is a widespread genetic heart disorder. Conventional diagnosis is based on physiological metrics such as blood pressure, imaging techniques, and genetic testing. Detection of HCM is crucial for proper follow-up, family screening, early treatment, and risk stratification to prevent sudden cardiac death. Therefore, there is an unmet need for fast and reliable diagnostic methods. This study introduces an innovative approach for the noninvasive, rapid, and accurate diagnosis of HCM by detecting patterns of volatile organic compounds (VOCs) in the patient's breath. Breath from 157 volunteers is collected on sorbent tubes and analyzed using a two-step approach, gas chromatography-mass spectrometry (GC-MS), and a developed nano-based sensor array. Initially, statistically significant differences in VOC patterns among sampled groups are identified using GC-MS. Then, the sensor array is used to differentiate between HCM patients and controls, resulting in the testing set, with 92.9% accuracy, 75% specificity, and 94.7% sensitivity. The sensors can further classify subcategories of HCM with >70.3% accuracy for all cases in the testing set. These findings show the applicability of the sensors setup and suggest that VOCs may be a promising noninvasive and real-time HCM diagnosis option.

Synergistic interactions between the supported thin oxide layer and the underlying metal oxide support led to the development of novel and exciting material properties. In this work, we present a new and general approach for the surface growth of MgAl layered double hydroxides (LDH) on ZrO₂, Al₂O₃, and TiO₂ support materials. We examine the synergistic interactions between the top MgAlO_x mixed metal oxide (MMO), obtained after LDH calcination, and the underlying metal oxide support (MMO/metal oxide) as a function of MMO loading and support type. The obtained materials are characterized using a range of analytical tools ICP-OES, H₂-TPR, CO₂-TPD, PXRD, TGA/DSC, physisorption, HRSEM-EDS and HAADF-STEM–EDS followed by catalytic testing. We show that regardless of the MMO/metal oxide combination, effective interaction between the MMO and the underlying support, more dominant at the lower MMO coverage, promotes synergistic effects, manifested by a lower Ni reduction temperature compared to Ni on bulk MMO. Evaluating the obtained catalysts (Ni/MMO/metal oxide) in the dry reforming of methane (DRM) reaction, we find that the increase in MgAlO_x-MMO coating amount on the ZrO₂ nanoparticles (NPs) leads to an improvement in DRM activity and stability. In addition, we find that for the same MgAlO_x-MMO coating amount, the Ni catalyst based on the ZrO₂ NPs is superior to the catalyst based on Al₂O₃ NPs, while the catalyst based on TiO₂ NPs is the least active. The obtained results are explained in context to the extent of coating, metal support interaction (MSI) levels, and support structure. Combined with the high versatility of LDH material, this new methodology provides a versatile synthetic route to adapt the surface property of an oxide to a certain application. For DRM, we show the tuning of MSI as governed by the interactions between the underlying metal oxide and supported MMO.

Biological Field Effect Transistors (Bio-FETs) are redefining the standard of biosensing by enabling label-free, real-time, and extremely sensitive detection of biomolecules. At the center of this innovation is the fundamental empowering role of advanced materials, such as graphene, molybdenum disulfide, carbon nanotubes, and silicon. These materials, when harnessed with the downstream biomolecular probes like aptamers, antibodies, and enzymes, allow Bio-FETs to offer unrivaled sensitivity and precision. This review is an exposition of how advancements in materials science have permitted Bio-FETs to detect biomarkers in extremely low concentrations, from femtomolar to attomolar levels, ensuring device stability and reliability. Specifically, the review examines how the incorporation of cutting-edge materials architectures, like flexible / stretchable and multiplexed designs, is expanding the frontiers of biosensing and contributing to the development of more adaptable and user-friendly Bio-FET platforms. A key focus is placed on the synergy of Bio-FETs with artificial intelligence (AI), the Internet of Things (IoT), and sustainable materials approaches as fast-tracking toward transition from research into practical healthcare applications. The review also explores current challenges such as material reproducibility, operational durability, and cost-effectiveness. It outlines targeted strategies to address these hurdles and facilitate scalable manufacturing. By emphasizing the transformative role played by advanced materials and their cementing position in Bio-FETs, this review positions Bio-FETs as a cornerstone technology for the future healthcare solution for precision applications. These advancements would lead to an era where material innovation would herald massive strides in biomedical diagnostics and subsume.

This review article explores the transformative potential of smart dust systems by examining how existing chemical sensing technologies can be adapted and advanced to realize their full capabilities. Smart dust, characterized by submillimeter-scale autonomous sensing platforms, offers unparalleled opportunities for real-time, spatiotemporal chemical mapping across diverse environments. This article introduces the technological advancements underpinning these systems, critically evaluates current limitations, and outlines new avenues for development. Key challenges, including multi-compound detection, system control, environmental impact, and cost, are discussed alongside potential solutions. By leveraging innovations in miniaturization, wireless communication, AI-driven data analysis, and sustainable materials, this review highlights the promise of smart dust to address critical challenges in environmental monitoring, healthcare, agriculture, and defense sectors. Through this lens, the article provides a strategic roadmap for advancing smart dust from concept to practical application, emphasizing its role in transforming the understanding and management of complex chemical systems.

Biological systems maintain homeostasis, ensuring stability in the face of internal and external perturbations and counteracting stochastic noise. Traditionally, this is understood through the lens of control mechanisms designed to offset deviations and maintain certain quantities near functionally desired set-points. Here, we propose an alternative perspective to understand homeostasis: the dynamic perspective, in which homeostasis emerges from high-dimensional interactions creating stable attractors in the phase space. These multi-dimensional attractor manifolds can constrain all components collectively, eliminating the need for explicit control of individual variables. The presence of null directions on an attractor allows for degenerate states that can add flexibility while preserving functionality. Using single cell growth and division homeostasis as a test case, we develop and support our perspective by models and meta-analysis of numerous single-cell datasets across organisms and conditions. Importantly, we do not reject the control-theory perspective but rather suggest that control circuit models can be seen as low-dimensional projections of a more complex, multi-dimensional system.

The acid–base properties of catalytic materials play a crucial role in facilitating chemical transformations. Nanoscale structural heterogeneities within these catalysts can significantly affect the distribution, type, and strength of their acid–base sites, thereby influencing both localized and overall catalytic reactivity. In this study, high spatial-resolution chemical imaging of basic sites on supported Mg–Al mixed oxide (MgAlO_x) particles, which serve as catalysts for aldol condensation reactions, was achieved using atomic force microscopy–infrared (AFM-IR) nanospectroscopy measurements while using formic acid as a chemical probe for surface basic sites detection. This approach enabled us to identify the distribution, geometry, and strength of basic sites with nanoscale precision. It was revealed that platelet MgAlO_x particles predominantly exhibit a uniform bidentate adsorption of formic acid, whereas aggregates display a heterogeneous distribution of both monodentate and bidentate adsorption modes, indicating differences in the distribution, geometry, and strength of the basic sites. Additionally, upon exposure to formic acid, smaller particles underwent phase reconstruction, transitioning into cubic-like structures characterized by distinct bidentate adsorption of formic acid. This transformation was attributed to the rehydration and intercalation of formate species. The insights gained by conducting high spatial resolution nanospectroscopy measurements highlight the correlation between flat surfaces, characterized by a low density of surface defects, and a homogeneous distribution of basic sites, with a dominant bidentate adsorption mode of formic acid. These results emphasize the critical role of high spatial resolution chemical imaging in unraveling the link between structural features and acid–base functionality in catalytic materials.

Magnetic nanorobots primarily composed of ferromagnetic materials have been extensively investigated for their potential medical applications. Here, we have designed and developed superparamagnetic iron oxide nanoparticles (SPIONs)-functionalized nanorobots (SPIONs-NR), a system that is significantly smaller in size and has larger magnetic anisotropy and steerability than most previously reported superparamagnetic microrobots. We demonstrate that the nanorobots are highly stable against magnetic agglomeration, even at high densities. Due to their smaller size, they can be controllably steered through crowded biological media, which was not possible before. We have maneuvered the robots through the extracellular matrix to target and annihilate malignant cells via magnetic hyperthermia-induced localized heating. Collectively, these properties make SPIONs-NR promising candidates for nanomedicine applications.

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 study introduces a flexible skin thermometer for personalized body temperature monitoring, enabling continuous measurement and offering advantages over conventional mouth-based techniques that are limited to point-in-time readings. Such personalization is critical for medical applications, particularly in environments with varying climatic conditions. Our in-house developed flexible thermometer FLEXTEM provides continuous real-time temperature readings, can be used on different body sites (such as forehead and forearm), and adapts to diverse physiological and environmental factors. In a novel study involving ∼470 individuals from Rajasthan, a region characterized by extreme seasonal variations, FLEXTEM was tested alongside standard digital and infrared thermometers, to examine the influence of environmental (such as ambient temperature) and physiological (such as gender) factors on body temperature. Based on the findings, normal body temperature ranges were established for different demographic groups based on gender and work conditions. However, defining ranges based on health status was constrained by the smaller sample size. Our research highlights the potential of flexible skin-based thermometers for tailored health assessments and demonstrates how environmental factors can lead to variations in body temperature ranges.