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Plastic pollution is a major environmental and health threat due to its widespread presence in ecosystems and food chains. Despite extensive research on microplastics, the detection of submicron plastics remains challenging due to their distinct physical and chemical properties and the limitations of current analytical methods. SERS has attracted significant attention in recent research as an ultra-sensitive approach for detecting nanoplastics compared to other spectroscopy techniques. In this paper, a stable, biodegradable, waste-free novel paper-based SERS substrate is developed for the rapid detection of submicron (200 nm) polystyrene (PS) particles via the controlled deposition of AuNPs onto filter paper using an atmospheric cold plasma jet printing process. The density of AuNPs increases with the number of printing passes, correlating with enhanced SERS results. The resulting SERS substrates are capable of quantifying a broad range of PS concentrations (1–500 μg mL⁻¹) using just 5 μL of analyte. The fabricated SERS substrate enables reliable quantification of PS in water, exhibiting a strong linear correlation (R² = 0.993) between SERS intensity and PS concentration, with a detection limit of 10 μg mL⁻¹ . These substrates demonstrate exceptional stability and reproducibility over a 10-week period, addressing key challenges associated with paper-based SERS substrates and making them suitable for long-term monitoring. Furthermore, analysis of tap water as a representative real-world sample demonstrates the practical applicability of the SERS substrate for environmental monitoring, revealing quantifiable levels of PS contamination. 

Abstract Molecular quantum emitters are becoming increasingly important in quantum information and communication. As a stepping stone towards a single-molecule quantum system, the collective emission from the ensemble of isolated organic chromophores, randomly and sparsely incorporated into an organometallic host crystal, is characterized by Raman and temperature-dependent photoluminescence spectroscopies. The tetracene or rubrene guest chromophores are deposited at very low densities when the ferrocene host is grown in a crystalline form, so that each of the chromophores is well isolated by its organometallic molecular neighbors. The ensemble emission of the chromophores is compared to that of the crystalline or dissolved forms to identify its unique spectral features. The enhanced quantum yield and reduced spectral linewidth with a significant blue-shift in photoluminescence suggest that ferrocene is a novel type of host matrix, maximizing the ability of the tetracene guest to act as a well-isolated quantum entity, while suppressing unwanted environmental decoherence by confining it within the ferromagnetic (organometallic) host material. 

Abstract Reducing wasted food has been identified as a key strategy to meet food security goals and attain human nutritional needs and food preferences in an equitable, sustainable, and resilient manner. Yet, mathematically modeling how reducing wasted food contributes to sustainability, equity, and resilience objectives, and the possible interactions and tradeoffs among these metrics, is limited by challenges to quantifying these characteristics. Using the process of convergent science, we develop a prototype wasted food model to evaluate how a set of common equity, sustainability, and resilience measures interact. We consider prevention (consumer education) and treatment (anaerobic digestion and composting) options for wasted food diversion from landfills. The model applies a convex nonlinear optimization to determine the allocation of wasted food to different management alternatives, optimizing for economic (net cost), sustainability (emissions reductions or energy savings), or equity (distribution of per-capita cost or emissions reduction impacts). The model developed in this research is available online as open-source code for others to replicate and build upon for future studies and analysis. Our findings illustrate that optimal wasted food management alternatives may vary when targeting different metrics and that strategies promoting cost-effectiveness may be in tension with sustainability or equity goals and vice versa. The implications of this study could be used by policy makers to evaluate how wasted food reduction measures will impact sustainability, equity, and resilience goals. 

Heat integration has been widely and successfully practiced for recovering thermal energy in process plants for decades. It is usually implemented through synthesizing heat exchanger networks (HENs). It is recognized that mechanical energy, another form of energy that involves pressure-driven transport of compressible fluids, can be recovered through synthesizing work exchanger networks (WENs). One type of WEN employs piston-type work exchangers, which demonstrates techno-economic attractiveness. A thermodynamic-model-based energy recovery targeting method was developed to predict the maximum amount of mechanical energy feasibly recoverable by piston-type work exchangers prior to WEN configuration generation. In this work, a heat-integrated WEN synthesis methodology embedded by the thermodynamic model is introduced, by which the maximum mechanical energy, together with thermal energy, can be cost-effectively recovered. The methodology is systematic and general, and its efficacy is demonstrated through two case studies that highlight how the proposed methodology leads to designs simpler than those reported by other researchers while also having a lower total annualized cost (TAC).