Analysis of model dimensionality, particle shrinkage, boundary layer reactions on particle-scale modelling of biomass char conversion under pulverized fuel combustion conditions

In this work, the effects of model dimensionality, particle shrinkage, and boundary layer reactions on particle-scale modelling of biomass char conversion under pulverized fuel combustion conditions have been analysed by using six models: zero-dimensional models with constant particle size (0D_Cons) or shrinking particle size (0D_SPM), one-dimensional models with/without considering particle shrinkage (1D_Cons/1D_SPM), and 1D_Cons and 1D_SPM with considering boundary layer reactions (1D_Cons_BH and 1D_SPM_BH). A comparison with existing experimental data shows that the 1D_SPM_BH model with consideration of intra-particle heat and mass transfer, particle shrinkage, and boundary layer reactions is an appropriate model to describe biomass char conversion over a wide range of conditions. The 0D_Cons model is a good approximation for the conditions of small particle size (< 1 mm) at 1273–1473 K, but overestimates the char conversion rate for larger biomass char particle or at high temperatures (regime III). The 0D_SPM model gives a reasonable prediction on char conversion time but predicts a larger contribution of reaction between char and O2 as compared to the 1D_SPM_BH model. The consideration of intra-particle heat and mass transfer in particle-scale modelling (1D_Cons and 1D_SPM) is beneficial to improving the model prediction of char conversion time and the contributions of char oxidation and gasification reactions. The boundary layer reactions have a significant effect on the prediction of char conversion for large particles (> 1 mm) and high temperatures (> 1473 K). An implication for the selection of a particle-scale model in CFD modelling is also given

Surface engineering of metal-organic framework nanoparticles-based miRNA carrier:Boosting RNA stability, intracellular delivery and synergistic therapy

MicroRNAs (miRNAs) are small noncoding RNAs that are critical for the regulation of multiple physiological and pathological processes, thus holding great clinical potential. However, the therapeutic applications of miRNAs are severely limited by their biological instability and poor intracellular delivery. Herein, we describe a dual-layers surface engineering strategy to design an efficient miRNA delivery nanosystem based on metal–organic frameworks (MOFs) incorporating lipid coating. The resulting nanoparticle system was demonstrated to protect miRNA from ribonuclease degradation, enhance cellular uptake and facilitate lysosomal escape. These ensured effective miRNA mediated gene therapy, which synergized with MOF-specific photodynamic therapy and pre-encapsulated doxorubicin (Dox) chemotherapy to provide a multifunctional with therapeutic effectiveness against cencer cells The mechanisms of miRNA binding and Dox loading were revealed, demonstrating the potential of the present MOFs surface-engineered strategy to overcome their inherent pore-size restriction for macromolecular miRNA carrying, enableefficient co-delivery. In vitro studies revealed the potential of our multifunctional system for miRNA delivery and the demonstrated the therapeutic effectiveness against cancer cells, thereby providing a versatile all-in-one MOFs strategy for delivery of nucleic acids and diverse therapeutic molecules in synergistic therapy.</p

Vapor–Liquid Equilibrium Measurements and Cubic-Plus-Association Modeling of Triethylene Glycol Systems

Due to the low vapor pressure of triethylene glycol, there is limited vapor–liquid equilibria data involving this component at high pressure. Aiming to expand this experimental database, new vapor–liquid equilibria data points were measured for the systems: triethylene glycol (1) + methane (2), triethylene glycol (1) + ethane (2), triethylene glycol (1) + ethane (2) + water (3), and triethylene glycol (1) + gas mixture (2). The experimental ranges were within the relevant process conditions for the natural gas dehydration, with T = (293.15, 333.15) K, and P = (3.0, 18.0) MPa. The new data include both gas and liquid phase compositions with relative experimental uncertainties (ur) below 0.17. Furthermore, the Cubic-Plus-Association (CPA) using the 4C association scheme for triethylene glycol (TEG) and only one interaction parameter per binary has provided a qualitative description of the newly measured data, with average absolute relative deviation (AARD) ranging between 3% and 54%

Flexible operation, optimisation and stabilising control of a quench cooled ammonia reactor for power-to-ammonia

This paper discusses the operation of an ammonia reactor for a Power-to-Ammonia (P2A) plant. We develop a dynamic model for an ammonia reactor system consisting of a three-bed quench cooled adiabatic reactor and a feed-effluent heat exchanger. The reactor bed model is formulated as a differential algebraic equations (DAE) system. We use the thermodynamic software Thermolib for rigorous modeling of the thermodynamic functions in the high pressure ammonia reactor. We present a case study of an ammonia synthesis loop in a P2A plant connected to a 250 MW renewable energy source with a capacity factor of 0.4. Static optimization and stability analysis are performed for the reactor system, which located the optimal operating point close to instability. The dynamic simulations confirm the unstable operating regions as severe oscillations arise. A fluctuating energy supply from renewable sources requires the ammonia reactor to operate over a wide operating window from 20%–120% of nominal capacity. We formulate a realistic strategy for varying the supply of H2 and (load) to the synthesis loop depending on the available energy. Open-loop simulations show that varying the synthesis feed flow cause oscillations in the ammonia reactor system. Therefore, we propose a regulatory control structure for stabilising the ammonia reactor. The optimisation algorithm determines the reactor set-point state by updating at changes to the synthesis loop load. Hereby, we achieved fast control and close tracking of the set-points for the ammonia reactor

Ce³⁺-based phosphor converter enabling laser lighting to attain both high CRI and high luminous efficacy

Eu2+ doped-CaAlSiN3 possesses broad red emission, enabling a phosphor-converted lighting device to achieve a high color rendering index (CRI) and proper color temperature. However, CaAlSiN3:Eu2+ exhibits relatively slow decay (∼1 μs) and intense re-absorption of luminescence from green/yellow emitters, thereby causing optical saturation and reducing the luminous efficacy. Here, we fabricated a novel phosphor converter comprising Lu3Al5O12:Ce3+ and Y1.3Gd1.6Al5O12:Ce3+ powders. The typical sample, when excited by a blue laser, exhibited a high luminous efficacy of 231 lm/W and a high saturation threshold of 22.2 W/mm2, resulting in a high luminous exitance of 695 lm/mm2. Importantly, the phosphor converter produced a broad emission band that included sufficient cyan and red components, resulting in a full width at half maximum (FWHM) of 134 nm and a high CRI of 81. With this excellent balance between CRI and luminous efficacy, the reported phosphor converter can significantly expand the range of laser lighting applications.</p

Co-enhancing effects of zero valent iron and magnetite on anaerobic methanogenesis of food waste at transition temperature (45 °C) and various organic loading rates

Deoiling of food waste (FW) after hydrothermal pretreatment occurs at high temperatures, and more energy is required for substrate cooling before the anaerobic digestion (AD) process. AD at the transition temperature (for example 45 °C) is good for energy saving and carbon emission reducing when treating deoiling FW. However, the metabolic activity of methanogens must increase at the transition temperatures. This study proposes the use of zero-valent iron (Fe0) and magnetite (Fe3O4) to boost CH4 yield from deoiling FW. The results showed a co-enhancing effect on CH4 yield upgradation when using Fe0 and Fe3O4 simultaneously, and the highest CH4 yield reached 536.23 mLCH4/gVS, which was 67.5 % higher than that of Fe0 alone (320.14 mLCH4/gVS). In addition, a high organic loading was favorable for increasing the CH4 yield from deoiling FW. Microbial diversity analysis suggested that the dominant methanogenic pathway at 45 °C was hydrogenotrophic methanogenesis. Herein, a potential metabolic pathway analysis revealed that the co-enhancing effects of Fe0 and Fe3O4 enhanced syntrophic methanogenesis and possibly boosted electron transfer efficiency

Democratizing uncertainty quantification

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.</p

A privacy-preserving heterogeneous federated learning framework with class imbalance learning for electricity theft detection

Electricity theft is a critical issue in smart grids, leading to significant financial losses for utilities and compromising the stability and reliability of the power system. Existing centralized methods for electricity theft detection raise privacy and security concerns due to the need for sharing sensitive customer data. To address these challenges, we propose HeteroFL, a novel heterogeneous federated learning framework for privacy-preserving electricity theft detection in smart grids. HeteroFL enables retailers to collaboratively train a global model without sharing their private data, while accounting for the class imbalance problem prevalent in electricity theft datasets. We introduce a data partitioning and aggregation scheme that assigns different weights to classes, ensuring a balanced contribution and representation of each class in the global model. In addition, our framework leverages the CKKS homomorphic encryption scheme to perform secure computations on encrypted parameters and employs a CNN-LSTM model to capture the spatial and temporal dependencies in electricity consumption patterns. We evaluate HeteroFL using a real-world smart grid dataset and demonstrate its effectiveness and efficiency in detecting energy theft. Furthermore, we analyze the robustness and perform ablation studies to validate the framework's stability and identify the contributions of its key components. Although the impact of approximation errors introduced by the CKKS scheme on the CNN-LSTM model's performance requires further investigation, our framework presents a promising solution for privacy-preserving and accurate electricity theft detection in smart grids using heterogeneous federated learning.</p

A laboratory and theoretical framework for systematic non-equilibrium turbulence studies

The cornerstone assumption of equilibrium of the small and intermediate scales in the classical view of turbulence (K41 - the combined efforts of Kolmogorov, Batchelor and Richardson) is under ever increased scrutiny. Although the K41 based models do appear to apply well to some flows, there exist many important flows that are problematic for these turbulence models. In particular, it is interesting to note that the most challenging applications appear to have one thing in common - rapid changes of the flow in the mean in time and/or space. It is thus interesting to systematically investigate what the bounds of validity of the classical K41-view of turbulence are, if any. And if the K41-picture of turbulence does indeed break down, what are the non-linear spectral energy transfer mechanisms that lead to nonequilibrium turbulence behavior (local vs. non-local)? Does the non-linear energy exchange between scales divert from the classically assumed Richardson cascade? And is the constancy of the spectral flux across the inertial range interrupted? In order to answer these questions, a new facility for the systematic study of non-equilibrium turbulence in a controlled setting has been established along with an accompanying theoretical framework that is tailored for addressing these specific issues