Starch is a widely used biopolymer, but native starch has several inherent limitations that restrict its industrial applications, including a broad and variable gelatinization temperature range, a strong tendency to retrograde, poor stability under shear as well as under acidic and thermal conditions, and limited freeze-thaw stability. Superheated steam (SHS) technology offers a green, physical route to mitigate these shortcomings. In the SHS process, secondary heating steam under low-humidity and oxygen-deficient conditions alters particle morphology, reduces crystallinity, and modifies chemical bond distribution through rapid heat transfer and its thermomechanical effects. Consequently, SHS typically increases the surface porosity and solubility of starch, reduces its relative crystallinity, and shifts the chain length distribution toward a higher proportion of shorter chains while decreasing the proportion of longer chains. Moreover, SHS can increase the content of resistant starch through V-type amylose-lipid complex formation at high temperatures. SHS technology reduces peak viscosity and disintegration values while enhancing final viscosity and thermal stability, thereby improving product texture and extending shelf life. Overall, quantitative control of SHS process parameters and mechanistic studies on different starch sources remain necessary for industrial conversion. SHS, as an energy-efficient and scalable physical modification technique, holds significant potential for the directional regulation of starch functionality in food applications.

Physics-informed neural networks (PINNs) often struggle to solve stiff partial differential equations (PDEs) with moving boundaries, such as convection-dominated droplet drying with shrinking domains and related Stefan-type phase-change problems. This study investigates a physics-guided PINN formulation for nanosuspension droplet drying in superheated steam, where an accurate prediction of the locking point is important, as it marks the onset of structure formation and significantly influences particle morphology and final powder characteristics. The formulation retains the standard PINN backbone and combines two problem-specific modifications: a logarithmic state-variable transformation to compress the solution dynamic range and improve the representation of steep near-surface gradients, and a Péclet number-based scaling of the surface residual to better balance the boundary and PDE training signals across the stiffness regimes. Compared with a numerically verified Crank-Nicolson (CN) reference solution, the proposed formulation showed the greatest advantage in the high-Péclet regime, where the boundary layer steepening and training difficulty were most pronounced. In the stiffest case considered, it substantially reduced the discrepancy from the numerically verified CN reference solution compared with both the baseline PINN and the unscaled log-transformed formulation, while also improving the locking-time prediction. These results show that a physics-guided state transformation, combined with residual scaling, can improve the robustness of PINNs for this class of stiff, moving-boundary drying problems.

Influence of glycerol monostearate on structural organization and digestibility of pea starch processed by superheated steam extrusion.

ABSTRACTCitrus sinensis (L.) Osbeck (C. sinensis) peel is a rich source of essential oil (EO) widely used in pharmaceutical, food, and aroma industries; however, effective extraction strategies and molecular insights remain unexplored. This study presents superheated steam extraction (SHSE) as a novel green approach for the C. sinensis EO extraction and its comparison with conventional hydro and steam distillation methods. The chemical profile and bioactivities were analyzed and further strengthened by molecular docking and DFT studies. A maximum yield of 0.20% (w/w) was obtained through SHSE. Volatile composition, studied by GC–MS, identified d‐limonene (8.84% to 30.72%) as the primary compound. Several tests, including resazurin microtiter plate assay, agar well diffusion, and microdilution broth assay, were performed to evaluate the antimicrobial potential. The SHS extracted EO exhibited maximum antibacterial and antifungal activity. Antioxidant properties of the extracted EOs were determined by employing the DPPH assay, hydrogen peroxide scavenging assay, and the FRAP assay. Superheated steam extracted EO also revealed the highest antioxidant activity. Molecular docking was performed to evaluate the ligand–protein interactions. All compounds showed lower binding energies; among them, four compounds, d‐limonene, trans‐carvyl acetate, β‐terpinyl acetate, and α‐himachalene, were found as significant binders to the targeted antioxidant and antimicrobial proteins. DFT studies were performed at the B3LYP/6–31G(d,p) level to elucidate the compound's antioxidant mechanism of action. DFT predicted β‐terpinyl acetate as the most effective antioxidant candidate, attributed to its lowest energy gap (6.7616 eV), highest chemical softness, and lowest chemical hardness. Overall, it is concluded that SHSE gave the highest EO yield while biological assays provided the synergistic performance of EO components which is justified by combining with computational analysis.

Oxidation behavior of Zr-4 cladding under superheated and high-temperature steam environments

Accurate prediction of superheated steam temperature (SST) is critical for the safe and efficient operation of large-scale thermal power units, particularly under large load variations and high thermal inertia. This study proposes an iTransformer-based SST prediction framework (iTransformer-SST) to address limitations of conventional proportional–integral–derivative (PID) control and existing data-driven models in capturing multivariable coupling, time-delay effects, and physical consistency. Using the A-side subsystem of a 1000 MW thermal power unit, 19-dimensional process data were collected continuously over two months with a sampling interval of 2.4 s. After data preprocessing, time-lagged cross-correlation (TLCC) analysis combined with expert knowledge was employed for feature screening, resulting in ten highly relevant input variables. To enhance predictive robustness, the baseline iTransformer was augmented with a Local Temporal Convolution (LTC) module for local disturbance modeling and a physics-guided regularization term to enforce delayed monotonicity and smoothness constraints. In 240 min rolling forecasts of the final-stage superheater outlet temperature, the proposed model achieved a mean squared error (MSE) of 0.0887, a mean absolute error (MAE) of 0.2312, and a coefficient of determination () of 0.9650, significantly outperforming long short-term memory (LSTM), Informer, and the baseline iTransformer. The combined LTC and physics-guided design reduced MSE by 13.5%, demonstrating strong potential for feedforward-assisted SST control in industrial thermal power applications.

Effect of superheated steam treatment on rehydration characteristics and eating quality of instant rice.

The effect of superheated steam ultra-high temperature short-time treatment on rice bran quality and storage stability.

Assessing and improving the operational flexibility of grate-fired cogeneration power plants

Small modular reactors (SMRs): Comparison of saturated versus superheated steam Rankine cycle under equal thermodynamic constraints

Flow field and noise study of supersonic superheated steam jet based on large eddy simulation

This study employs numerical simulation to investigate the mechanisms through which centrifugal nozzle structural parameters and superheated steam velocity influence steam desuperheating performance. The model accuracy was validated against factory measurement data, demonstrating a maximum deviation of only 1.07% (specifically for the outlet steam temperature in Case 2, comparing the simulated 696.65 K against the measured 704.21 K). Results indicate that the spray cone angle is the primary factor governing desuperheating efficiency, exerting a stronger influence than the droplet Sauter Mean Diameter (SMD). Specifically, the simulations identified that optimal atomization and heat transfer occur at a nozzle stem angle of 30° and a swirl hole angle of 67.5°. Furthermore, increasing the swirl chamber angle and steam velocity (> 45 m/s) markedly enhances heat exchange by promoting droplet breakup and dispersion. Based on these findings, an L9(34) orthogonal experiment was conducted to determine the optimal configuration. The resulting parameter combination – a 67.5° swirl hole, 120° swirl chamber, 30° nozzle stem, and 75 m/s steam velocity – exhibited superior performance. Compared with the original model, the optimized design reduced the droplet SMD by 22.2%, increased the spray cone angle by 3%, and improved the steam temperature reduction rate by 6.6 percentage points. This study provides a theoretical foundation for the structural optimization of high-efficiency centrifugal adjustable nozzles.

Antimicrobial mist pretreatment for enhancing superheated steam efficacy in inactivating Enterococcus faecium NRRL B-2354 on dry food processing surface.

Superheated steam sterilization of foodborne pathogens on pork belly: Biphasic kinetics, dual-action mechanisms, and logistic model validation.

Steam Explosion (SE) is a relatively newly developed physicochemical pretreatment method that has received increasing attention since it can effectively upgrade biomass for further utilization. During SE, biomass is first exposed to high-temperature, high-pressure steam and then rapidly depressurized. This process efficiently breaks down the lignocellulosic structure, reduces moisture content, and increases fixed carbon and calorific value. It also enhances biomass grindability and densification, making it more suitable as a renewable solid fuel. This review carefully discusses the fundamental principles of SE and its effects on particle characteristics. Then, the types of SE reactors (mainly composed of batch reactors and continuous reactors) are systematically compared, and the challenges in scaling up and commercialization are discussed. Also, the characteristics of pyrolysis or gasification of biomass pretreated by SE are described in detail. Studies indicate that SE is beneficial for the enhancement of product quality. Finally, the prospects and future challenges in the development of SE (including superheated steam explosion, reaction kinetics improvement, and heat and mass transfer intensification) are presented and discussed.

Superheated steam temperature (SST) regulation in large coal-fired combined heat and power (CHP) units becomes increasingly challenging under deep peak-shaving. Wide-range load variations and multisource disturbances require strong disturbance rejection, whereas industrial distributed control systems typically retain PID-oriented implementations with limited computational capability. Motivated by these, this paper proposes a bilevel IMC-DDE-PID control framework for SST regulation. In the inner loop, a desired dynamic equation (DDE)-based tuning rule shapes the plant dynamics to follow a prescribed desired closed-loop model without requiring a precise process model and partially attenuates input-side disturbances. The residual disturbance is then handled by an outer internal model control (IMC) layer built upon the desired model as an embedded internal model. Comprehensive simulations are conducted on seven benchmark SISO plants and on identified SST models at multiple loads, including scenarios with large load variations and cross-load model variation, to evaluate tracking, disturbance rejection, and control variation. Finally, field tests on an in-service 660 MW CHP unit under deep peak-shaving validate the practicality of the proposed method, reducing the SST fluctuation range by 7 °C.

Chemical Profile, Biological Activities, Molecular Docking, and Density Functional Theory (DFT) of Cymbopogon citratus Essential Oil Extracted By Conventional and Superheated Steam Extraction Techniques

The increasing integration of renewable energy sources into power generation systems has led steam turbines to operate more frequently under off-design conditions, with repeated start-ups and shutdowns introducing thermal transients that can compromise structural integrity. During cold start-up, the interaction between superheated steam and cold walls can trigger film condensation, releasing a large amount of energy and creating a strongly coupled problem between the film dynamics and the thermal response of the solid. While various strategies have been proposed to address the mismatch in characteristic timescales between fluid and solid in Conjugate Heat Transfer (CHT) problems, the limitations of commonly used quasi-steady approaches has been rarely discussed. In light of this, the novelty of this work lies in the development and validation, with both analytical solution and experimental data, of an equilibrium-based phase change model for laminar condensate films and in the demonstration of the inadequacy of widely adopted computational cost-saving strategies in turbomachinery applications, when dealing with thermal transients involving the transport of a laminar condensing film. Finally, the source terms based loosely-coupled Dual Time-Step method is adopted, showing a remarkable ability to predict the non negligible inertia that a condensing laminar film typically exhibits. • Research context: transient cold start-ups of steam turbines. • Proposal and validation of a multiphase model for wall condensation of pure steam. • Monolithic CHT simulation of wall condensation over a vertical plate. • Exploration of multiphysics approaches to reduce computational costs. • Remarkable accuracy by the Dual time-step method against the standard approaches.

Experimental investigation on influence of inlet subcooling to “S-shaped” density wave oscillation in parallel helical channels

Corrosion behavior of Zr-xSn-0.20Fe-0.18Cr-0.03Ni alloys in 400 ℃ and 500 ℃ superheated steam