Linking additive manufacturing process parameters and surface roughness to optical absorptance for solar energy applications

Solar Energy · 2026-04-27

A CFD Study of the Influence of Porous Structure Placement on Jet Formation in Laser-Induced-Forward-Transfer (LIFT) Printing

2025-07-08

Abstract Laser-Induced Forward Transfer (LIFT) printing is a highresolution, non-contact, laser-based direct-writing technology suitable for various materials. The LIFT process is limited by its one-to-one correspondence between laser pulses and jet formation, which restricts the printing throughput and complicates scaling for high-speed operations. To address this challenge, we propose a novel strategy to integrate a porous structure below the donor slide in the LIFT system. The porous structure is expected to facilitate the formation of multiple jets from a single laser pulse, thereby overcoming traditional throughput limitations. In this study, we developed a computational fluid dynamics (CFD) model to verify the proposed idea. The findings confirmed that the formation of multiple jets induced by a single laser pulse can be achieved by manipulating the dynamics of bubble expansion within the porous structures. The simulations also demonstrated that variations in the size, spacing, and positioning of the porous structures, along with the initial bubble pressure, can significantly influence jet characteristics. This enables precise control over jet width and length, suggesting a viable approach to achieving high-throughput, high-efficiency LIFT printing through the deployment of porous structures.

Development of boron-enhanced inconel 718 with superior thermomechanical properties for high-temperature concentrated solar power applications

Solar Energy Materials and Solar Cells · 2025-06-20 · 2 citations

A generative deep learning and explainable machine learning framework for heat transfer prediction and analysis in porous structures with oscillatory flows

Applied Thermal Engineering · 2025-12-03 · 1 citations

A high accuracy machine-learning potential model for Mo-Re binary alloy

Computational Materials Science · 2025-04-16 · 4 citations

Molybdenum is a promising candidate material for advanced nuclear reactors . However, its application in nuclear energy facilities is limited by its intrinsic brittleness , a common characteristic of body-centered cubic transition metals, which often exhibit poor plasticity and workability. The addition of Re to Mo can exploit the “Re softening effect” to enhance plasticity. To better understand the physical origin of this effect and explore the nanoscale atomistic mechanisms in Mo-Re alloys under service conditions, atomic-scale simulation methods, such as molecular dynamics (MD), are widely used as a complementary theoretical tool to experimental studies. However, the reliability of MD simulations is constrained by the limitations of existing empirical interatomic potentials . To address this challenge, this study employs state-of-the-art deep-potential methods to develop a machine learning-based interatomic potential for Mo-Re alloys. This advanced potential model achieves first-principles accuracy across a wide range of material properties , including elastic constants , surface energies, point defects , dislocations, and melting points, within a single potential. It enables high-accuracy atomic-scale simulations and investigations into the microstructural evolution of Mo-Re alloys under complex multi-field coupling conditions (irradiation, heat, and stress), which will establish the theoretical foundation for understanding the Re softening effect. • A accurate machine-learning interatomic potential for Mo-Re alloy. • Accurate in a wide range of basic, surface, and defect properties. • Highly generalizable to predict properties that are not training targets. • Suitable for investigation of the Re softening effect in Mo-Re alloy during service.

Study on Water Phase Interference Mechanism and Its Effect on Production Performance of Tight Gas Reservoir

Springer series in geomechanics and geoengineering · 2025-01-01

3D Printing of Inconel 718 with Enhanced Boron Composition as a Novel Solar Absorber Tube Material in the Concentrated Solar Power (CSP) System

2024-03-07

The growing demands for elevated efficiency in the solar energy industry led researchers to focus on the development of functional solar absorber tube material in concentrated solar power (CSP) systems, when molten salts are adopted as the heat transfer fluid. In this study, the typical solar absorber tube material, Inconel 718, was enhanced with boron to achieve a higher solar absorptivity in the visible light spectrum. Combined with an additive manufacturing (AM) method, the boron composition exceeded the traditional manufacturing limit of 60 ppm without microstructural defects. The boron-enhanced Inconel 718 exhibited a high solar absorptivity of nearly 90 % while maintaining a high thermal cycle fatigue resistance after thermal cycling treatment between 550°C and 720°C. The boron composition was increased to the manufacturing failure point, and the effects of different boron compositions on mechanical properties, microstructure, and optical properties were studied. The provided microstructure-property map in this study delivers high potentials of functional AM-printed alloy material in CSP applications.

Flow and Heat Transfer Experimental Study for 3D-Printed Solar Receiving Tubes With Helical Fins at Internal Surface

Journal of Solar Energy Engineering · 2024-06-04 · 7 citations

Abstract 3D-printing technology was applied to fabricate novel solar thermal collection tubes that have internal heat transfer enhancement fins and external surfaces with high solar absorptivity and low emissivity due to the ability to use different materials in one tube. Helical fins were selected to introduce circumferential flow and thus minimize the circumferential temperature difference of the tube that receives sunlight on one side. The structures of the helical fins were previously optimized from computational fluid dynamics (CFD) analysis with the objective of low entropy production rate by looking for high heat transfer coefficient and relatively lower pressure loss. High-temperature alloy, Inconel-718, was used to 3D print the tubes, which can resist corrosion for the potential application of molten chloride salts as heat transfer fluid. Experimental tests were carried out using water as the heat transfer fluid with the high heat flux provided by a tubular furnace heater. The tested Reynolds number ranges from 3.9 × 103 to 6.1 × 104. Heat transfer coefficients of up to 2.8 times that of the smooth tube could be obtained with the expense of increased pressure loss compared to that of the smooth tube. The total system entropy generation can be significantly reduced due to the benefit of heat transfer enhancement that is greater than the expenses of the increased pressure loss. The experimental results of the 3D-printed heat transfer tubes confirmed the CFD-based results of fin optimization. The novel heat transfer tube is recommended for application in concentrating solar power systems.

Helical Fins for Concentrated Solar Receivers: Design Optimization and Entropy Analysis

Journal of Energy Resources Technology · 2023-08-18 · 10 citations

Abstract Concentrated solar power (CSP) with thermal energy storage (TES) has the potential to achieve grid parity. This can be realized by operating CSP systems at temperatures above 700 °C with high-efficiency sCO2 power cycles. However, operating CSP systems at such temperatures poses several challenges, among which the design of solar receivers to accommodate increased thermal loads is critical. To this end, this work explores and optimizes various swirl-inducing internal fin designs for solar receiver tubes. These fin designs not only improve the thermal performance of receiver tubes but also levelize temperature unevenness caused by non-uniform thermal loading. In this work, the geometric parameters of the fin designs are optimized to maximize the Nusselt number with a constraint on the friction factor. This optimization, however, is computationally intensive, requiring hundreds of simulation calls to computational fluid dynamics (CFD) models. To circumvent this problem, surrogate models are used to approximate the simulation outputs needed during the optimization. In addition, this study also examines the fin designs from an entropy generation perspective. To this end, the entropy contributions from thermal and viscous effects are quantitatively compared while varying the operational Reynolds number.

3D Printing of Solar Absorber Tube with Internal/External Structures for Heat Transfer Enhancement and Temperature Leveling using Additive Manufacturing Technology

2023-04-30

In this project, to tackle the technical obstacles, we utilized Laser Additive Alloying (LAA), an additive manufacturing (AM) technology, to 3D print the entire absorber tube with optimized helical fins to improve heat transfer at the expense of minimized pressure drop increase. The 3D printed absorber tubes can increase the uniformity of circumferential temperature distribution, reduced the thermal stresses, decrease the heat loss, and reach the target receiver thermal efficiency.