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Laser powder bed fusion (PBF‐LB) is an additive manufacturing (AM) technology for producing complex geometry parts. However, the high cost of post‐processing coarse as‐built surfaces drives the need to control surface roughness during fabrication. Prior studies have evaluated the relationship between process parameters and as‐built surface roughness, but they rely on forward models using trial‐and‐error, regression, and data‐driven methods based only on areal surface roughness parameters that neglect spatial surface characteristics. In contrast, this study introduces, for the first time, an inverse data‐centric framework that leverages machine learning algorithms and an experimental dataset of Inconel 718 as‐built surfaces to predict the PBF‐LB process parameters required to achieve a desired as‐built roughness. This inverse model shows a prediction accuracy of ≈80%, compared to 90% for the corresponding forward model. Additionally, it incorporates deterministic surface roughness parameters, which capture both height and spatial information, and significantly improves prediction accuracy compared to only using areal parameters. The inverse model provides a digital tool to process engineers that enables control of surface roughness by tailoring process parameters. Hence, it establishes a foundation for integrating surface roughness control into the digital thread of AM, thereby reducing the need for post‐processing and improving process efficiency. 

PurposeThe ability to use laser powder bed fusion (LPBF) to print parts with tailored surface topography could reduce the need for costly post-processing. However, characterizing the as-built surface topography as a function of process parameters is crucial to establishing linkages between process parameters and surface topography and is currently not well understood. The purpose of this study is to measure the effect of different LPBF process parameters on the as-built surface topography of Inconel 718 parts. Design/methodology/approachInconel 718 truncheon specimens with different process parameters, including single- and double contour laser pass, laser power, laser scan speed, build orientation and characterize their as-built surface topography using deterministic and areal surface topography parameters are printed. The effect of both individual process parameters, as well as their interactions, on the as-built surface topography are evaluated and linked to the underlying physics, informed by surface topography data. FindingsDeterministic surface topography parameters are more suitable than areal surface topography parameters to characterize the distinct features of the as-built surfaces that result from LPBF. The as-built surface topography is strongly dependent on the built orientation and is dominated by the staircase effect for shallow orientations and partially fused metal powder particles for steep orientations. Laser power and laser scan speed have a combined effect on the as-built surface topography, even when maintaining constant laser energy density. Originality/valueThis work addresses two knowledge gaps. (i) It introduces deterministic instead of areal surface topography parameters to unambiguously characterize the as-built LPBF surfaces. (ii) It provides a methodical study of the as-built surface topography as a function of individual LPBF process parameters and their interaction effects. 

Ultrasound directed self-assembly (DSA) utilizes the acoustic radiation force (ARF) associated with a standing ultrasound wave to organize particles dispersed in a fluid medium into specific patterns. The ARF is a superposition of the primary acoustic radiation force, which results from the incident standing ultrasound wave, and the acoustic interaction force, which originates from single and multiple scattering between neighboring particles. In contrast with most reports in the literature that neglect multiple scattering when calculating the ARF, we demonstrate that the deviation between considering single or multiple scattering may reach up to 100%, depending on the ultrasound DSA process parameters and material properties. We evaluate a theoretical case with three spherical particles in a viscous medium and derive operating maps that quantify the deviation between both scattering approaches as a function of the ultrasound DSA process parameters. Then, we study a realistic system with hundreds of particles dispersed in a viscous medium, and show that the deviation between the ARF resulting from single and multiple scattering increases with decreasing particle size and increasing medium viscosity, density ratio, compressibility ratio, and particle volume fraction. This work provides a quantitative basis for determining whether to consider single or multiple scattering in ultrasound DSA simulations. 

Vat photopolymerization (VP) additive manufacturing involves selectively curing low‐viscosity photopolymers via exposure to ultraviolet light in a layer‐wise fashion. Dispersing filler materials in the photopolymer enables tailored end‐use properties, but also increases the viscosity and the timescale associated with interparticle network structural recovery postshear. These rheological properties influence self‐leveling and recoating of the liquid photopolymer mixture during VP. Herein, viscosity of photopolymer and rigid spherical glass microparticles (filler) is experimentally determined as a function of filler fraction, filler size distribution (mono‐ and polydisperse), shear rate, and temperature, which are important VP process parameters. Employing existing viscosity models for mono‐ and polydisperse polymer mixtures demonstrates that particle–particle interactions and the formation of nonspherical clusters of particles strongly affect the viscosity of both monodisperse and polydisperse mixtures with particle volume fractions > 0.05 due to agglomeration/deagglomeration of clusters at elevated shear rates. Consequently, unmodified viscosity models, which assume uniformly dispersed, rigid, spherical particles, are applicable only for mixtures with particle volume fractions < 0.05. It is shown that modifying model parameters such as the fluidity limit and intrinsic viscosity, which explicitly account for nonspherical clusters of particles, improves agreement between viscosity models and experiments, in particular when using a fractal approach. 

Numerically generating synthetic surface topography that closely resembles the features and characteristics of experimental surface topography measurements reduces the need to perform these intricate and costly measurements. However, existing algorithms to numerically generated surface topography are not well-suited to create the specific characteristics and geometric features of as-built surfaces that result from laser powder bed fusion (LPBF), such as partially melted metal particles, porosity, laser scan lines, and balling. Thus, we present a method to generate synthetic as-built LPBF surface topography maps using a progressively growing generative adversarial network. We qualitatively and quantitatively demonstrate good agreement between synthetic and experimental as-built LPBF surface topography maps using areal and deterministic surface topography parameters, radially averaged power spectral density, and material ratio curves. The ability to accurately generate synthetic as-built LPBF surface topography maps reduces the experimental burden of performing a large number of surface topography measurements. Furthermore, it facilitates combining experimental measurements with synthetic surface topography maps to create large data-sets that facilitate, e.g. relating as-built surface topography to LPBF process parameters, or implementing digital surface twins to monitor complex end-use LPBF parts, amongst other applications. 

We model near-field thermal emission from metasurfaces structured as two-dimensional arrays of ellipsoidal SiC particles. The modeling approach is developed from fluctuational electrodynamics and is applicable to systems of ellipsoidal particles within the dipole limit. In all simulations, the radial lengths of particles are restricted to the range of 10–100 nm, and interparticle spacing is constrained to at least three times the particle characteristic length. The orientation and dimensions of constituent ellipsoidal particles are varied to tune localized surface phonon resonances and control the near-field energy density above metasurfaces. Results show that particle orientation can be used to regulate the relative magnitude of resonances in the energy density, and particle dimensions may be changed to adjust the frequency of these resonances within the Reststrahlen band. Metasurfaces constructed from particles with randomized dimensions display comparatively broadband thermal emission rather than the three distinct resonances seen in metasurfaces made with ellipsoidal particles of equivalent dimensions. When the interparticle spacing in a metasurface exceeds about three times the particle characteristic length, the spectral energy density above the metasurface is dominated by individual particle self-interaction and can be approximated as a linear combination of single-particle spectra. When interparticle spacing is at the lower limit of three times the characteristic length, however, multiparticle interaction effects increase and the spectral energy density above a metasurface deviates from that of single particles. This work provides guidance for designing all-dielectric, particle-based metasurfaces with desired near-field thermal emission spectra, such as thermal switches. 

Abstract Ultrasound‐directed self‐assembly (DSA) utilizes the acoustic radiation force associated with a standing ultrasound wave field to organize particles dispersed in a fluid medium into specific patterns. State‐of‐the‐art ultrasound DSA methods use single‐frequency ultrasound wave fields, which only allow organizing particles into simple, periodic patterns, or require a large number of ultrasound transducers to assemble complex patterns. In contrast, this work introduces multi‐frequency ultrasound wave fields to organize particles into complex patterns. A method is theoretically derived to determine the operating parameters (frequency, amplitude, phase) of any arrangement of ultrasound transducers, required to assemble spherical particles dispersed in a fluid medium into specific patterns, and experimentally validated for a system with two frequencies. The results show that multi‐frequency compared to single‐frequency ultrasound DSA enables the assembly of complex patterns of particles with substantially fewer ultrasound transducers. Additionally, the method does not incur a penalty in terms of accuracy, and it does not require custom hardware for each different pattern, thus offering reconfigurability, which contrasts, e.g., acoustic holography. Multi‐frequency ultrasound DSA can spur progress in a myriad of engineering applications, including the manufacturing of multi‐functional polymer matrix composite materials that derive their structural, electric, acoustic, or thermal properties from the spatial organization of particles in the matrix.