Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Multiple scattering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Results of a Geant4 benchmarking study for bio‐medical applications, performed with the G4‐Med system

Geant4, a Monte Carlo Simulation Toolkit extensively used in bio-medical physics, is in continuous evolution to include newest research findings to improve its accuracy and to respond to the evolving needs of a very diverse user community. In 2014, the G4-Med benchmarking system was born from the effort of the Geant4 Medical Simulation Benchmarking Group, to benchmark and monitor the evolution of Geant4 for medical physics applications. The G4-Med system was first described in our Medical Physics Special Report published in 2021. Results of the tests were reported for Geant4 10.5. Purpose In this work, we describe the evolution of the G4-Med benchmarking system. Methods The G4-Med benchmarking suite currently includes 23 tests, which benchmark Geant4 from the calculation of basic physical quantities to the simulation of more clinically relevant set-ups. New tests concern the benchmarking of Geant4-DNA physics and chemistry components for regression testing purposes, dosimetry for brachytherapy with a 125 I source, dosimetry for external x-ray and electron FLASH radiotherapy, experimental microdosimetry for proton therapy, and in vivo PET for carbon and oxygen beams. Regression testing has been performed between Geant4 10.5 and 11.1. Finally, a simple Geant4 simulation has been developed and used to compare Geant4 EM physics constructors and physics lists in terms of execution times. Results In summary, our EM tests show that the parameters of the multiple scattering in the Geant4 EM constructor G4EmStandardPhysics_option3 in Geant4 11.1, while improving the modeling of the electron backscattering in high atomic number targets, are not adequate for dosimetry for clinical x-ray and electron beams. Therefore, these parameters have been reverted back to those of Geant4 10.5 in Geant4 11.2.1. The x-ray radiotherapy test shows significant differences in the modeling of the bremsstrahlung process, especially between G4EmPenelopePhysics and the other constructors under study (G4EmLivermorePhysics, G4EmStandardPhysics_option3, and G4EmStandardPhysics_option4). These differences will be studied in an in-depth investigation within our Group. Improvement in Geant4 11.1 has been observed for the modeling of the proton and carbon ion Bragg peak with energies of clinical interest, thanks to the adoption of ICRU90 to calculate the low energy proton stopping powers in water and of the Linhard–Sorensen ion model, available in Geant4 since version 11.0. Nuclear fragmentation tests of interest for carbon ion therapy show differences between Geant4 10.5 and 11.1 in terms of fragment yields. In particular, a higher production of boron fragments is observed with Geant4 11.1, leading to a better agreement with reference data for this fragment. Conclusions Based on the overall results of our tests, we recommend to use G4EmStandardPhysics_option4 as EM constructor and QGSP_BIC_HP with G4EmStandardPhysics_option4, for hadrontherapy applications. The Geant4-DNA physics lists report differences in modeling electron interactions in water, however, the tests have a pure regression testing purpose so no recommendation can be formulated.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Elucidating Structural Disorder in Ultra‐Thin Bi‐Rich Bismuth Oxyhalide Photocatalysts

Abstract Advancing the field of photocatalysis requires the elucidation of structural properties that underpin the photocatalytic properties of promising materials. The focus of the present study is layered, Bi‐rich bismuth oxyhalides, which are widely studied for photocatalytic applications yet poorly structurally understood, due to high levels of disorder, nano‐sized domains, and the large number of structurally similar compounds. By connecting insights from multiple scattering techniques, utilizing electron‐, X‐ray‐ and neutron probes, the crystal phase of the synthesized materials is allocated as layered Bi 24 O 31 X 10 (X = Cl, Br), albeit with significant deviation from the reported 3D crystalline model. The materials comprise anisotropic platelet‐shaped crystalline domains, exhibiting significant in‐plane ordering in two dimensions but disorder and an ultra‐thin morphology in the layer stacking direction. Increased synthesis pH tailored larger, more ordered crystalline domains, leading to longer excited state lifetimes determined via femtosecond transient absorption spectroscopy (fs‐TAS). Although this likely contributes to improved photocatalytic properties, assessed via the photooxidation of benzylamine, increasing the overall surface area facilitated the most significant improvement in photocatalytic performance. This study, therefore, enabled both phase allocation and a nuanced discussion of the structure‐property relationship for complicated, ultra‐thin photocatalysts.

Chemistry↗
DOE OSTI2022

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗
DOE OSTI2025

Power-Capping Metric Evaluation for Improving Energy Efficiency in HPC Applications

With high-performance computing systems now running at exascale, optimizing power-scaling management and resource utilization has become more critical than ever. This paper explores runtime power-capping optimizations that leverage integrated CPU-GPU power management on architectures like the NVIDIA GH200 superchip. We evaluate energy-performance metrics that account for simultaneous CPU and GPU power-capping effects by using two complementary approaches: speedup-energy-delay and a Euclidean distance-based multi-objective optimization method. By targeting a mostly compute-bound exascale science application, the Locally Self-Consistent Multiple Scattering (LSMS), we explore challenging scenarios to identify potential opportunities for energy savings in exascale applications, and we recognize that even modest reductions in energy consumption can have significant overall impacts. Our results highlight how GPU task-specific dynamic power-cap adjustments combined with integrated CPU-GPU power steering can improve the energy utilization of certain GPU tasks, thereby laying the groundwork for future adaptive optimization strategies.

Patrou, Maria [ORNL] (ORCID:0000000339754638)↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Non-destructive measurement and real-time monitoring of apple hardness during ultrasonic contact drying via portable NIR spectroscopy and machine learning

Portable near-infrared spectrometer in the spectral range of 900–1700 nm was evaluated for the first time to assess and monitor apple hardness in real-time during ultrasonic drying. Calibration models were developed using PLS and ANN, and their performances were evaluated by internal leave-one-out cross-validation and an external dataset. Several pre-treatments including standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky–Golay first and second derivatives were employed to examine the effects of spectral variations in hardness prediction. Seven important wavelengths were selected using weighted regression coefficients to develop a simple MLR model to facilitate the model interpretation and circumvent noise. The models using PLS, MLR, and ANN with selected wavelengths predicted the apple hardness with R 2 p of 0.91, 0.91, 0.95, and RMSEP of 14.78, 14.85, and 12.46 N, respectively. Finally, the results indicate that portable NIR spectrometers are quite promising for real-time monitoring of apple hardness during ultrasonic drying.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Radiation-hard miniature optical engine with high bandwidth

Future silicon trackers will be operated in an intense radiation environment and require large volumes of data to be transmitted off detector. In addition, the optical modules must be of low mass in order to limit multiple scattering and nuclear interactions that would degrade the overall performance of the detector. Here, we present a miniature optical engine that satisfies these constraints. The optical engine consists of an ASIC driving a VCSEL (Vertical Cavity Surface Emitting Laser) array in an optical package. Two ASICs are designed to operate a 12-channel VCSEL array at 1.28 or 5.12 Gb/s per channel, which yields a total data rate of up to 60 Gb/s. The core transistors are fabricated in a 65 nm CMOS process which enhance the radiation-hardness. Each channel contains equalizer (CTLE) and clock-data recovery circuits (CDR) so that the ASIC can restore the highly distorted electrical signal after propagating through several meters of cables of small diameter. The equalizer, CDR, and VCSEL driver are configured via a digital I 2 C chip interface with triple redundant memory to mitigate single event upset (SEU) effects. The bias and modulation currents are controlled by a digital-to-analog converter (DAC). We present the design of the circuit together with the results of the simulations and preliminary measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Reproducible emission from nonlinear random lasers

Multiple scattering of light serves as a mechanism for feedback in random lasers. Consequently, internal spatial mode patterns, lasing wavelengths, and output directionality can all be random. Strong mode interaction can occur in such devices due to spatially overlapping modes resulting in nonlinearity with respect to the pump input power. Nevertheless, temporal coherence and lasing mode amplitude can be fixed at a constant pumping rate. This is a property desirable for applications where unique randomness is exploited but expected to be reliable over time, such as physical unclonable functions. Random lasers can also be cheaply and easily fabricated, exhibit relatively low lasing thresholds and high emission intensity. However, the precise scattering properties of such structures and fluctuations in the pump field can make device emission irreproducible, thereby limiting random laser applications. Here, in this work, we directly compare the random lasing spectra from zinc oxide samples fabricated in four distinct ways: spin-coating, sputtering, solgel deposition, and atomic layer deposition. The particular method of fabrication has a strong impact. Samples made through atomic layer deposition here exhibit both reproducibility and strong nonlinearity desirable for applications. Randomness in emission spectra persists across hundreds of repeated and averaged measurements irrespective of spatial location and is demonstrably nonlinear with respect to input signal intensity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Origin and Suppression of Beam Damage-Induced Oxygen-K Edge Artifact from γ-Al 2 O 3 using Cryo-EELS

Gamma-alumina (γ-Al 2 O 3 ), like other low-Z oxides, is readily damaged when exposed to an electron beam. This typically results in the formation of a characteristic pre-edge peak in the oxygen-K edge of electron energy-loss spectra (EELS) acquired during or after the damage process. This artifact can mask the presence of intrinsic O-K edge fine structure that would reveal chemical properties of the material; therefore, its suppression is key. In this work, we systematically investigate the conditions that give rise to the damage-induced O-K pre-edge peak and show that it can be effectively suppressed by performing EELS experiments at cryogenic (cryo) temperatures. Prolonged exposure of γ-Al 2 O 3 to a focused electron beam results in a hole bored through the sample; this was used as a reproducible beam damage condition. O-K edge EELS spectra were collected from a single-crystal γ-Al 2 O 3 sample both during and after focused 2 electron beam hole drilling, and at room and cryo temperatures, using a monochromated scanning transmission electron microscope (STEM). Furthermore, the characteristic 531 eV pre-edge peak visible in the room temperature EELS spectra was completely suppressed in the cryo-EELS spectra, even in the presence of a visible drilled hole. We then correlated these experimental observations with multiple-scattering EELS simulations to determine the likely atomistic origin of the damage-induced O-K pre-edge peak. The findings indicate that the pre-edge peak is caused primarily by the presence of surface O dimer (O-O) bonds formed during beam damage, and that operating at cryo temperature suppresses the formation of surface O-O bonds, thus preventing formation of the O-K pre-edge peak. Additionally, Al-L 2,3 edge EELS spectra revealed Al loss primarily from tetrahedral sites during hole drilling.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Toward accurate measurement of electromagnetic field by retrieving and refining the center position of non-uniform diffraction disks in Lorentz 4D-STEM

Recent advancement in scanning transmission electron microscopy (STEM) allows the use of 4D-STEM, a technique that captures an electron diffraction pattern at each scan point in STEM, to measure electrostatic and magnetic potential and field in materials. However, accurate measurement, separation of the magnetic and electric signals, and removal of artifacts remain challenging, especially in the presence of complex non-uniform diffraction contrast within the disks. In this work, based on dynamic simulations of 4D-STEM patterns built upon superstructures consisting of millions of atoms to account for different sample thickness and edge geometries, we show how the shape and intensity distribution of the central disk are affected by multiple scattering. We propose a robust refinement procedure through iteration of the spin-sensitive peak position of the disk-center in the circular Hough transform filtered images from experimental Lorentz 4D-STEM dataset after minimizing the possible artifacts, such as those due to the change of thickness, dynamic scattering, and scanning process. We verify that caution must be taken as in practice the rigid-disk-shift model used to reconstruct induction maps can easily break down due to disk-protrusion when there exists a nonconstant phase gradient or thickness within the width of the probe. Through quantitative analysis and comparing experiment with calculation the effect of the non-spin-related intensity distribution inside the disk as well as that causes the disk shift due to the intensity-protrusion can be removed, and high-quality magnetic field mapping is possible.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Circular dichroism in hard X-ray photoelectron diffraction observed by time-of-flight momentum microscopy

X-ray photoelectron diffraction (XPD) is a powerful technique that yields detailed structural information of solids and thin films that complements electronic structure measurements. Among the strongholds of XPD we can identify dopant sites, track structural phase transitions, and perform holographic reconstruction. High-resolution imaging of k ll -distributions (momentum microscopy) presents a new approach to core-level photoemission. It yields full-field k x -k y XPD patterns with unprecedented acquisition speed and richness in details. Here, we show that beyond the pure diffraction information, XPD patterns exhibit pronounced circular dichroism in the angular distribution (CDAD) with asymmetries up to 80%, alongside with rapid variations on a small k ll -scale (0.1 Å -1 ). Measurements with circularly-polarized hard X-rays (hν = 6 keV) for a number of core levels, including Si, Ge, Mo and W, prove that core-level CDAD is a general phenomenon that is independent of atomic number. The fine structure in CDAD is more pronounced compared to the corresponding intensity patterns. Additionally, they obey the same symmetry rules as found for atomic and molecular species, and valence bands. Further, the CD is antisymmetric with respect to the mirror planes of the crystal, whose signatures are sharp zero lines. Calculations using both the Bloch-wave approach and one-step photoemission reveal the origin of the fine structure that represents the signature of Kikuchi diffraction. To disentangle the roles of photoexcitation and diffraction, XPD has been implemented into the Munich SPRKKR package to unify the one-step model of photoemission and multiple scattering theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Semi Transparent Three-Dimensional Macroporous Quaternary Oxynitride Photoanodes for Photoelectrochemical Water Oxidation

Semi transparent three-dimensional macroporous (3DM) photoanodes based on quaternary oxynitrides have the potential to simultaneously realize superior light harvesting and efficient charge transfer in a tandem photoelectrochemical (PEC) cell. A 3DM CaTaO 2 N photoanode was prepared for the first time on a GaN/Al 2 O 3 substrate via a chemical route, and it exhibits a high transmittance of >60% in the wide solar spectrum and a photoresponse onset at −0.3 V versus the reversible hydrogen electrode (V RHE ) under simulated solar illumination. In particular, a plateau photocurrent density of 0.21 mA cm –2 was achieved at a low potential of 0.4 V RHE , which was 1.6-fold and more than 50-fold higher than a two-dimensional macroporous (2DM) CaTaO 2 N/GaN/Al 2 O 3 photoanode and a conventional particle-based CaTaO 2 N/GaN/Al 2 O 3 photoanode, respectively. The bicontinuous, interconnected pore structure within this 3DM film can improve charge carrier separation and collection by reducing the average diffusion distance for minority carriers toward the electrolyte. Optical measurements and simulations verified the enhanced sunlight harvesting in the 3DM photoanode, which was ascribed to the concentrated distribution of the electric field and multiple scattering. Furthermore, this study provides guidance for future synthesis of highly efficient semitransparent 3DM quaternary oxynitride-based photoanodes for a tandem PEC device.

Layers↗
DOE OSTI2021

Coordination Sphere of Lanthanide Aqua Ions Resolved with Ab Initio Molecular Dynamics and X-ray Absorption Spectroscopy

To resolve the fleeting structures of lanthanide Ln 3+ aqua ions in solution, we (i) performed the first ab initio molecular dynamics (AIMD) simulations of the entire series of Ln 3+ aqua ions in explicit water solvent using pseudopotentials and basis sets recently optimized for lanthanides and (ii) measured the symmetry of the hydrating waters about Ln 3+ ions (Nd 3+ , Dy 3+ , Er 3+ , Lu 3+ ) for the first time with extended X-ray absorption fine structure (EXAFS). EXAFS spectra were measured experimentally and generated from AIMD trajectories to directly compare simulation, which concurrently considers the electronic structure and the atomic dynamics in solution, with experiment. In this study, we performed a comprehensive evaluation of EXAFS multiple-scattering analysis (up to 6.5 Å) to measure Ln–O distances and angular correlations (i.e., symmetry) and elucidate the molecular geometry of the first hydration shell. This evaluation, in combination with symmetry-dependent L 3 - and L 1 -edge spectral analysis, shows that the AIMD simulations remarkably reproduces the experimental EXAFS data. The error in the predicted Ln–O distances is less than 0.07 Å for the later lanthanides, while we observed excellent agreement with predicted distances within experimental uncertainty for the early lanthanides. Our analysis revealed a dynamic, symmetrically disordered first coordination shell, which does not conform to a single molecular geometry for most lanthanides. This work sheds critical light on the highly elusive coordination geometry of the Ln 3+ aqua ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Toward a Machine Learning Approach to Interpreting X-ray Spectra of Trace Impurities by Converting XANES to EXAFS

The fact that the photoabsorption spectrum of a material contains information about the atomic structure, commonly understood in terms of multiple scattering theory, is the basis of the popular extended X-ray absorption spectroscopy (EXAFS) technique. How much of the same structural information is present in other complementary spectroscopic signals is not obvious. Here we use a machine learning approach to demonstrate that within theoretical models that accurately predict the EXAFS signal, the extended near-edge region does indeed contain the EXAFS-accessible structural information. We do this by exhibiting deep operator neural networks (DeepONets) that have learned the relationship between the extended and near edge portions of the X-ray absorption spectrum to predict the former from the latter. We find that we can accurately predict the EXAFS spectrum between 6 and 14 Å –1 from the first 6 Å –1 (≈100 eV) of the absorption spectrum of Cu 2 + substitutional defects in the Fe 3+ mineral hematite (α-Fe 2 O 3 ). This surprising finding implies that theoretical analyses of X-ray absorption spectra could be implemented that extract the same conclusions as high-quality EXAFS studies from spectra collected over a much smaller range of photon energies. This relaxes a host of experimental limitations related to the X-ray source and measurement sample, including collection time, minimum dopant concentration, source brilliance, and energy range. We describe the theoretical data sets and DeepONet construction and show that the resulting DeepONets produce EXAFS that recovers linear combination fits to experimental data with accuracy approaching the original ab initio calculations. We discuss the implications of our findings for minor constituent characterization and for understanding the information content of spectroscopic data more broadly, including how this approach might be applied to measured experimental spectra. In conclusion, to encourage similar efforts, the simulated X-ray spectra, machine learning, and fitting code are publicly available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗
DOE OSTI2024

Electron Radiation-Induced Nickel Nanoparticle Formation in KCl-ZnCl 2 Eutectic Molten Salt Using X-ray Absorption Spectroscopy

Understanding the speciation and local structure of metal solutes in molten salts is essential for predicting thermal properties and the redox and corrosion potentials of molten salts for next-generation nuclear reactors and concentrated solar power plant applications. Here, we employ X-ray absorption spectroscopy combined with electron paramagnetic resonance (EPR) measurements to investigate the effects of electron irradiation on 0.1 wt % NiCl 2 dissolved in molten eutectic KCl-ZnCl 2 salt. Radiation-driven reduction of Ni 2+ leading to nucleation and growth of Ni nanoparticles is studied as a function of electron dose (3–15 MGy) and temperature. Quantitative X-ray absorption near edge structure and linear combination fitting are utilized to investigate the extent of reduction as a function of the electron dose and temperature. A multiple-scattering (MS) approach is used for extended X-ray absorption fine structure analysis to deduce the size of the Ni nanoparticles formed and to understand the effect of the dose on the local structure of the nanoparticles. EPR studies on solidified NiCl 2 dissolved in molten eutectic KCl-ZnCl 2 salt show the formation of magnetic Ni nanoparticles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Toward Ultracold Organic Chemistry: Prospects of Laser Cooling Large Organic Molecules

Ultracold organic chemistry enables studies of reaction dynamics and mechanisms in quantum regime. Access to ultracold molecules hinges on the ability to efficiently scatter multiple photons via quasi-closed cycling transitions. Optical cycling in polyatomic molecules is challenging due to their complex electronic structure. Using equation-of-motion coupled-cluster calculations, we demonstrate that an alkaline earth metal attached to various aromatic ligands (such as benzene, phenol, cyclopentadienyl, and pyrrolide) offer nearly closed cycling transitions with only a few additional repump lasers. Here, we also show that aromatic ligands such as benzene can accommodate multiple cycling centers in various geometrical arrangements, opening new avenues in quantum information science, precision measurements, and ultracold chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Modeling Structural Colors from Disordered One-Component Colloidal Nanoparticle-Based Supraballs Using Combined Experimental and Simulation Techniques

Bright, saturated structural colors in birds have inspired synthesis of self-assembled, disordered arrays of assembled nanoparticles with varied particle spacings and refractive indices. However, predicting colors of assembled nanoparticles, and thereby guiding their synthesis, remains challenging due to the effects of multiple scattering and strong absorption. In this work, we use a computational approach to first reconstruct the nanoparticles’ assembled structures from small-angle scattering measurements and then input the reconstructed structures to a finite-difference time-domain method to predict their color and reflectance. This computational approach is successfully validated by comparing its predictions against experimentally measured reflectance and provides a pathway for reverse engineering colloidal assemblies with desired optical and photothermal properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗