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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.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Bubble explosion induced melt pool instabilities in electron beam melting of aluminum alloy

Electron beam melting (EBM) is an additive manufacturing technology that can process materials and manufacture components otherwise impossible or uneconomical. However, defects, including porosity and surface irregularities, are widely reported in EBM-built components, and their formation mechanisms are not fully understood. Here, using in-situ high-speed synchrotron X-ray imaging, we reveal that bubble explosions in Al6061 during EBM induce melt pool instabilities contributing to defect formation. The melt pool and keyhole evolve through three stages: (1) initial formation of a melt pool, (2) subsurface bubble formation and explosion, and (3) periodic keyhole oscillation. During scanning, periodic bubble explosions can eject molten liquid as spatters and disturb the vapor depression and melt pool, contributing to surface humping, that may trigger lack-of-fusion defects in subsequent layers. The physical insights we report could provide guidance for EBM machine development, process innovation, alloy design and model development.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Photoswitching dynamics of a guanidine anion receptor

Photoswitchable molecules involving large-scale structural changes such as E/Z photoisomerization offer remarkable opportunities for light-stimulated catch-and-release chemical separations. While the feasibility of this photochemically driven mechanism has been demonstrated in pioneering studies, the electronic excited-state relaxation processes and concomitant structural changes of such a functional photoswitcher remain largely unexplored. Here, we investigate an exceptional photoswitchable molecule, 2-pyridyl-diiminoguanidinium (2PyDIG), which exhibits strong and selective anion binding, along with an extraordinary capability for light-induced release of a guest ion. Through time-resolved fluorescence measurements and multireference and time-dependent density functional theory calculations, we reveal the dynamics underlying electronic excited state relaxation and photoisomerization central to photoswitching. A very rapid and dominant decay component was found that is consistent with radiationless de-excitation from S 1 to S 0 through conical intersections. This process competes effectively with the slower photoisomerization process taking place in 94 ps. We further identified the underlying causes through theoretical calculations and potential routes towards improved photoisomerization efficiencies.

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

Anion photoelectron spectroscopy and chemical bonding of ThS 2 – and ThSO –

Anion photoelectron spectra of ThSO – and ThS 2 – were recorded using the third (355 nm) harmonic of an Nd-YAG laser; these provided the measured vertical detachment energies of each anion. The experiments are supported by extensive coupled cluster calculations on ThSO, ThSO – , ThS 2 , and ThS 2 – , as well as the oxygen congeners ThO 2 and ThO 2 – . The ab initio calculations, which included complete basis set extrapolations, spin–orbit effects using four-component coupled cluster, and higher-order correlation contributions through CCSDT(Q), yielded an adiabatic electron affinity for ThO 2 – that was within 0.02 eV of the previously determined experimental value. The singly occupied molecular orbital (SOMO) in all three anions corresponds primarily to the 7s orbital on Th. Successive substitution of S for each O in ThO 2 leads to larger electron affinities and smaller bond angles in the neutral molecules, but larger angles in the anions. As demonstrated by Franck–Condon simulations of the spectra using the CCSD(T) spectroscopic constants, substitution of O by S significantly complicates the resulting detachment spectra due to the lower vibrational frequencies in the sulfur species. Altogether the calculated vertical detachment energies are in very good agreement with the experiment. In addition to the adiabatic electron affinities of each species, atomization energies and heats of formation have also been determined via the FPD approach with expected uncertainties of 1–2 kcal/mol.

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

X-ray optics for the cavity-based X-ray free-electron laser

A cavity-based X-ray free-electron laser (CBXFEL) is a possible future direction in the development of fully coherent X-ray sources. CBXFELs consist of a low-emittance electron source, a magnet system with several undulators and chicanes, and an X-ray cavity. The X-ray cavity stores and circulates X-ray pulses for repeated FEL interactions with electron pulses until the FEL reaches saturation. CBXFEL cavities require low-loss wavefront-preserving optical components: near-100%-reflectivity X-ray diamond Bragg-reflecting crystals, outcoupling devices such as thin diamond membranes or X-ray gratings, and aberration-free focusing elements. In the framework of the collaborative CBXFEL research and development project of Argonne National Laboratory, SLAC National Accelerator Laboratory and SPring-8, we report here the design, manufacturing and characterization of X-ray optical components for the CBXFEL cavity, which include high-reflectivity diamond crystal mirrors, a diamond drumhead crystal with thin membranes, beryllium refractive lenses and channel-cut Si monochromators. All the designed optical components have been fully characterized at the Advanced Photon Source to demonstrate their suitability for the CBXFEL cavity application.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Extending JuTrack’s capabilities to the FRIB accelerator to enhance online modeling

JuTrack is a Julia-based accelerator modeling and tracking package that utilizes compiler-level automatic differentiation (AD) to enable fast and accurate derivative calculations. While JuTrack provides a solid foundation for beam dynamics simulations, its capabilities must be extended to support the Facility for Rare Isotopes (FRIB) linac. This includes modeling heavy-ion linac accelerator components such as the liquid-lithium charge stripper, which facilitates efficient acceleration by remove electrons from heavy isotopes, and incorporating multi-charge state acceleration tracking, which allows for charge-dependent beam dynamics. These extensions address challenges such as the beam matching and optimization of multi charge state through various accelerating structures and beam-material interaction modeling while maintaining the auto differentiation capability. This work focuses on adapting JuTrack to incorporate these elements, enhancing its online modeling abilities. We present modifications to JuTrack’s framework and demonstrate their performance in FRIB simulations.

Accelerator Physics↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
DOE OSTI2025

An electro-optical Mott neuron based on niobium dioxide

Various applications—including brain-like computing and on-chip artificial vision—increasingly demand a combination of electronic and photonic techniques. However, integrating both approaches on a single chip is challenging, and solutions typically rely on disparate components with power-hungry signal conversions. Here, in this paper, we report electro-optical Mott neurons that combine visible light emission with electrical threshold switching, as well as neuron-like oscillations. The devices are based on thin films of sputtered niobium dioxide (NbO 2 ), a Mott insulator–metal transition material, operating at room temperature and emitting light that peaks around 810 nm. Operando measurements reveal an electronic origin to the light emission: charge carrier relaxation initiated by high-field transport in the NbO 2 . Our devices combine electrical and optical functions within a single material, thereby expanding the options available for future artificial intelligence hardware.

electrical engineering↗
DOE OSTI2025

Microscopic signatures of topology in twisted MoTe 2

In moiré materials with flat electronic bands and suitable quantum geometry, strong correlations can give rise to various topological states of matter. The non-trivial band topology of twisted MoTe 2 , which is responsible for its fractional quantum anomalous Hall states, is predicted to arise from a skyrmion lattice texture in the layer pseudospin of the electronic wavefunctions. Tracing the layer polarization of wavefunctions within the moiré unit cell can, thus, offer insights into the band topology. Here we measure the out-of-plane component of the layer-pseudospin skyrmion textures of twisted MoTe 2 using scanning tunnelling microscopy and spectroscopy. We do this by simultaneously visualizing the moiré lattice structure and the spatial localization of its electronic states. We find that the wavefunctions associated with the topological flat bands exhibit a spatially dependent layer polarization within the moiré unit cell, in agreement with our theoretical modelling. Furthermore, our work enables future local probe studies of the intertwined correlated and topological states arising in gate-tunable devices.

Electronic properties and materials↗
DOE OSTI2024

ELECTRONIC STRUCTURE METHODS AND PROTOCOLS WITH APPLICATION TO DYNAMICS, KINETICS AND THERMOCHEMISTRY

Hydrocarbon combustion involves the reaction dynamics of a tremendous number of species beginning with many-component fuel mixtures and proceeding via a complex system of intermediates to form primary and secondary products. Combustion conditions corresponding to new advanced engines and/or alternative fuels rely increasingly on autoignition and low-temperature-combustion chemistry. In these regimes various transient radical species such as HO2, ROO·, ·QOOH, HCO, NO2, HOCO, and Criegee intermediates play important roles in determining the detailed as well as more general dynamics. A clear understanding and accurate representation of these processes is needed for effective modeling. Given the difficulties associated with making reliable experimental measurements of these systems, computation can play an important role in developing these energy technologies. Accurate calculations have their own challenges since even within the simplest dynamical approximations such as transition state theory, the rates depend exponentially on critical barrier heights and these may be sensitive to the level of quantum chemistry. Moreover, it is well-known that in many cases it is necessary to go beyond statistical theories and consider the dynamics. Quantum tunneling, resonances, radiative transitions, and non-adiabatic effects governed by spin-orbit or derivative coupling can be determining factors in those dynamics. Building upon progress made during a period of prior support through the DOE Early Career Program, this project combines developments in the areas of potential energy surface (PES) fitting and multistate multireference quantum chemistry to allow spectroscopically and dynamically/kinetically accurate investigations of key molecular systems (such as those mentioned above), many of which are radicals with strong multireference character and have the possibility of multiple electronic states contributing to the observed dynamics. An ongoing area of investigation is to develop general strategies for robustly convergent electronic structure theory for global multichannel reactive surfaces including diabatization of energy and other relevant surfaces such as dipole transition. Combining advances in ab initio methods with automated interpolative PES fitting allows the construction of high-quality PESs (incorporating thousands of high-level data) to be done rapidly through parallel processing on high-performance computing (HPC) clusters. In addition, new methods and approaches to electronic structure theory will be developed and tested through applications. This project will explore limitations in traditional multireference calculations (e.g., MRCI) such as those imposed by internal contraction, lack of high-order correlation treatment and poor scaling. Methods such as DMRG-based extended active-space CASSCF and various Quantum Monte Carlo (QMC) methods will be applied (including VMC/DMC and FCIQMC). Insight into the relative significance of different orbital spaces and the robustness of application of these approaches on leadership class computing architectures will be gained. Synergy with other components of this research program such as automated PES fitting and multireference quantum chemistry will be used to address challenges encountered by the standard approaches to computational thermochemistry (those being single-reference quantum chemistry and perturbative treatments of the anharmonic vibrational energy, which break down for some cases of electronic structure or floppy strongly coupled vibrational modes).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Mechanistic Insights into Dinitrogen Reduction to Ammonia in Light-Controlled Nanocrystal:Nitrogenase Complexes

Developing systems that can efficiently capture photon energy and convert this energy into fuels and chemicals requires understanding how to assemble molecular components with diverse functions into complete systems possessing selectivity and efficiency in directing charge carriers to catalytic reactions. There are many challenges to achieving this goal. One promising approach is the development of hybrid systems that combine semiconductor nanocrystals (NCs) for light capture and enzymes as efficient catalysts. Such biohybrid systems capitalize on the tunable electronic and optical properties of NCs while leveraging the unmatched specificity and efficiency of enzymes in catalyzing chemical reactions, thereby offering opportunities to surpass the limitations of each component alone. Here, we focus on recent progress in developing a biohybrid system that combines CdS NCs for photon capture with the enzyme nitrogenase to accomplish light-driven dinitrogen (N 2 ) reduction to ammonia (NH 3 ). Integrating light-harvesting materials with biological catalysts requires a deep understanding of NC properties, protein stability, and electron transfer (ET), making it an inherently multidisciplinary problem. The reduction of N 2 to NH 3 is a challenging reaction, with a high demand in both agriculture and industrial chemical production. This reaction is intrinsically energy intensive, due to the need to activate the N≡N triple bond. The current standard industrial approach to N 2 reduction, the Haber−Bosch reaction, obtains the necessary energy input from fossil fuels, whereas biological systems capable of N 2 reduction utilize the hydrolysis of ATP as their energy source. Replacing these costly, energy-intensive inputs with renewable light energy represents a critical step toward sustainable NH 3 production. Recent progress has demonstrated that semiconductor CdS NCs can be coupled to the catalytic component of nitrogenase, the MoFe protein, to form a biohybrid CdS NC:MoFe protein complex, enabling light-driven N 2 reduction rather than energy input from fossil fuels or ATP. This illustrates how inorganic NCs can functionally replace the natural Fe protein partner, yielding a biohybrid catalyst that enables controlled electron delivery and provides not only light-driven NH 3 production but also new approaches for probing enzyme catalytic function. The CdS NC:MoFe protein biohybrid system enables light-initiated electron delivery at ambient temperature, as well as temperatures below freezing, allowing for stabilization and spectroscopic characterization of key reaction intermediates. These findings highlight how photochemical biohybrids can serve as both functional catalysts and mechanistic probes. Beyond studies of the nitrogenase mechanism, studies of the CdS NC:MoFe system reveal how variables such as NC size, electrostatic binding interactions, and sacrificial electron donors (SEDs) govern complex stability, charge transfer efficiency, and catalytic performance. In addition, studies of nitrogenase and the high activation barrier for N 2 reduction are enabling investigations of new and interesting questions regarding the properties and limitations of NC biocatalysis. In this Account, we describe the key features of CdS NC:MoFe protein biohybrids and the parameters for optimal light-driven N 2 reduction, and how controlling ET with light illuminates the path to new insights into the nitrogenase mechanism.

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

SINGLE BUNCH TRACKING ON THE TEN-PASS ER@CEBAF ENERGY RECOVERY BEAMLINE

The proposed ten-pass energy recovery linac (ERL) demonstration (five accelerating, five decelerating) at the CEBAF accelerator, ER@CEBAF, involves a multi-GeV en- ergy range of a continuous electron beam. New CEBAF transverse optics were designed for this ERL demonstration. This redesign incorporates additional components in Arc A, including a path length chicane and new quadrupoles to ensure proper dispersion localization. The new five energy recovery passes with a shared arc transport scheme chal- lenge the overall beamline optics design, including large beta functions in the CEBAF spreaders and recombiners. Here we discuss results of bunch tracking performed using the elegant tracking code for the full ER@CEBAF beamline

Neththikumara, I.↗
DOE OSTI2024

Integrated Traction Drive Thermal Management: Keystone Project 3

The presentation represents a report of accomplishments during FY 2024 and is prepared for 2024 DOE VTO Annual Merit Review. The project goal is identifying pathways enabling high-performance, compact, and reliable integrated electric drives and facilitation of achieving DOE 2025 target of 33 kW/L system power density for an electric traction drive through support of other EDT consortium members in design and development of thermal management systems for their respective integrated drive concepts. Specific objectives are: 1) research and evaluation of motor-integrated power electronics packaging technologies and thermal management approaches; 2) explore novel materials and manufacturing options (3D printing with thermally enhanced polymers or ceramic materials) for key thermal management system components; 3) develop thermal management system and its sub-components to enable integrated electric drive DOE power density targets in collaboration with project partners; 4) support activities of DOE's Electric Drive Technologies (EDT) consortium members, Oak Ridge National Laboratory (ORNL), University of Wisconsin and Georgia Tech research teams in thermal management component design and thermal modeling of their integrated traction drives.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗
DOE OSTI2024

Regulation of Solar Wind Electron Temperature Anisotropy by Collisions and Instabilities

Abstract Typical solar wind electrons are modeled as being composed of a dense but less energetic thermal “core” population plus a tenuous but energetic “halo” population with varying degrees of temperature anisotropies for both species. In this paper, we seek a fundamental explanation of how these solar wind core and halo electron temperature anisotropies are regulated by combined effects of collisions and instability excitations. The observed solar wind core/halo electron data in ( β ∥ , T ⊥ / T ∥ ) phase space show that their respective occurrence distributions are confined within an area enclosed by outer boundaries. Here, T ⊥ / T ∥ is the ratio of perpendicular and parallel temperatures and β ∥ is the ratio of parallel thermal energy to background magnetic field energy. While it is known that the boundary on the high- β ∥ side is constrained by the temperature anisotropy-driven plasma instability threshold conditions, the low- β ∥ boundary remains largely unexplained. The present paper provides a baseline explanation for the low- β ∥ boundary based upon the collisional relaxation process. By combining the instability and collisional dynamics it is shown that the observed distribution of the solar wind electrons in the ( β ∥ , T ⊥ / T ∥ ) phase space is adequately explained, both for the “core” and “halo” components.

Yoon, Peter H. (ORCID:0000000181343790)↗
DOE OSTI2026

Path integral molecular dynamics: A high-fidelity approach to quantum dynamics of electrons

We investigate electron transport in the uniform electron gas using ring-polymer molecular dynamics (RPMD). Working in the weakly coupled, non-degenerate regime, we use RPMD to probe how the onset of quantum diffraction effects at high temperature reshapes electron–electron collisions and leads to a classical-to-quantum crossover in macroscopic transport properties. Static thermodynamics obtained with RPMD are consistent with the weak-coupling equation of state, confirming correct quantum Boltzmann sampling. Real-time transport extracted from mean square displacements exhibits the expected ballistic-to-diffusive transition and a systematic reduction of the electronic self-diffusivity as quantum effects strengthen, due to quantum diffraction modifying electron–electron collisions. Direct ring-polymer scattering simulations reveal diffractive “softening” of binary deflections, providing a micro-to-macro link between collision physics and diffusion. The present study establishes RPMD as a quantitative, trajectory-based tool for electron transport across the classical–quantum crossover and furnishes benchmarks for improving Coulomb-log interpolation models. We outline extensions to multi-component plasmas and a path to incorporate Fermi–Dirac statistics within path-integral dynamics.

Electronic transport↗
DOE OSTI2024

Interface-modulated kinetic differentials in electron and hole transfer rates as a key design principle for redox photocatalysis by Sb2VO5/QD heterostructures

The efficient conversion of solar energy to chemical energy represents a critical bottleneck to the energy transition. Photocatalytic splitting of water to generate solar fuels is a promising solution. Semiconductor quantum dots (QDs) are prime candidates for light-harvesting components of photocatalytic heterostructures, given their size-dependent photophysical properties and band-edge energies. A promising series of heterostructured photocatalysts interface QDs with transition-metal oxides which embed midgap electronic states derived from the stereochemically active electron lone pairs of p-block cations. Here, we examine the thermodynamic driving forces and dynamics of charge separation in Sb2VO5/CdSe QD heterostructures, wherein a high density of Sb 5s2-derived midgap states are prospective acceptors for photogenerated holes. Hard-x-ray valence band photoemission spectroscopy measurements of Sb2VO5/CdSe QD heterostructures were used to deduce thermodynamic driving forces for charge separation. Interfacial charge transfer dynamics in the heterostructures were examined as a function of the mode of interfacial connectivity, contrasting heterostructures with direct interfaces assembled by successive ion layer adsorption and reaction (SILAR) and interfaces comprising molecular bridges assembled by linker-assisted assembly (LAA). Transient absorption spectroscopy measurements indicate ultrafast (<2 ps) electron and hole transfer in SILAR-derived heterostructures, whereas LAA-derived heterostructures show orders of magnitude differentials in the kinetics of hole (<100 ps) and electron (∼1 ns) transfer. The interface-modulated kinetic differentials in electron and hole transfer rates underpin the more effective charge separation, reduced charge recombination, and greater photocatalytic efficiency observed for the LAA-derived Sb2VO5/CdSe QD heterostructures.

Chemistry↗
DOE OSTI2025

Multiphoton and Harmonic Imaging of Microarchitected Materials

Microadditive manufacturing has revolutionized the production of complex, nano- to microscale components across various fields. This work investigates two-photon (2P) and three-photon (3P) fluorescence imaging, as well as third-harmonic generation (THG) microscopy, to examine periodic microarchitected lattice structures fabricated using multiphoton lithography (MPL). By immersing the structures in refractive index matching fluids, we demonstrate high-fidelity 3D reconstructions of both fluorescent structures using 2P and 3P microscopy as well as low-fluorescence structures using THG microscopy. These results show that multiphoton fluorescence (MPF) imaging offers reduced signal decay with respect to depth compared to single-photon techniques in the examined structures. We further demonstrate the ability to nondestructively identify intentional internal modifications of the structure that are not immediately visible with scanning electron microscope (SEM) images and compression-induced fractures, highlighting the potential of these techniques for quality control and defect detection in microadditively manufactured components.

36 MATERIALS SCIENCE↗