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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On-PIC Light Source Integration & Micro-dispensing of Solder Paste for Flip Chip Application

To reach the next level benefits of photonic integrated circuits (PICs), the Integrated Photonic Systems Roadmap-International describes the necessity of either heterogeneous or hybrid integration of light sources [1]. A new approach for hybrid integration is Photonic Wire Bonding where 3D nanolithography is used to pattern a polymer waveguide that connects light sources to PIC waveguides. The waveguides resemble electrical wire bonds and essentially do the same as their electrical counterpart for packaging photonic chips together. In order to reap the full benefits of a photonic wire bonds, the light source must be carefully packaged. In this work I seek to expand RIT’s photonic packaging capability by establishing a packaging process to integrate light sources, specifically an Indium Phosphide distributed feedback lasers and a reflective semiconductor optical amplifiers, directly onto a photonic integrated circuits. Another necessary requirement for PIC packaging is densely integrated electrical connectivity. In this thesis I developed a fine pitch flip chip interconnect technique demonstrated using gold stud bumps in conjunction with micro-dispensed solder paste. This work opens the door to high density photonic flip chip applications. The micro-dispensed solder paste dots having diameters 50-125 µm are currently being tested at a pitch of 150 µm . The gold stud bumps are formed with 1mil gold wire creating bumps with a diameter of 40-60 µm depending on specific parameter values. These capabilities will allow RIT to assemble and test novel photonic integrated devices, cutting down on the time and cost associated with third party assembly and tests facilities. Thereby keeping RIT at the forefront of photonic research.

Wongk, Nicole↗
DOE OSTI2023

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗
DOE OSTI2022

Development of advanced machine learning models for analysis of plutonium surrogate optical emission spectra

This work investigates and applies machine learning paradigms seldom seen in analytical spectroscopy for quantification of gallium in cerium matrices via processing of laser-plasma spectra. Ensemble regressions, support vector machine regressions, Gaussian kernel regressions, and artificial neural network techniques are trained and tested on cerium-gallium pellet spectra. A thorough hyperparameter optimization experiment is conducted initially to determine the best design features for each model. The optimized models are evaluated for sensitivity and precision using the limit of detection (LoD) and root mean-squared error of prediction (RMSEP) metrics, respectively. Gaussian kernel regression yields the superlative predictive model with an RMSEP of 0.33% and an LoD of 0.015% for quantification of Ga in a Ce matrix. This study concludes that these machine learning methods could yield robust prediction models for rapid quality control analysis of plutonium alloys.

Rao, Ashwin P. (ORCID:0000000319312568)↗
DOE OSTI2020

Disassembling 2D van der Waals crystals into macroscopic monolayers and reassembling into artificial lattices

Two-dimensional materials from layered van der Waals (vdW) crystals hold great promise for electronic, optoelectronic, and quantum devices, but technological implementation will be hampered by the lack of high-throughput techniques for exfoliating single-crystal monolayers with sufficient size and high quality. Here, we report a facile method to disassemble vdW single crystals layer by layer into monolayers with near-unity yield and with dimensions limited only by bulk crystal sizes. The macroscopic monolayers are comparable in quality to microscopic monolayers from conventional Scotch tape exfoliation. The monolayers can be assembled into macroscopic artificial structures, including transition metal dichalcogenide multilayers with broken inversion symmetry and substantially enhanced nonlinear optical response. This approach takes us one step closer to mass production of macroscopic monolayers and bulk-like artificial materials with controllable properties.

Science & Technology - Other Topics↗
DOE OSTI2021

Graphene Electric Field Sensor Enables Single Shot Label-Free Imaging of Bioelectric Potentials

The measurement of electrical activity across systems of excitable cells underlies current progress in neuroscience, cardiac pharmacology, and neurotechnology. However, bioelectricity spans orders of magnitude in intensity, space, and time, posing substantial technological challenges. The development of methods permitting network-scale recordings with high spatial resolution remains key to studies of electrogenic cells, emergent networks, and bioelectric computation. Here, for this work, we demonstrate single-shot and label-free imaging of extracellular potentials with high resolution across a wide field-of-view. The critically coupled waveguide-amplified graphene electric field (CAGE) sensor leverages the field-sensitive optical transitions in graphene to convert electric potentials into the optical regime. As a proof-of-concept, we use the CAGE sensor to detect native electrical activity from cardiac action potentials with tens-of-microns resolution, simultaneously map the propagation of these potentials at tissue-scale, and monitor their modification by pharmacological agents. This platform is robust, scalable, and compatible with existing microscopy techniques for multimodal correlative imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Single-shot electro-optic sampling with arbitrary terahertz polarization

With the recent development of diversity electro-optic sampling (DEOS), significant progress has been made in the range of applicability of single-shot EOS measurements, allowing broadband THz waveforms to be captured in a single shot over large temporal windows. In addition to the decrease in acquisition time compared to standard multishot data acquisition, this technique allows measurements on systems far from equilibrium with large shot-to-shot noise or with irreversible or poorly repeatable dynamics. Although DEOS has been demonstrated and verified for linearly polarized THz waveforms, we investigate the effects resulting from the presence of a secondary polarization component. This imposes new challenges for accurate waveform reconstruction, and opens the opportunity to measure out complex polarization states such as arbitrary elliptically polarized THz field. We demonstrate a single-shot diversity-electro-optic-sampling-based approach to capture both x- and y-THz fields simultaneously with a single (110)-cut EO crystal for THz polarimetry and ellipsometry over a wide range of frequencies.

Lenz, Maximilian [University of California, Los An↗
DOE OSTI2021

Nanoscale properties of lead halide perovskites by scanning tunneling microscopy

Since the introduction of lead halide perovskites, tremendous progress has been made regarding their stability, reproducibility and durability. However, one of the issues that remains is related to the interfacial atomic structure arrangement and structure-property relationship under optical and electrical stimuli. In this critical review, we highlight the recent progress using scanning tunneling microscopy (STM) to understand the nanoscale properties and dynamic processes occurring in these halide perovskite materials. STM is known to be a very challenging technique, which is reflected by the low number of relevant publications in the last years. These initial reports mirror the unique potential of STM to give Ångstrom-scale insight into the (opto)-electronic properties, morphology and underlying electronic structure and provide a path toward harnessing the full potential of these materials. However, care must be taken to understand the effects of the perturbations caused by STM and tailor the measurement conditions accordingly.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals

Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. Here, this work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.

Industrial Internet of Things↗
DOE OSTI2020

Measurement of engine-oil fuel dilution using laser induced florescence spectroscopy

An optical diagnostic, based on laser-induced fluorescence (LIF), has been developed for on-engine measurements of real-time fuel dilution of engine oil, or fuel in oil (FiO). Fuel dilution of oil is believed to be one of the underlying mechanisms that promotes low speed pre-ignition (LSPI) during high-load engine operations. While standard (e.g., ASTM D3524-90) methods are not capable of transient measurements, the LIF technique resolves transient dilution on the minutes time scale, making it possible to study the relation between FiO and LSPI. The measurement is based on adding a dye (ca. 500 ppm) to the fuel and monitoring for its presence in the oil via LIF. The instrument contains a 532-nm laser diode, and a spectrometer to resolve the LIF spectra. A fiber-optic assembly links the instrument to the engine measurement location; the probe is in a Y-configuration with the six fibers around one on a common probe end that connects to the engine; the Y-assembly legs are connected to the instrument; the two legs are the six fibers for transporting the laser light, and the single fiber for the fluorescence. We have expanded on our previous work (Parks et al, SAE paper 2007-01-4108, 2007), by demonstrating the diagnostic technique with to measure transient oil dilution on a 2.0-liter GM ECOTEC LNF single cylinder SI engine. The proposed LIF diagnostic will be critical in studying oil-dilution correlation with LSPI events.

Neupane, Sneha↗
DOE OSTI2024

Algorithmic optimization of quantum optical storage in solids

Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and algorithmic optimization techniques to demonstrate nearly a sixfold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Published by the American Physical Society 2024

Lei, Yisheng↗
DOE OSTI2026

Embedding Fiber Optic Sensors in Stainless Steel using Spark Plasma Sintering for Structural Health Monitoring in Harsh Environments

Embedded fiber optic sensors such as fiber Bragg gratings (FBGs) offer a unique route for distributed real-time in-situ imaging of various engineering parameters for numerous purposes. This study advanced the current sensor embedding approaches by exploring a spark plasma sintering (SPS)-assisted technology to embed FBGs in high-temperature structural materials and demonstrated the capability of temperature measurement. In this approach, single-mode FBGs were integrated into stainless steel (SS) 316L components using SPS, followed by the evaluation of the bonding quality between the FBGs and matrix, the optical attenuation of the fibers induced by embedding, and the sensing characters of the FBGs under temperature stimuli. The results demonstrated that superior bonding was achieved between the FBGs and highly-densified SS316L. Examination of the behavior of Bragg gratings validated signal fidelity after embedding. Real-time thermal imaging under temperature cycling using the FBGs demonstrated the effectiveness of the technique for smart materials manufacturing.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

High finesse buckled microcavities

Optical cavities are widely used in modern science and technology to enable a wide range of both quantum and classical applications. Recently, the growing demand for miniaturization and high performance has fueled the exploration of new fabrication methods beyond traditional polishing techniques and macroscopic mirrors. Visible and near-infrared (NIR) wavelengths are particularly important for quantum applications, where achieving low-loss resonators is also more challenging than in the telecom range, presenting unique challenges and opportunities for microscopic cavity systems. Here, we present a fabrication method for making NIR microcavities using buckled dielectric membrane mirrors, achieving a record finesse of 0.9 million at 780 nm for microcavities. We demonstrated flexible device geometries—including singular mirrors and mirror arrays, featuring radii of curvature ranging from 1 to 10 mm. The fabrication process offers high uniformity, high yield, and robust performance across a wide range of cavity lengths. Additionally, we can produce easy-to-assemble microcavity packages, with a total volume of ~2(4) mm 3 , featuring optical modes with a linewidth of 5.16 MHz (570 kHz) and a free spectral range (FSR) of 3.18 THz (150 GHz). Our results extend the frontier of microcavity fabrication for classical and quantum photonic technologies.

Ding, Sophie Weiyi [Harvard Univ., Cambridge, MA (↗
DOE OSTI2021

Generalized Ellipsometry Measurements of Crystalline Thin Film and Bulk Tin Oxide

Here, several bulk and thin-film crystals of SnO2 are grown and examined using generalized ellipsometry techniques. The bulk samples are grown using the chemical vapor transport technique and thin films of SnO2 are grown using the pulsed laser deposition technique. The bulk samples are examined using the two-modulator generalized ellipsometry microscope (2-MGEM) at normal incidence and the spectroscopic two-modulator generalized ellipsometer (2-MGE). The spectroscopic optical functions of tin oxide are then obtained using the 2-MGE from 1.46 to 6.2 eV. The material is highly birefringent, and the ordinary bandgap is less than the extraordinary band edge. 2-MGE measurements are also made on thin-film samples of crystalline tin oxide grown on sapphire and rutile, showing no cross polarization. Because of the complicated morphology of the tin oxide films grown on sapphire, the ellipsometry data are simulated using the Tauc–Lorentz model. Films grown on rutile had the optic axis perpendicular to the sample surface, but the film is strained, resulting in a more complicated ellipsometric spectrum. These films are modeled using the air/surface roughness/tin oxide/interface/rutile model, where the roughness and interface are modeled using the incomplete Beta function.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Efficient Perovskite Solar Cells Achieved via Rapid Photonic Annealing of all Stacking Layers: Unveiling the Crystallization Energy Window

In this study, we report high-performance perovksite solar cells (PSCs) with rapid photonic annealing (RPA) of all stacking layers, enabled by ultraviolet (UV) light-emitting diode (LED) sources, to replace lengthy and energy-intensive thermal annealing (TA). The UV-LED annealing technique allows for layer-specific annealing, where the selected light source provides a precise UV wavelength for maximizing the amount of light absorption by the target layer. The disparity in optical absorption between the target layer and the underlying films allows the stack of the underlying films to remain relatively unaffected, making this process ideal for heating sensitive substrates. Along with a systematic investigation into the layer-specific annealing mechanism of RPA, the results demonstrated that this UV-LED-based photonic annealing of all stacking layers (7 s for perovskite absorber) can produce PSCs with the power conversion efficiency (PCE) of over 23%, the highest reported among optically annealed PSCs. Moreover, the RPA device retains over 80% of the initial PCE over 1000 h under continuous 1 sun illumination at 55 °C and 30%–60% relative humidity (RH), while TA control device drops to 50% of its initial efficiency. Furthermore, these findings represent significant strides toward achieving rapid, cost-effective, and scalable manufacturing of commercial perovskite photovoltaics (PV).

14 SOLAR ENERGY↗
DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗
DOE OSTI2022

Automated bubble analysis of high-speed subcooled flow boiling images using U-net transfer learning and global optical flow

Capturing and analyzing the bubble dynamics is crucial to improving the understanding of boiling heat transfer mechanisms and predicting boiling heat transfer coefficient and boiling crisis. High speed video (HSV) imaging has been used for decades towards this end. Still, there is no universal approach to quantitatively analyze bubble dynamics from HSV images. In this study, we propose a data-driven post-processing approach to segment, track, and identify wall-attached vapor bubbles from HSV images of the boiling process in subcooled flow conditions. Firstly, we employ a transfer learning framework with a U-Net-based convolution neural network (CNN) architecture to detect and segment bubbles in HSV images of diverse contrast and surface texture using very little data (e.g., 10 images) for training. Then, we evaluate the trained CNN model with 100 ground-truth images, and the validation results show that the model accuracy and precision in detecting the optical footprint of bubbles are higher than 90%. Finally, we suggest a criterion to identify a condensing bubble based on the divergence of the bubble displacement, which is calculated from sequential segmented bubble images using a global optical flow code. Using this combination of machine learning and optical flow, we can identify nucleation sites and track the growth of bubbles nucleating at each site to quantify nucleation site density, nucleation frequency, and other fundamental boiling parameters. The proposed system is validated using results obtained on a special heater, which enables both infrared (IR) thermometry and HSV imaging on a metallic surface. We compare the fundamental boiling parameters obtained by the two different diagnostics. The results show good agreement. In conclusion, the difference between the measurements of nucleation site density, averaged nucleation frequency, and averaged growth time performed with the two techniques is always within ± 20% and mostly ± 10% of the values measured with IR thermometry.

42 ENGINEERING↗
DOE OSTI2020

Electro-chemo-mechanical evolution of sulfide solid electrolyte/Li metal interfaces: operando analysis and ALD interlayer effects

Sulfide solid electrolytes (SE) show promise for high-performance solid-state batteries because of their high ionic conductivity and ease of processing. However, sulfide electrolytes have suffered from chemical and electrochemical instability against Li metal anodes. In this paper, we use a suite of in situ/operando microscopy and spectroscopy techniques to demonstrate that Al 2 O 3 interlayers deposited using atomic layer deposition (ALD) delay degradation at the Li/LGPS interface by modifying the solid electrolyte interphase (SEI) chemistry and morphology. Optical and scanning electron microscopy are used to rationalize the electrochemical response of the system, which is attributed to a delayed onset of mechanical degradation at the interface when ALD interlayers are used. Operando X-ray photoelectron spectroscopy demonstrates that the dynamic evolution of SEI chemistry is impacted by the presence of the ALD interlayer. In situ Auger spectroscopy and operando optical microscopy provide visual evidence of spatial heterogeneity of Li plating, which is attributed to the chemo-mechanical degradation of the ALD interphase. The implications of these observations provide valuable insights toward the development of robust interlayers for solid-state batteries.

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

Element differentiation with a Hartmann- based X-ray phase imaging system

Significant efforts are currently ongoing in X-ray imaging to provide multimodal imaging systems, targeting better sensitivity and specificity for both biomedical or non-destructive testing applications. Knowing the elemental composition of specific structures, such as breast microcalcifications in mammography, would help to differentiate malign and benign tumours. Standard X-ray Phase Contrast Imaging techniques provide only qualitative information on elements with similar absorption properties. However, their chemical composition can be determined from the measurement of the phase as it is directly related to the optical index of elemental materials. We will show new experimental results obtained with an X-ray phase imaging system based on a Hartmann mask. Early data treatment succeeded in retrieving both the real and imaginary parts of the refractive index. The system demonstrates the capability to discriminate materials based on elemental composition.

36 MATERIALS SCIENCE↗