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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Acoustic Travel-Time Tomography for Wind Energy

New remote sensing technologies for direct observation of the atmospheric flow in the proximity of operating wind turbines are necessary for the advancement of wind turbine design, wind plant control, and the validation of high-fidelity numerical models; fundamental goals of the DOE Wind Energy Technology Office's (WETO's) A2e program. Modern remote sensing technologies for commercial and research applications rely on the backscatter of light or sound waves, which limits spatial and temporal resolution and cannot produce reliable flow estimates near solid bodies or reflective surfaces. Acoustic tomography (AT) is an innovative sensing technology based on fundamental thermodynamic properties of the atmosphere and an inverse algorithm that can reconstruct both velocity and temperature fields within a network of acoustic transducers. AT relies on the direct travel path of acoustic signals between speakers and microphones in the network and can achieve much higher resolutions than conventional backscatter technologies. For wind energy R&D applications, AT represents an extremely economical option over other remote sensing technologies, integrating mature and commonly available acoustic and signal processing hardware. This report is intended as an update on the development of the AT array on the NREL Flatirons Campus (FC) and includes a brief review of the instrumentation, the calibration of equipment, signal processing, and resulting flow field estimates. Designs for future AT systems and applications are detailed in this report, including summaries of new capabilities, engineering and theoretical challenges, and anticipated costs help to outline future directions for AT technology R\&D. The potential for application of AT to utility-scale turbines is also discussed. Investing in the development of the proposed instrument will establish AT as a transformational RS technique that represents a significant advance in measurement instrumentation, enabling new fundamental insights into the structure of the atmospheric boundary layer and supporting applications for wind energy, pollution transport, and resource characterization. AT is also an extremely economical option over other RS instruments, integrating mature and commonly available acoustic and signal processing hardware.

17 WIND ENERGY↗
DOE OSTI2025

High Aspect Ratio OLEDs

Long-term reliability is especially challenging for organic light emitting diodes (OLEDs) used in solid-state lighting applications because OLED lifetime is inversely proportional to luminance, and most lighting applications demand high luminance. This project explored a new strategy to overcome this tradeoff by constructing OLEDs on a substrate with sub-mm, high aspect ratio surface texture. By creating more active OLED area per unit lighting panel area, the device current density required to generate a given panel luminance decreases. We validated this approach for both fluorescent and phosphorescent OLEDs, demonstrating good thickness uniformity on corrugated substrates with area enhancement factors up to 1.4x using a standard thermal evaporator. Relative to planar controls at the same panel current density, the high aspect ratio devices achieve a 2.7-fold increase in operating lifetime and up to a 40% increase in external light extraction efficiency. Experiments carried out on a pilot-line OLED manufacturing system demonstrated good coating uniformity, indicating that this approach has the potential to be implemented at scale and therefore offers a powerful pathway to improve the efficiency and lifetime of OLED lighting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

CLASSY III. The Properties of Starburst-driven Warm Ionized Outflows

We report the results of analyses of galactic outflows in a sample of 45 low-redshift starburst galaxies in the COS Legacy Archive Spectroscopic SurveY (CLASSY), augmented by five additional similar starbursts with Cosmic Origins Spectrograph (COS) data. The outflows are traced by blueshifted absorption lines of metals spanning a wide range of ionization potential. The high quality and broad spectral coverage of CLASSY data enable us to disentangle the absorption due to the static interstellar medium (ISM) from that due to outflows. We further use different line multiplets and doublets to determine the covering fraction, column density, and ionization state as a function of velocity for each outflow. We measure the outflow's mean velocity and velocity width, and find that both correlate in a highly significant way with the star formation rate, galaxy mass, and circular velocity over ranges of four orders of magnitude for the first two properties. We also estimate outflow rates of metals, mass, momentum, and kinetic energy. We find that, at most, only about 20% of silicon created and ejected by supernovae in the starburst is carried out in the warm phase we observe. The outflows' mass-loading factor increases steeply and inversely with both circular and outflow velocity (log–log slope ~–1.6), and reaches ~10 for dwarf galaxies. We find that the outflows typically carry about 10%–100% of the momentum injected by massive stars and about 1%–20% of the kinetic energy. We show that these results place interesting constraints on, and new insights into, models and simulations of galactic winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Spatially and temporally resolved plasma parameter estimations of laser heated MagLIF relevant gas pipes at NIF

The ability to control laser pre-heat is an integral part of the inertial confinement fusion concept known as Magnetized Liner Inertial Fusion. This process is studied at the National Ignition Facility (NIF) where 4 of the 192 laser beams are propagated through a 1-cm long gas cell where they deposit >20 kJ of energy into the gaseous fuel via inverse bremsstrahlung absorption. This process ionizes the gas, producing a plasma that follows behind the laser front and expands over the radius of the cell. Emission from this plasma, as viewed by a gated x-ray detector, can be used to build spatially and temporally resolved estimations of the pre-heat plasma's density and temperature profiles. This can then be used to estimate the plasma pressure, internal energy, and radiation losses. Estimations show the evolution of the plasma in magnetized and unmagnetized gas cells filled with ambient temperature neopentane (C5H12) +1% Ar, as well as unmagnetized cryogenically cooled (32 K) deuterium +1% Ne filled targets. This analysis shows the effects of initial gas-fill density, composition, and axial magnetization on the time-dependent plasma parameters. Previously, these parameters at the NIF had not been experimentally characterized, and these estimations provided a potential new means of testing radiation magneto-hydrodynamic predictive capability models. Results in unmagnetized targets have strong agreement with simulations. However, in targets with a 19 T applied axial magnetic field, this method yields electron temperatures up to 100% hotter than those predicted by HYDRA codes.

Bremsstrahlung↗
DOE OSTI2022

Impact of the built, social, and food environment on long‐term weight loss within a behavioral weight loss intervention

Abstract Background Behavioral weight loss interventions can lead to an average weight loss of 5%–10% of initial body weight, however there is wide individual variability in treatment response. Although built, social, and community food environments can have potential direct and indirect influences on body weight (through their influence on physical activity and energy intake), these environmental factors are rarely considered as predictors of variation in weight loss. Objective Evaluate the association between built, social, and community food environments and changes in weight, moderate‐to‐vigorous physical activity (MVPA), and dietary intake among adults who completed an 18‐month behavioral weight loss intervention. Methods Participants included 93 adults (mean ± SD; 41.5 ± 8.3 years, 34.4 ± 4.2 kg/m 2 , 82% female, 75% white). Environmental variables included urbanicity, walkability, crime, Neighborhood Deprivation Index (includes 13 social economic status factors), and density of convenience stores, grocery stores, and limited‐service restaurants at the tract level. Linear regressions examined associations between environment and changes in body weight, waist circumference (WC), MVPA (SenseWear device), and dietary intake (3‐day diet records) from baseline to 18 months. Results Grocery store density was inversely associated with change in weight ( β = −0.95; p = 0.02; R 2 = 0.062) and WC ( β = −1.23; p < 0.01; R 2 = 0.109). Participants living in tracts with lower walkability demonstrated lower baseline MVPA and greater increases in MVPA versus participants with higher walkability (interaction p = 0.03). Participants living in tracts with the most deprivation demonstrated greater increases in average daily steps ( β = 2048.27; p = 0.02; R 2 = 0.039) versus participants with the least deprivation. Limited‐service restaurant density was associated with change in % protein intake ( β = 0.39; p = 0.046; R 2 = 0.051). Conclusion Environmental factors accounted for some of the variability (<11%) in response to a behavioral weight loss intervention. Grocery store density was positively associated with weight loss at 18 months. Additional studies and/or pooled analyses, encompassing greater environmental variation, are required to further evaluate whether environment contributes to weight loss variability.

Tewahade, Selam↗
DOE OSTI2021

Potential Activities and Long Lifetimes of Organic Carbon-Degrading Extracellular Enzymes in Deep Subsurface Sediments of the Baltic Sea

Heterotrophic microorganisms in marine sediments produce extracellular enzymes to hydrolyze organic macromolecules, so their products can be transported inside the cell and used for energy and growth. Therefore, extracellular enzymes may mediate the fate of organic carbon in sediments. The Baltic Sea Basin is a primarily depositional environment with high potential for organic matter preservation. The potential activities of multiple organic carbon-degrading enzymes were measured in samples obtained by the International Ocean Discovery Program Expedition 347 from the Little Belt Strait, Denmark, core M0059C. Potential maximum hydrolysis rates (V max ) were measured at depths down to 77.9mbsf for the following enzymes: alkaline phosphatase, β- d -xylosidase, β- d -cellobiohydrolase, N-acetyl-β- d -glucosaminidase, β-glucosidase, α-glucosidase, leucyl aminopeptidase, arginyl aminopeptidase, prolyl aminopeptidase, gingipain, and clostripain. Extracellular peptidase activities were detectable at depths shallower than 54.95mbsf, and alkaline phosphatase activity was detectable throughout the core, albeit against a relatively high activity in autoclaved sediments. β-glucosidase activities were detected above 30mbsf; however, activities of other glycosyl hydrolases (β-xylosidase, β-cellobiohydrolase, N-acetyl-β-glucosaminidase, and α-glucosidase) were generally indistinguishable from zero at all depths. These extracellular enzymes appear to be extremely stable: Among all enzymes, a median of 51.3% of enzyme activity was retained after autoclaving for an hour. We show that enzyme turnover times scale with the inverse of community metabolic rates, such that enzyme lifetimes in subsurface sediments, in which metabolic rates are very slow, are likely to be extraordinarily long. A back-of-the-envelope calculation suggests enzyme lifetimes are, at minimum, on the order of 230days, and may be substantially longer. These results lend empirical support to the hypothesis that a population of subsurface microbes persist by using extracellular enzymes to slowly metabolize old, highly degraded organic carbon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Why matter effects matter for JUNO

In this paper we focus on the Earth matter effects for the solar parameter determination by a medium baseline reactor experiment such as JUNO. We derive perturbative expansions for the mixing angles θ 12 and θ 13 as well as the Δm$^{2}_{21}$ and Δm$^{2}_{31}$ in terms of the matter potential relevant for JUNO. These expansions, up to second order in the matter potential, while simple, allow one to calculate the electron antineutrino survival probability to a precision much better than needed for the JUNO experiment. We use these perturbative expansions to semi-analytically explain and confirm the shift caused by the matter effects on the solar neutrino mixing parameters θ 12 and Δm$^{2}_{21}$ which were previously obtained by a purely numerical χ 2 analysis. Since these shifts do not satisfy the naive expectations and are significant given the precision that can be achieved by the JUNO experiment, a totally independent cross check using a completely different method is of particular importance. We find that these matter effect shifts do not depend on any of the details of the detector characteristics apart from the baseline and earth mass density between reactor(s) and detector, but do depend on the normalized product of reactor neutrino spectrum times the inverse-beta decay cross-section. The results of this manuscript suggests an alternative analysis method for measuring sin 2 θ 12 and Δm$^{2}_{21}$ in JUNO which would be a useful cross check of the standard analysis and for the understanding of the Wolfenstein matter effect. The explanation of these shifts together with a quantitative understanding, using a semi-analytical method, is the principal purpose of this paper.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Theory for transport in magnetized plasmas

We present a two fluid model for anomalous thermal, particle and momentum transport which has been derived from kinetic theory using a small parameter ε~10-2. This small parameter can come from either the ratio of wave frequency to cyclotron frequency or the ratio of potential to thermal energies. This fluid model is strongly nonlinear and has an exact closure within the accuracy ε. It can be used to simulate the full radius of a tokamak including internal and edge transport barriers at the same time without introducing any local assumptions for physics model or grid size. It involves a full transport matrix, thus giving possibility for both density and heat pinches. The model can be derived from the Vlasov equation, adding also close collisions and includes particle pinches of the type found in the magnetosphere and in the Massachusetts Institute of Technology elevated dipole machine. Pinches are also in agreement for the heat pinch experiments on Doublet III D including simultaneous particle and heat pinches. For tokamaks it gives the right scaling of confinement time versus heating power. Finally, we have also recovered the Turbulent Equipartition result that the density scales as inverse safety factor q in typical simulations. Thus this model is both fundamental and of high practical use.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

EvoDiffMol: evolutionary diffusion framework for 3D molecular design with optimized properties

Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a computational framework that integrates evolutionary algorithms with three-dimensional diffusion models for property-driven molecular generation. The method operates through adaptive evolutionary optimization, where population-based selection guides the generation process toward desired property landscapes. EvoDiffMol supports both unconstrained molecular design and scaffold-constrained generation that preserves fixed substructures while optimizing complementary regions. Comprehensive evaluation demonstrates exceptional performance, achieving the highest drug-likeness score (0.94) among all compared state-of-the-art methods while maintaining excellent validity, uniqueness, and novelty. Beyond single property optimization, the framework demonstrates flexible multi-property optimization capabilities, simultaneously controlling multiple molecular descriptors including synthetic accessibility, lipophilicity, topological polar surface area, and clinically relevant ADMET properties such as cardiotoxicity (hERG) and intestinal permeability (Caco-2). This adaptability spans from simple descriptors to practical pharmaceutical endpoints without requiring complete model retraining. The framework achieves precise control over target property values, generating molecules with properties closely matching specified targets for both single and multiple descriptors. Scaffold-constrained experiments preserve fixed molecular cores while maintaining effective property optimization. The three-dimensional representation offers advantages in maintaining structural validity during iterative optimization, with potential for geometry-aware applications in materials science and drug discovery.

3D molecular generation↗
DOE OSTI2026

Learning neural representations for X-ray ptychography reconstruction with unknown probes

X-ray ptychography provides exceptional nanoscale resolution and is widely applied in materials science, biology, and nanotechnology. However, its full potential is constrained by the critical challenge of accurately reconstructing images when the illuminating probe is unknown. Conventional iterative methods and deep learning approaches are often suboptimal, particularly under the low-signal conditions inherent to low-dose and high-speed experiments. These limitations compromise reconstruction fidelity and restrict the broader adoption of the technique. In this work, we introduce the Ptychographic Implicit Neural Representation (PtyINR), a self-supervised framework that simultaneously addresses the object- and probe-recovery problem. By parameterizing both as continuous neural representations, PtyINR performs end-to-end reconstruction directly from raw diffraction patterns without requiring any pre-characterization of the probe. Extensive evaluations demonstrate that PtyINR achieves superior reconstruction quality on both simulated and experimental data, with remarkable robustness under challenging low-signal conditions. Furthermore, PtyINR offers a generalizable, physics-informed framework for addressing probe-dependent inverse problems, making it applicable to a wide range of computational microscopy problems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Large inverse Faraday effect for Rydberg states of free atoms and isolated donors in semiconductors

We report on the induction of magnetization in Rydberg systems by means of the inverse Faraday effect and propose the appearance of the effect in two such systems: Rydberg atoms proper and shallow dopants in semiconductors. Rydberg atoms are characterized by a large orbital radius. This large radius gives such excited states a large angular moment, which when driven with circularly polarized light translates to a large effective magnetic field $\mathscr{B}$ eff . We calculate this effect to generate effective magnetic fields of O⁡(1⁢ µ⁢T)×($\frac{ω}{1THz}$) -1 ⁢ ($\frac{\mathscr{I}}{10Wcm^{-2}}$)⁢n 4 in the Rydberg states of atoms such as Rb and Cs for off-resonant photon beams with frequency ω and intensity $\mathscr{I}$ expressed in units of the denominators and n the principal quantum number. Additionally, terahertz spectroscopy of phosphorus-doped silicon reveals a large cross section for excitation of shallow dopants to Rydberg-like states, which even for small n have the potential to be driven similarly with circularly polarized light to produce an even larger magnetization. Our theoretical calculations estimate $\mathscr{B}$ eff as O⁡(10 2 T) for Si:P with a beam intensity of 10 8 Wcm -2 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multi-mode THz quantum-cascade VECSELs based on disordered metasurfaces

Quantum-cascade vertical-external-cavity surface-emitting-lasers (VECSELs) based on disordered amplifying metasurfaces are demonstrated and explored as potential broadband, multi-mode THz sources. The disorder is introduced along one spatial axis of the metasurface by pseudo-randomly varying the width of its resonant ridge antennas. Compared to a quantum-cascade (QC) VECSEL based on a uniform metasurface, the disordered structure supports much more localized transverse modes with reduced spatial overlap within the QC gain material. This localization is hypothesized to facilitate the spatial hole burning of the gain material and, therefore, enable multi-mode lasing, particularly for short cavities on the order of a few wavelengths. Several devices have been fabricated and shown to differ from uniform QC-VECSELs in a few key ways, possessing highly nonlinear light-current characteristics, angle-dependent emission spectra and broadband multi-mode lasing. At most, 17 modes are simultaneously observed, spanning 680 GHz. The number of VECSEL modes is shown to have an inverse relationship with the cavity length, which is attributed to increased diffractive losses in the open plano-plano cavity. As the cavity length is tuned, the device emits over a quasi-continuous band from 3.15 to 3.97 THz or up to 4.24 THz with a longitudinal mode hop.

Morag, Eilam [Univ. of California, Los Angeles, CA↗
DOE OSTI2020

Uranium Mass Attribute System (UMAS) Study: Evaluation of Options against the Arms Control Evaluation Criteria

In this FY19 study, a range of possible measurement systems for confirming a U-235 mass attribute were identified. The systems were reviewed for their applicability in a potential future arms control agreement, and a subset of the eight most plausible systems were selected for further evaluation against the Arms Control Evaluation Criteria (ACEC). The evaluation results were then used to identify a primary and secondary recommended measurement system for confirming a U-235 mass attribute on warheads, nuclear components of warheads, and/or materials as part of a hypothetical arms control agreement.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

nPINNs: Nonlocal physics-informed neural networks for a parametrized nonlocal universal Laplacian operator. Algorithms and applications

Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius $\delta$ goes to zero, and to the fractional Laplacian as $\delta$ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We also provide theoretical convergence rates with respect to $\delta$ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, $\delta$ and $\alpha$, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order $\alpha(y)$, which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as $\delta$. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications

Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius δ goes to zero, and to the fractional Laplacian as δ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We provide theoretical convergence rates with respect to δ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, δ and α, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order α(γ), which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as δ. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Toward the implementation of self-powered, wireless, real-time reactor power sensing

The successful development of real-time, self-powered, wireless reactor power sensing technology would enable key operating parameters of every fuel assembly in a commercial reactor core to be continuously monitored, and potentially be utilized for applications such as closed-loop reactor control. This paper discusses the expansion of successful work on the application of Self Powered Neutron Detectors (SPND) for reactor power monitoring and the wireless transmission of these detector signals using advanced vacuum micro-electronic (VME) transmitter technology developed by Westinghouse in collaboration with the Penn State University Radiation Science and Engineering Center. Results demonstrate that this technology may be successfully applied via long-term testing in the Penn State TRIGA reactor. SPND are inherently slower than, for example, ion chambers due to their dependence on radioactive decay to generate a signal. Additional research developed delay compensation algorithms to accelerate the response of these detectors for use in near-real-time closed-loop reactor control. Initial results indicate that practical signal acceleration can be obtained digitally or with an equivalent analog circuit. Future research will apply an inverse model of the sensor’s balance differential equations to more-effectively accelerate the SPND signal. Use of inverse models will also prove to be adaptive in the sense that time-dependent burn-up of these detectors, due to neutron activation of the detector material, can be modeled and applied in the acceleration algorithm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Shedding light on shadow generalized parton distributions

The feasibility of extracting generalized parton distributions (GPDs) from deeply virtual Compton scattering (DVCS) data has recently been questioned because of the existence of an infinite set of so-called “shadow GPDs” (SGPDs). These SGPDs depend on the process and manifest as multiple solutions (at a fixed scale 𝑄 2 ) to the inverse problem that needs to be solved to infer GPDs from DVCS data. SGPDs therefore pose a significant challenge for extracting GPDs from DVCS data. With this motivation we study the extent to which QCD evolution can provide constraints on SGPDs. This is possible because the known classes of SGPDs begin to contribute to observables after evolution, and can then be constrained (at the input scale 𝑄$^{2}_{0}$) by data that has a finite 𝑄 2 range. The impact that SGPDs could have on determining the total angular momentum, pressure and sheer force distributions, and tomography is also discussed. We find that 𝑄 2 evolution, given empirical data over a wide range of skewness (𝜉 ) and 𝑄 2 scales, constrains the SGPDs studied at low 𝑥 and low 𝜉. If this finding generalizes to all SGPDs—and we have not been able to find any SGPDs with qualitatively different behavior—then this potentially makes extraction of GPDs from DVCS possible over a limited range of 𝑥 and 𝜉.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Rapid Patterning and Advanced Device Structures for Low Cost Manufacturable Crystalline Si IBC Cells

Recent record efficiency Si cells have had an interdigitated back contact (IBC) design where both positive and negative contacts are fabricated on the back side of the Si wafer. Many industry groups have investigated IBC cells but used photolithography to pattern the rear contacts although it is considered impractical for low cost, high volume manufacturing. Alternative patterning methods using lasers and mechanical masking have been utilized in fabrication of patterned regions in IBC Si solar cells to replace photolithography. Another exciting advance in Si solar cell technology has been replacing the high temperature diffusion of doped regions inside the crystalline Si wafer with low temperature deposition of very thin layers of doped amorphous hydrogenated Si (a-Si:H) on the Si wafer. This is called a Si heterojunction (HJ) device. The a-Si:H provides excellent passivation of surface defects and has produced the highest open circuit voltages (VOC) of any Si solar cell device structure. The Institute of Energy Conversion (IEC) demonstrated the first IBC-HJ solar cell combining these two strategies in 2007 and has fabricated IBC-HJ cells with 20% efficiency using three photolithography steps. Despite the demonstrated efficiency potential of this device by industry groups (>26%) there is no commercial production because of the challenges of patterning and processing the structure in an industrial environment. Our work sought to address that challenge. The objective of this 3 year project was to develop the processing for the IBC-HJ Si solar cell using lasers for patterning and contact formation instead of photolithography. Laser patterning enables rapid, contactless manufacturing of patterned regions. We intensively studied laser fired contacts, laser patterning of the a-Si multi-layer stacks and metal layers and the use of plasma shadow masks. After an exhaustive focus in the first year on the laser fired emitter (LFE) and contact (LFC), we were unable to achieve VOC greater than 660 mV, compared to the 720 mV required to meet our milestones. We discovered that an additional issue with our original IBC structure was the presence of an inversion layer at the back surface connecting the p and n regions which reduced the VOC and fill factor (FF). We developed innovative methods for characterizing the inversion layer. These two limitations in the original design lead to development of a new IBC-HJ process sequence and device structure which we called Plasma Masked Laser Processed (PMLP). It retained the original high efficiency features including manufacturability. The LFC was replaced with a standard n-type a-Si HJ contact. The inversion layer was eliminated by replacing the previous p-type stack in the gap with an n-type or SiN stack. The PMLP used laser ablation of a multi-layer a-Si stack followed by chemical etching to open the n-contact. It required deposition of a patterned stack through a mask in the plasma deposition chamber. This turned out to be a source of significant problems due to inevitable unwanted deposition ‘leakage’ under the mask. This formed a blocking contact on the emitter which significantly reduced Voc and FF. Several iterations in PMLP device structure and chemical etching steps resulted in a large improvements, e.g. the efficiency increasing from 3 to 15% and Voc from 450 to 660 mV but they were unable to completely eliminate it. The best IBC-HJ device we fabricated had only 15% efficiency. For perspective, our standard FHJ devices had 20% efficiency.

14 SOLAR ENERGY↗