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At least 307 records · Page 17

Amine-Appended Metal–Organic Frameworks as Switch-Like Adsorbents for Energy-Efficient Carbon Capture

The goal of this final project report is to comprehensively summarize the work conducted on project FP-00006194. In accordance with the Project Management Plan (PMP) revised May 2019, and Statement of Project Objectives (SOPO) within, Lawrence Berkeley National Laboratory (LBNL), with industrial partners such as Mosaic Materials, Svante, and Electricore, as well as CCSI 2 , has developed a cost-effective post-combustion CO 2 capture system using diamineappended metal–organic frameworks (MOFs). This project involved (i) synthesis and characterization of framework materials that exhibit a switch-like CO 2 adsorption behavior, (ii) scaling-up of MOF production, development of production cost models, and fabrication of materials, and (iii) deployment of materials in a patented VeloxoTherm process and characterization to optimize the material’s performance in the context of real process streams and conditions. During each of the four project budget periods, the project team met Success Criteria for Year 1 to 3; however, because of the decision to halt the project in Q1 2021, Success Criteria for Year 4 were not achieved.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization of electroless nickel-phosphorus plating for ultracold-neutron storage

Electroless nickel plating is an established industrial process that provides a robust and relatively low-cost coating suitable for transporting and storing ultracold neutrons (UCN). Using roughness measurements and UCN-storage experiments we characterized UCN guides made from polished aluminum or stainless-steel tubes plated by several vendors. All electroless nickel platings were similarly suited for UCN storage with an average loss probability per wall bounce of 2.8 • 10 -4 to 4.1 • 10 -4 for energies between 90 neV and 190 neV, or a ratio of imaginary to real Fermi potential η of 1.7 • 10 -4 to 3.3 • 10 -4 . Measurements at different elevations indicate that the energy dependence of UCN losses is well described by the imaginary Fermi potential. Some special considerations are required to avoid an increase in surface roughness during the plating process and hence a reduction in UCN transmission. Increased roughness had only a minor impact on storage properties. In conclusion, based on these findings we chose a vendor to plate the UCN-production vessel that will contain the superfluid-helium converter for the new TRIUMF UltraCold Advanced Neutron (TUCAN) source, achieving acceptable UCN-storage properties with η = 3.5(5)•10 -4 .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fabrication and Characterization of High Temperature Resin/Carbon Nanofiber Composites

Multifunctional composites present a route to structural weight reduction. Nanoparticles such as carbon nanofibers (CNF) provide a compromise as a lower cost nanosize reinforcement that yields a desirable combination of properties. Blends of PETI-330 and CNFs were prepared and characterized to investigate the potential of CNF composites as a high performance structural medium. Dry mixing techniques were employed and the effect of CNF loading level on melt viscosity was determined. The resulting powders were characterized for degree of mixing, thermal and rheological properties. Based on the characterization results, samples containing 30 and 40 wt% CNF were scaled up to approx.300 g and used to fabricate moldings 10.2 cm x 15.2 cm x 0.32 cm thick. The moldings were fabricated by injecting the mixtures at 260-280 C into a stainless steel tool followed by curing for 1 h at 371 C. The tool was designed to impart high shear during the process in an attempt to achieve some alignment of CNFs in the flow direction. Moldings were obtained that were subsequently characterized for thermal, mechanical and electrical properties. The degree of dispersion and alignment of CNFs were investigated using high-resolution scanning electron microscopy. The preparation and preliminary characterization of PETI-330/CNF composites are discussed. Keywords: resins, carbon nanofibers, scanning electron microscopy, electrical properties, thermal conductivity,injection

Ghose, Sayata↗

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is commonly characterized as one of two types: production testing for certification and acceptance of engine hardware, and developmental testing for prototype evaluation or research and development (R&D) purposes. For programmatic reasons there is a continuing need to assess and evaluate the test costs for the various types of test campaigns that involve liquid rocket propellant test articles. Presently, in fact, there is a critical need to provide guidance on what represents a best value for testing and provide some key economic insights for decision-makers within NASA and the test customers outside the Agency. Hence, selected rocket propulsion test databases and references have been evaluated and analyzed with the intent to discover correlations of technical information and test costs that could help produce more reliable and accurate cost projections in the future. The process of searching, collecting, and validating propulsion test cost information presented some unique obstacles which then led to a set of recommendations for improvement in order to facilitate future cost information gathering and analysis. In summary, this historical account and evaluation of rocket propulsion test cost information will enhance understanding of the various kinds of project cost information; identify certain trends of interest to the aerospace testing community.

Ramirez, Carmen↗

CO 2 capture from wet flue gas using a water-stable and cost-effective metal-organic framework

We report the use of MIL-120 as a water-stable and cost-effective metal-organic framework (MOF) for selectively capturing CO 2 from wet flue gas. Synthesized using inexpensive and environmentally benign reagents in water, MIL-120 possesses one-dimensional pores decorated with hydroxyl-bridged Al(III) ions and benzene rings with an interstitial spacing of 4.78 Å. Carbon dioxide isotherms show steep uptake at low pressure, and the affinity of MIL-120 for CO 2 is 44 kJ mol –1 . CO 2 -loading 13 C solid-state nuclear magnetic resonance and Fourier transform infrared spectra tracking the sorption of CO 2 into MIL-120 revealed that the interplay of pore size, functionality, and dimensionality is vital for CO 2 restriction within the pores of MIL-120. Breakthrough experiments reveal that MIL-120 can capture CO 2 from dry and wet flue gas with uptake capacities of 1.215 and 1.118 mmol g –1 , respectively. Our work highlights the synthetic benefits of MIL-120 and elucidates its selective capture of CO 2 from wet flue gas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of Actuator Movement Rate During Acquisition of Inlet Characterization Data

This report considers using a process to acquire performance data for supersonic mixed-compression inlets that is faster and less costly than the previous process. In the previous process for acquiring data during wind tunnel experiments, actuators for backpressuring an inlet moved in discrete increments, paused for dynamics to dampen, measured data for 5 s, recorded the data, and then reduced the data to graphic plots of pressure recovery versus mass capture ratio. This discrete data acquisition procedure was methodical, reliable, and accurate. However, acquiring data to characterize the inlet consumed significant wind-on time. Wind tunnel operation was costly when considering maintenance, energy, and human resources (operators and research team); therefore, the price for each data point was high. This report presents a quicker method to obtain all measurements, one which can also be used in blowdown wind tunnels. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. The backpressuring actuator moves continuously, and measurements from high-speed pressure sensors are recorded as the actuator progresses to and past the incremental points. Despite its advantages, the approach raised the following questions: (1) Will the new process be as accurate as the previous process? and (2) Are there any hidden costs? These concerns are addressed in this report. This report reviews a study that was undertaken to compare wind tunnel experiment data taken using the previous discrete data acquisition procedure with data recorded using the dynamic inlet characterization data acquisition procedure. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data for analysis are explained, and a discussion of the results is given. Finally, conclusions from this study that may guide further work in this area are presented.

Inlet Characterization Curves↗

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Advancing Additive Manufacturing Through Artificial Intelligence–Powered, High-Throughput, Nondestructive Characterization and Process Optimization

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and ZEISS Industrial Metrology has demonstrated the transformative potential of artificial intelligence (AI)-enabled x-ray computed tomography (XCT) to accelerate the qualification and certification of additively manufactured (AM) parts. At the core of this effort is Simurgh, an AI-powered XCT reconstruction framework jointly advanced by ORNL and ZEISS that integrates computer-aided design (CAD) models, physics-based simulations, and deep learning to overcome the long-standing challenges of metal artifact correction, long scan durations, and limited flaw detectability in dense and geometrically complex components. Simurgh enables high-throughput, high-quality 3D reconstruction from sparse and fast scans, which reduces XCT acquisition times by more than an order of magnitude and simultaneously improves defect detection limits by up to fourfold compared with industry-standard approaches. This capability reduces scan costs by more than 50%, lowers labor overhead, and makes XCT characterization economically viable for routine industrial use. By enabling reliable flaw detection in minutes rather than hours, Simurgh facilitates real-time feedback loops for process parameter optimization, which was highlighted in a recent npj Computational Materials (a Nature journal) issue. In the published study, more than 100 alloy coupons were characterized within a single day. This work represents a tenfold acceleration in the development of novel AM alloys and processes compared with conventional workflows. The ZEISS collaboration has also demonstrated the scalability of Simurgh to diverse application domains, including aerospace, nuclear, automotive, and biomedical components; in these applications, ensuring structural integrity is paramount. By drastically reducing barriers to XCT adoption, this partnership has laid the foundation for digital twins and data-driven certification pipelines and directly addressed bottlenecks in qualifying new materials and designs. Together, ORNL and ZEISS have shown that Simurgh advances the state of the art in nondestructive evaluation and aligns with the broader mission of enabling Industry 4.0 manufacturing ecosystems, in which intelligent, cost-effective, rapid quality assurance is integral to accelerating innovation and ensuring safety in critical applications.

36 MATERIALS SCIENCE↗

Multibeam Phased-Array Antennas Developed and Characterized

Fixed-formation microsatellites have been proposed for future NASA missions to lower costs and improve data collection and reliability. Achieving seamless connectivity communications between these satellites requires the use of multibeam array antennas. As a result of NASA Glenn Research Center s collaborative efforts with the University of Colorado and Texas A&M University, two prototype multibeam array antennas have been developed and demonstrated at Ka-band frequencies. These arrays are designed to be dual-beam, dual-frequency arrays, with two fixed scan beams at around +/- 30 . They can be used in both ground and space systems for transmit and receive functions.

Lee, Richard Q.↗

ER-2 High Altitude Solar Cell Calibration Flights

Evaluation of space photovoltaics using ground-based simulators requires primary standard cells which have been characterized in a space or near-space environment. Due to the high cost inherent in testing cells in space, most primary standards are tested on high altitude fixed wing aircraft or balloons. The ER-2 test platform is the latest system developed by the Glenn Research Center (GRC) for near-space photovoltaic characterization. This system offers several improvements over GRC's current Learjet platform including higher altitude, larger testing area, onboard spectrometers, and longer flight season. The ER-2 system was developed by GRC in cooperation with NASA's Armstrong Flight Research Center (AFRC) as well as partners at the Naval Research Laboratory and Air Force Research Laboratory. The system was designed and built between June and September of 2014, with the integration and first flights taking place at AFRC's Palmdale facility in October of 2014. Three flights were made testing cells from GRC as well as commercial industry partners. Cell performance data was successfully collected on all three flights as well as solar spectra. The data was processed using a Langley extrapolation method, and performance results showed a less than half a percent variation between flights, and less than a percent variation from GRC's current Learjet test platform.

ER-2↗

Microstructural Simulation of Ion-Irradiated Natural Rocks and Minerals

This report details the contribution of Oak Ridge National Laboratory to the Nuclear Energy University Program (NEUP) project, "Rapid Characterization of Concrete Mineralogy using Multi-Scale Tools" led by the University of Illinois at Urbana-Champaign. To support the subsequent license renewal (SLR) of the US nuclear power plants (NPPs) fleet, the performance of concrete-forming aggregates against neutron irradiation needs to be assessed. Ion irradiation is proposed as a rapid, cost-effective surrogate method to full neutron irradiation testing. To complement the characterization of ion-irradiated rock specimens, ORNL has run finite-elements and fast-Fourier transform (FFT-based) simulations using the codes MARS and Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC). The main conclusion of this analysis is that the apparent post–ion-irradiation step-height underestimates the accumulated free radiation-induced volumetric expansion (RIVE) in the ion-implanted depth by about 15% at full amorphization and about 25% toward the beginning of the ion irradiation experiment. The discrepancy is explained by the fact that the step height is proportional to the sum of the RIVE (i.e., one third of the RIVE) and the irradiation-assisted plastic strains in the vertical direction (lower than two thirds of the RIVE). Because of the large lateral compressive stresses caused by the restraining effect of the unirradiated substrate, the stress field in the mineral grains and at the grain boundary (GB) in the ion-implanted layer is much different than the comparable stress field occurring during neutron irradiation. Hence, the mismatch RIVE causing cracks in the rock-forming minerals leads to different cracking patterns. Ion irradiation continues to be used as a rapid technique to assess the RIVE potential of rocks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Accelerated Creep Test Qualification of Creep-Resistance Using the Wilshire–Cano–Stewart Constitutive Model and Stepped Isostress Method

In this paper, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire–Cano–Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing is a long-term continuous process; in fact, the ASME B&PV III requires that 10,000+ h of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The SSM has been developed, which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750 °C and predictions are compared to conventional creep testing data. The WCS model has proven to make long-term predictions for stress-rupture, MCSR, creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are postaudit validated using the National Institute of Material Science database. Similarly, the MCSR predictions are compared from previous studies. Finally, the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and industrial gas turbines.

42 ENGINEERING↗

ACCELERATED CREEP TEST (ACT) QUALIFICATION OF CREEP RESISTANCE USING THE WCS CONSTITUTIVE MODEL AND STEPPED ISOSTRESS METHOD (SSM)

In this study, a qualification of accelerated creep-resistance of Inconel 718 is assessed using the novel Wilshire-Cano-Stewart (WCS) model and the stepped isostress method (SSM) and predictions are made to conventional creep data. Conventional creep testing (CCT) is a long-term continuous process, in fact, the ASME B&PV III requires that 10,000+ hours of experiments must be conducted to each heat for materials employed in boilers and/or pressure vessel components. This process is costly and not feasible for rapid development of new materials. As an alternative, accelerated creep testing techniques have been developed to reduce the time needed to characterize the creep resistance of materials. Most techniques are based upon the time-temperature-stress superposition principle (TTSSP) that predicts minimum-creep-strain-rate (MCSR) and stress-rupture behaviors but lack the ability to predict creep deformation and consider deformation mechanisms that occur for experiments of longer duration. The stepped isostress method (SSM) has been developed which enables the prediction of creep deformation response as well as reduce the time needed for qualification of materials. The SSM approach has been successful for polymer, polymeric composites, and recently has been introduced for metals. In this study, the WCS constitutive model, calibrated to SSM test data, qualifies the creep resistance of Inconel 718 at 750°C and predictions are compared to CCT data. The WCS model has proven to make long-term predictions for stress-rupture, minimum-creep-strain-rate (MCSR), creep deformation, and damage in metallic materials. The SSM varies stress levels after time interval adding damage to the material, which can be tracked by the WCS model. The SSM data is calibrated into the model and the WCS model generates realistic predictions of stress-rupture, MSCR, damage, and creep deformation. The calibrated material constants are used to generate predictions of stress-rupture and are post-audit validated using the National Institute of Material Science (NIMS) database. Similarly, the MCSR predictions are compared from previous studies. Finally the creep deformation predictions are compared with real data and is determined that the results are well in between the expected boundaries. Material characterization and mechanical properties can be determined at a faster rate and with a more cost-effective method. This is beneficial for multiple applications such as in additive manufacturing, composites, spacecraft, and Industrial Gas Turbines (IGT).

36 MATERIALS SCIENCE↗

Rocket engine injection element characterization

Characterization of liquid rocket engine injection elements is an important part of the development process for rocket engine combustion devices. Modern nonintrusive instrumentation for flow velocity and spray droplet size measurement and automated, computer-controlled test facilities allow rapid, low-cost evaluation of injection element performance and behavior. Application of these methods in rocket engine development, paralleling their use in gas turbine engine development, will reduce rocket engine development cost and risk. Two types of liquid rocket engine injection elements have been characterized using such methods.

Cox, George B., Jr.↗

In situ measurement of phase transformations and residual stress evolution during welding using spatially distributed fiber-optic strain sensors

Welding of high-strength steels can result in large tensile strains as the base metal and filler material cool from their molten state. To combat these large tensile strains, low-transformation-temperature (LTT) metal fillers have been proposed. These fillers undergo a martensitic phase transformation at a lower temperature which can ultimately reduce the tensile strain or can even introduce compressive strain adjacent to the weld metal. However, the process for optimizing the composition of the LTT material, as well as various weld parameters for each unique weld geometry, can be quite expensive, especially if the acceptance criterion requires using neutrons, x-ray beams, or destructive techniques to characterize residual stresses. This work describes a simple, low-cost method for quantifying residual stresses and phase transformations in situ during welding. Spatially distributed fiber-optic sensors were bonded to a cast iron plate, along with tack-welded thermocouples, to measure temperature and strain during multiple passes with LTT filler metals. Results show that the fiber-optic sensors can successfully resolve compressive strain adjacent to the weld region caused by the martensitic phase transformations in the LTT filler material.

47 OTHER INSTRUMENTATION↗

Low-Cost Screening of Algae for Extreme Tolerance to pH, Temperature, Salinity, and Light

AbstractBioprospecting algae strains with tolerance to extreme conditions such as pH, temperature, salinity, and light is crucial for advancing biotechnology and environmental applications. However, traditional screening methods often involve significant costs and labor, restricting their accessibility and practical use. In this study, we developed and validated low-cost, high-throughput screening techniques, predominantly employing agar plates and liquid culture assays, to effectively differentiate tolerance levels among various algae strains. The methodologies were optimized using the model microalgaChlamydomonas reinhardtiiand its closely related speciesChlamydomonas incertaand the recently discovered extremophilicChlamydomonas pacifica. We systematically evaluated the algae for tolerance to extremes by establishing precise gradients of pH (acidic to alkaline conditions), salinity (0 to 5 M NaCl), temperature (34–42°C), and light intensity (40 to 2977 μE·m⁻²·s⁻¹). Our results demonstrated that these cost-effective, agar plate-based methods effectively distinguished algae strains exhibiting superior tolerance to extreme environmental conditions. These screening techniques not only provided clear differentiation among the closely related strains but also delivered reproducible outcomes suitable for scaling up to larger bioprospecting efforts. Furthermore, the affordability and simplicity of these methods facilitate their implementation in resource-limited laboratories, thereby broadening participation in algae bioprospecting endeavors. This study highlights the potential of low-cost, accessible screening techniques to significantly enhance the discovery and characterization of algal strains with extreme traits. Ultimately, these methods support the development of robust algae-based resources, driving innovation in diverse industrial processes and environmental solutions.Graphical Abstract

Saucedo, Barbara (ORCID:0009000008860839)↗

Analysis of Crystalline Defects Caused by Growth on Partially Planarized Spalled (100) GaAs Substrates

We analyze the effect of growth on non-(100) surfaces resulting from incomplete planarization of spalled GaAs wafers on the defect structure of GaAs solar cell layers grown by hydride vapor phase epitaxy (HVPE). Controlled spalling of (100)-oriented GaAs has the potential to reduce substrate costs for III-V epitaxy; however, it creates regularly faceted surfaces that may complicate the growth of high-quality III-V optoelectronic devices. We leverage the anisotropic growth rate of HVPE to planarize these faceted GaAs substrates, reducing the surface roughness and degree of faceting. We observe degraded solar cell performance and material quality in sample areas where facets are not completely removed. We used dark lock-in thermography and photoluminescence to identify recombination in areas that were not fully planarized. We used cathodoluminescence to identify the presence of extended defects in these regions, which are correlated with bandgap fluctuations in the material. We hypothesize that these defects were created by strain from compositional fluctuations in ternary alloys grown on the faceted surfaces. This work elucidates the potential issues of solar cells grown on faceted surfaces and builds understanding toward realizing high performance III-V photovoltaics with the cost-reduction potential of controlled spalling.

14 SOLAR ENERGY↗