Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Process sensitivity”

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

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

At least 271 records · Page 15

Process-informed adsorbent design guidelines for direct air capture

Direct air capture using solid adsorbents is a proven technology critical to reducing our net greenhouse gas emissions to zero and beyond. Currently, academic research into the technology mainly focuses on the development of new adsorbents. However, there is a discord between the adsorbent design and process performance. Many materials scientists focus on maximising metrics such as the CO 2 capacity of their adsorbent. Here, we combine detailed process modelling, machine learning, and extensive global sensitivity analysis, which entails varying all of the model parameters together, on a direct air capture process to show that the dry CO 2 adsorption capacity does not influence process performance for an amine-functionalised adsorbent operating in a temperature vacuum swing adsorption (TVSA) process, while it is important in a steam-assisted TVSA (S-TVSA) process. In fact, adsorption kinetics, density, and thermal conductivity are all critical attributes to obtaining a low energy penalty and reduced costs. The analysis also highlights the importance of heat transfer, directing process engineers to (alternative) adsorber designs that maximise this. By an in-depth evaluation of how process performance indicators are affected by materials properties and process operating parameters, this work provides guidance to both material scientists and process engineers towards the design of a “unicorn adsorbent” and intensified DAC processes. This will improve the performance of solid adsorbent direct air capture and help drive down the costs of this vital technology to avert the worst impacts of climate change.

42 ENGINEERING↗

Curing process and pore structure of metakaolin-based geopolymers: Liquid-state 1H NMR investigation

Geopolymers are emerging construction materials with lower carbon dioxide emissions compared to the conventional cementitious materials. The knowledge of the curing process and the related pore structures are important for optimizing the properties of these materials for different applications. The curing process and final pore structure are sensitive to the amount of used water, however the specifics are unclear. The curing process and pore structures of metakaolin-based geopolymers with a narrow water-to-solid (w/s) ratio (0.59–0.66) were monitored by nuclear magnetic resonance (NMR) relaxometry and cryoporometry. The 14-day curing process was investigated by monitoring the change of T{sub 2} and T{sub 1} relaxation times and water signal intensity. After the curing, the pore structures were characterized by 2D T{sub 1}-T{sub 2} correlation and T{sub 2}-T{sub 2} exchange measurements of absorbed water. The pore size distributions (PSDs) were measured with NMR cryoporometry and compared to nitrogen physisorption and mercury intrusion porosimetry (MIP) results. We found that the relaxation times decreased as the pore structure of the geopolymers matured during the curing while the dissolution and the condensation periods of the curing were distinguished by the changes in signal amplitude reflecting the proton density. After the curing, three distinct pore sizes and connectivity between pores were identified from T{sub 1}-T{sub 2} and T{sub 2}-T{sub 2} spectra. Their PSDs were measured, and they were found to correspond to two different pore sizes originating from the arrangement of clusters and defective pores. In the narrow w/s ratio (0.59–0.66), the curing times were the same for all samples when cured at 24 °C while the pore sizes were observed to increase as a function of the w/s ratio.

36 MATERIALS SCIENCE↗

Real-Time Partitioning of Diurnal Stem CO 2 Efflux into Local Stem Respiration and Xylem Transport Processes

The apparent respiratory quotient (ARQ) of tree stems, defined as the ratio of net stem CO 2 efflux (E S_CO2 ) to net stem O 2 influx (E S_O2 ), offers insights into the balance between local respiratory CO 2 production and CO 2 transported via the xylem. Traditional static chamber methods for measuring ARQ can introduce artifacts and obscure natural diurnal variations. Here, we employed an open flow-through stem chamber with ambient air coupled with cavity ring-down spectrometry, which uses the molecular properties of CO 2 and O 2 molecules to continuously measure E S_CO2 , E S_O2 , and ARQ, at the base of a California cherry tree (Prunus ilicifolia) during the 2024 growing season. Measurements across three stem chambers over 3–11-day periods revealed strong correlations between E S_CO2 and E S_O2 and mean ARQ values ranging from 1.3 to 2.9, far exceeding previous reports. Two distinct diurnal ARQ patterns were observed: daytime suppression with nighttime recovery, and a morning peak followed by gradual decline. Partitioning E S_CO2 into local respiration and xylem-transported CO 2 indicated that the latter can dominate when ARQ exceeds 2.0. Furthermore, transported CO 2 exhibited a higher temperature sensitivity than local respiration, with both processes showing declining temperature sensitivity above 20 °C. These findings underscore the need to differentiate stem CO 2 flux components to improve our understanding of whole-tree carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Grounding our Understanding of the Impacts of Boreal Forest Expansion on Shallow Cumulus Clouds with a Simple Modeling Framework

Abstract The expansion of the boreal forest poleward is a potentially important driver of feedbacks between the land surface and Arctic climate. A growing body of work has highlighted the importance of differences in evaporative resistance between different possible future Arctic land covers, which in turn alters humidity and cloudiness in the boundary layer, for these feedbacks. While thus far this problem has been studied primarily with complex Earth system models, we turn to a locally focused, idealized model capable of diagnosing and testing the sensitivity of first-order processes connecting vegetation, the atmospheric boundary layer, and low clouds in this critical region. This allows us to benchmark the mechanisms and results at the center of predictions from larger-scale simulations. A surface dominated by broadleaf trees, characterized by higher albedo and lower surface evaporative resistance, drives cooling and moistening of the boundary layer relative to a surface of needleleaf trees, characterized by lower albedo and higher surface evaporative resistance. Differences in evaporative resistance between these hypothetical Arctic vegetation covers are of equal importance to changes in albedo for the initial response of the boundary layer to boreal expansion, even with our idealized approach. However, compensation between the elevation of the lifting condensation level (LCL) and more rapid growth of the mixed layer over higher evaporative resistance surfaces can minimize changes in the favorability of shallow clouds over different land cover types under some conditions. We then perform two tests on the sensitivity of this compensating effect, to changes in water availability, represented first by a reduction in boundary layer humidity and then by both a reduction in humidity and soil moisture available to our vegetation surface. Finally, given the importance of this potential LCL–mixed-layer height compensation in our idealized modeling results, we look to determine its relevance in observational data from a field campaign in boreal Finland. These observations do confirm that such a coupling plays an important role in cumulus-topped boundary layers over a needleleaf forest surface. While our results confirm some underlying mechanisms at the center of prior work with Earth system models, they also provide motivation for future work to constrain the impact of boreal forest expansion. This will include both large eddy simulations to examine the impact of processes and feedbacks not resolved by a mixed-layer model, as well as a more systematic evaluation and comparison of relevant observations at the site in Finland and sites from prior boreal field campaigns. Significance Statement Clouds and vegetation are both important components of the climate system that interact across a range of scales. These interactions are central to understanding how changes at the land surface feedback on climate. For example, if a forest expands or recedes, diagnosing how that will impact clouds will determine whether you predict warming or cooling temperatures from that shift in the forest area. These predictions are often made with complex Earth system models, but we look to a more idealized representation of the land–atmosphere system to diagnose how shallow clouds should respond to changes in surface properties with different scenarios of boreal forest expansion at a more foundational level. This both grounds our understanding of previous analysis and provides helpful direction for future studies of this relevant and impactful land cover change.

Meteorology & Atmospheric Sciences↗

Evaluating the Influence of Plants on Hydrologic Cycling: Quantifying and Validating the Role of Plant Processes and Stomatal Conductance (Final Report)

Plants can exert strong controls on water cycling, both locally and across the globe. The impacts are driven by how plants control the exchange of water and energy between the land and the atmosphere, which in turn are influenced by how plants photosynthesize and grow (e.g. biogeochemical cycling). Our team has shown previously that plant responses to increasing CO 2 in the atmosphere can influence the water cycle through changes in rainfall and the amount of water on land with implications for drought. Plant responses can also alter both average and extreme flow of water in rivers, with implications for freshwater availability and flood frequency. Although the impact of plant responses on water cycling has been demonstrated to exist, significant uncertainty remains in our understanding of the magnitude and form of the plant responses themselves, as well as their ultimate impact on water availability for people and ecosystems. In this project we worked to quantify the role of plant processes in regulating water cycling (e.g., precipitation, evapotranspiration, runoff, droughts, etc.). We addressed the following objectives: quantify the control of physiological vs. radiative effects on water cycling across many coupled models in idealized and realistic scenarios, as well as to quantify how our assumptions about leaf-level processes (e.g. coupling between stomatal conductance and photosynthesis), and organism-level processes (e.g. leaf area response to high CO 2 ) contributed to uncertainties and biases in water cycling. We focused on the impact of these processes on water cycling to assess the sensitivities of precipitation, evapotranspiration, and runoff to model assumptions about plant processes at the leaf, organism, and community level. As part of this project we used measurements of stable carbon isotopes to generate observationally based estimates of plant functioning during the historical period. This work is directly relevant to DOE’s primary scientific research questions in the RGMA topic area (b) on Biogeochemical processes, feedbacks, and interactions in the Earth system.

59 BASIC BIOLOGICAL SCIENCES↗

LLNL SFA OBER FY23 Program Management and Performance Report: BioGeoChemistry at Interfaces

The focus of the BioGeoChemistry at Interfaces SFA has been to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach has included: (1) Field Studies that capture actinide behavior on the timescale of decades (Research Thrust 1), and (2) Fundamental Laboratory Studies that isolate specific biogeochemical processes observed in the field (Research Thrust 2). These Research Thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory, allowing the BioGeoChemistry at Interfaces SFA to advance our understanding of actinide migration behavior in the environment, and serve as a resource for environmental radiochemistry research internationally (Figure 1). In FY23, our SFA research focused on transient redox gradients across stratified waters, sediment-water interfaces, and mineral-water interfaces to address processes controlling cycling of redox-sensitive metals. Nevertheless, Research Thrusts 1 and 2 are guided by the following broad central hypotheses that were developed during our last program review held at the end of FY18: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limits their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides and other radionuclides (e.g. Cs) and provide DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites. More broadly, we are improving our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. While we retained some of our historical focus on actinide biogeochemistry this past fiscal year, biogeochemical processes occurring at unique Test Bed locations associated with this SFA provide fundamental information on abiotic and biotic redox processes that control the cycling of redox sensitive metals under dynamic and transient conditions. Furthermore, in collaboration with SFA teams at Argonne National Laboratory, our SFA has begun to transition away from the current research focus and develop a new research program in terrestrial wetland systems. The Terrestrial Wetland Function and Resilience SFA program plan will be delivered to the Environmental System Science (ESS) program within BER at the end of FY23.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗

BioGeoChemistry at Interfaces (LLNL SFA OBER FY22 Program Management and Performance Report)

The focus of the BioGeoChemistry at Interfaces SFA is to identify and quantify the biogeochemical processes and the underlying mechanisms that control actinide mobility in an effort to reliably predict and control the cycling and migration of actinides in the environment. The research approach includes: (1) Field Studies that capture actinide behavior on the timescale of decades (Research Thrust 1), and (2) Fundamental Laboratory Studies that isolate specific biogeochemical processes observed in the field (Research Thrust 2). These Research Thrusts are underpinned by the unique capabilities and staff expertise at Lawrence Livermore National Laboratory, allowing the BioGeoChemistry at Interfaces SFA to advance our understanding of actinide migration behavior in the environment, and serve as an resource for environmental radiochemistry research internationally. In the past year, our greater focus on transient redox gradients across stratified waters, sediment-water interfaces, and mineral-water interfaces extended our research beyond actinides to address processes controlling cycling of redox-sensitive metals more broadly. Nevertheless, Research Thrusts 1 and 2 are guided by the following broad central hypotheses that were developed during our last program review held at the end of FY18: Thrust 1 Hypothesis: Biogeochemical processes occurring on the timescale of years to decades lead to greater actinide recalcitrance in sediments and limits their migration in surface and groundwater. Thrust 2 Hypothesis: Long-term biogeochemical processes include mineral and surface alteration, which leads to stabilization of actinide surface associations or incorporation into mineral precipitates. Our strategic goal is to use the knowledge gained from our Science Plan to advance our understanding of the behavior of actinides and other radionuclides (e.g. Cs) and provide DOE with the scientific basis for remediation and long-term stewardship of DOE’s legacy sites. More broadly, we will enhance our understanding of transport phenomena in environmental systems sciences with a particular emphasis on environmentally relevant (long-term) timescales. While we retain our focus on actinide biogeochemistry, our increased focus on overall biogeochemical processes occurring at unique Test Bed locations associated with this SFA provides fundamental information on abiotic and biotic redox processes that control the cycling of redox sensitive metals under dynamic and transient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nuclear data uncertainty propagation applied to the versatile test reactor conceptual design

We report the Versatile Test Reactor (VTR) currently under development is a 300 MWth sodium-cooled fast reactor (SFR) fueled with ternary metal alloy fuel, which aims to accelerate the testing of advanced nuclear fuels, materials, instrumentation, and sensors in high flux environments that are necessary to license the next generation of advanced reactor concepts. To support the VTR design process, uncertainties associated with the nuclear data has been propagated through the reactor core neutronics calculation to global parameters of interest, such as the core multiplication factor, kinetic parameters, and various reactivity feedback coefficients, following the sensitivity based uncertainty propagation approach. By folding the sensitivity coefficients, separately computed by the generalized perturbation theory code PERSENT and Monte Carlo code Serpent 2, with the variance-covariance matrices from COMMARA-2.0, we obtain the reaction-wise, isotope-wise, and overall uncertainties for each response of interest due to nuclear data uncertainty. With Serpent 2, the statistical error of the uncertainty is obtained by propagating the statistical error of the sensitivity coefficients through the same process using a newly developed uncertainty propagation method. From both codes, the overall top uncertainty contributors are found to be the cross section of Fe-56 elastic scattering, Na-23 elastic scattering, and U 238 inelastic scattering. The large contributions of the Fe-56 elastic scattering cross sections to global parameters are due to its relatively large relative uncertainty of 5–10% in nuclear data and the large volume of Fe-containing reflector assemblies in the fairly compact VTR core design. Both codes agreed well for the overall uncertainty estimates of all responses of interest, except the delayed neutron fraction, prompt neutron generation time, and the coolant density feedback coefficient, where Serpent 2 yielded a much larger value than PERSENT due to the large statistical error of sensitivity coefficients. The calculated uncertainties are also compared to those associated with other SFR cores. Another outcome of this study is a variance-covariance matrix of reactivity coefficients, which can be used in the subsequent uncertainty propagation to the system level to investigate the impact of identified uncertainties on system responses in the safety analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Search for a heavy Higgs boson decaying into two lighter Higgs bosons in the ττbb final state at 13 TeV

A search for a heavy Higgs boson H decaying into the observed Higgs boson h with a mass of 125 GeV and another Higgs boson hS is presented. The h and hS bosons are required to decay into a pair of tau leptons and a pair of b quarks, respectively. The search uses a sample of proton-proton collisions collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 137 fb -1 . Mass ranges of 240–3000 GeV for m H and 60–2800 GeV for m h S are explored in the search. No signal has been observed. Model independent 95% confidence level upper limits on the product of the production cross section and the branching fractions of the signal process are set with a sensitivity ranging from 125 fb (for m H = 240 GeV) to 2.7 fb (for m H = 1000 GeV). These limits are compared to maximally allowed products of the production cross section and the branching fractions of the signal process in the next-to-minimal supersymmetric extension of the standard model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the Mo 100 ( α , x n ) cross section at weak r -process energies

Here, the weak r process in neutrino-driven winds following a core-collapse supernova is thought to contribute to the cosmic abundances of the first r-process peak elements between Se and Ag. Sensitivity studies have found that the early nucleosynthesis in the weak r process is primarily driven by (α, xn) reactions due to the high temperatures, and that current nuclear physics uncertainties in the (α, xn) rates result in significant uncertainties of the calculated abundances. The weak r-process path proceeds several nuclei away from stability where (α, xn) reaction cross sections have not yet been measured. In this paper we report the 100 Mo (α, xn) cross section (between 8.9 and 13.2 MeV in the center of mass, corresponding to 3.5–6.8 GK) in inverse kinematics using the Multi-Sampling Ionization Chamber (MUSIC) detector at the Argonne Tandem Linac Accelerator System (ATLAS) facility. With this first measurement of the 100 Mo (α, xn) cross section, we have demonstrated the ability of MUSIC to measure (α, xn) cross sections for A up to 100, therefore paving the way for further measurements with radioactive beams at ATLAS or the Facility for Rare Isotope Beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗

Visualization of hydraulic fracture using physics-informed clustering to process ultrasonic shear waves

Ultrasonic transmission is sensitive to the spatial variation in mechanical properties of materials due to the presence of cracks/fractures. Wave propagation through fractured media introduces changes in the frequency content, travel time and transmission coefficient of the wave. A workflow based on physics-informed unsupervised learning is developed to process the transmitted ultrasonic-shear waveforms to non-invasively visualize the geomechanical alterations due to hydraulic fracturing. Novelty of the work involves the assignment of both statistically consistent and physically consistent clusters to the measurements of shear waveforms acquired across the one axial and two frontal planes. Physically consistent/relevant information is incorporated by considering the travel time of the peak of spectral energy and transmission coefficient of the transmitted waveform. The proposed workflow generates maps of geomechanical alterations across the frontal and axial planes of the sample. The outputs of the workflow are in good agreement with independent techniques viz. acoustic emission and X-ray computed tomography. Finally, the proposed workflow can be adapted for improved fracture characterization in the subsurface when processing sonic-logging, cross-wellbore seismic or surface seismic waveform data.

42 ENGINEERING↗

Effects of fragmentation on post-inflationary reheating

We consider the effects of fragmentation on the post-inflationary epoch of reheating. In simple single field models of inflation, an inflaton condensate undergoes an oscillatory phase once inflationary expansion ends. The equation of state of the condensate depends on the shape of the scalar potential, V(Φ), about its minimum. Assuming V(Φ) ~ Φ k , the equation of state parameter is given by w = P Φ /ρ Φ = (k - 2)/(k + 2). The evolution of condensate and the reheating process depend on k. For k ≥ 4, inflaton self-interactions may lead to the fragmentation of the condensate and alter the reheating process. Indeed, these self-interactions lead to the production of a massless gas of inflaton particles as w relaxes to 1/3. If reheating occurs before fragmentation, the effects of fragmentation are harmless. We find, however, that the effects of fragmentation depend sensitively to the specific reheating process. Reheating through the decays to fermions is largely excluded since perturbative couplings would imply that fragmentation occurs before reheating and in fact could prevent reheating from completion. Reheating through the decays to boson is relatively unaffected by fragmentation and reheating through scatterings results in a lower reheating temperature.

79 ASTRONOMY AND ASTROPHYSICS↗

The case for digital twins in metal additive manufacturing

The digital twin (DT) is a relatively new concept that is finding increased acceptance in industry. A DT is generally considered as comprising a physical entity, its virtual replica, and two-way digital data communications in-between. Its primary purpose is to leverage the process intelligence captured within digital models—or usually their faster-solving surrogates—towards generating increased value from the physical entities. The surrogate models are created using machine learning based on data obtained from the field, experiments and digital models, which may be physics-based or statistics-based. Anomaly detection and correction, and diagnostic closed-loop process control are examples of how a process DT can be deployed. In the manufacturing industry, its use can achieve improvements in product quality and process productivity. Metal additive manufacturing (AM) stands to gain tremendously from the use of DTs. This is because the AM process is inherently chaotic, resulting in poor repeatability. However, a DT acting in a supervisory role can inject certainty into the process by actively keeping it within bounds through real-time control commands. Closed-loop feedforward control is achieved by observing the process through sensors that monitor critical parameters and, if there are any deviations from their respective optimal ranges, suitable corrective actions are triggered. The type of corrective action (e.g. a change in laser power or a modification to the scanning speed) and its magnitude are determined by interrogating the surrogate models. Because of their artificial intelligence (AI)-endowed predictive capabilities, which allow them to foresee a future state of the physical twin (e.g. the AM process), DTs proactively take context-sensitive preventative steps, whereas traditional closed-loop feedback control is usually reactive. Apart from assisting a build process in real-time, a DT can help with planning the build of a part by pinpointing the optimum processing window relevant to the desired outcome. Again, the surrogate models are consulted to obtain the required information. In this article, we explain how the application of DTs to the metal AM process can significantly widen its application space by making the process more repeatable (through quality assurance) and cheaper (by getting builds right the first time).

36 MATERIALS SCIENCE↗

Efficiency of bulk perovskite-sensitized upconversion: Illuminating matters

Photon upconversion via triplet–triplet annihilation could allow for the existing efficiency limit of single junction solar cells to be surpassed. Indeed, efficient upconversion at subsolar fluences has been realized in bulk perovskite-sensitized systems. Many questions have remained unanswered, in particular, regarding their behavior under photovoltaic operating conditions. Here, we investigate the impact of repeated and continuous illumination on bilayer perovskite/rubrene upconversion devices. We find that variations of the underlying perovskite carrier recombination dynamics greatly impact the upconversion process. Trap filling and triplet sensitization are in direct competition: more saturated trap states in the perovskite and, thus, longer underlying perovskite photoluminescence lifetimes allow for an increased number of carriers to diffuse to the perovskite/rubrene interface and undergo charge extraction to the triplet state of rubrene. As a result, the upconversion efficiency is greatly influenced by the underlying trap density: the upconverted photoluminescence intensity increases by two orders of magnitude under continuous illumination for 4 h. This shows that the upconversion efficiency is difficult to define for this system. Importantly, these results indicate that perovskite-sensitized upconversion devices exhibit peak performance under continuous illumination, which is a requirement for their successful integration into photovoltaics to help overcome the Shockley–Queisser limit in single junction solar cells.

VanOrman, Zachary A. (ORCID:000000027773012X)↗

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli.

Here, we report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

Mu2e-II: Muon to electron conversion with PIP-II

An observation of Charged Lepton Flavor Violation (CLFV) would be unambiguous evidence for physics beyond the Standard Model. The Mu2e and COMET experiments, under construction, are designed to push the sensitivity to CLFV in the mu to e conversion process to unprecedented levels. Whether conversion is observed or not, there is a strong case to be made for further improving sensitivity, or for examining the process on additional target materials. Mu2e-II is a proposed upgrade to Mu2e, with at least an additional order of magnitude in sensitivity to the conversion rate over Mu2e. The approach and challenges for this proposal are summarized. Mu2e-II may be regarded as the next logical step in a continued high-intensity muon program at FNAL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗