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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Electron Cloud Simulations for the Electron-Ion Collider in Brookhaven National Laboratory

For high-intensity circular accelerators and storage rings, if the secondary electron emission yield (SEY) of the vacuum chamber surfaces is high, an EC (Electron Cloud) could build up with the passage of the circulating beam. The presence of EC can strongly affect the beam quality, such as transverse instabilities, transverse emittance growth, and beam loss. Furthermore, the heat load from EC can exceed the available cryogenic capability. For the RHIC superconducting (SC) arc magnets, to be used for the hadron storage ring of the Electron-Ion Collider (EIC), the dynamic heat load budget is 0.5 W/m to the 4.5 K stainless steel beam pipe. This can limit the maximum beam bunches or intensity of the EIC, hence diminishing the luminosity provided by the EIC. The EC has affected the beam instability and significantly contributed to cryogenic heat load in the Large Hadron Collider (LHC). Positron storage rings for which ECs have been a critical factor in the design and performance include KEKB in Japan and EC buildup remains one of the concerns for future high-intensity accelerators design. EC considerations have driven the SuperKEKB collider design and the positron damping ring for the proposed International Linear Collider (ILC). The LHC luminosity upgrade is contingent on reducing the bunch spacing to 25 ns; at this bunch spacing, severe EC buildup has been observed. The success of the upgrade is likely contingent on limiting EC buildup. To study the EC heat load, we did some EC simulations with PyECLOUD code for the dipole, quadrupole, sextupole magnets, and the warm (drift) section of the EIC hadron storage ring. PyECLOUD is an EC simulation code developed by CERN. The code has been validated and used to study EC in the LHC, SPS, and PS. To eliminate EC buildup, the sources of electrons must be minimized. First, we will reduce the production of electrons due to residual gas ionization by specifying the maximum gas density, which requires a vacuum chamber with low electron-stimulated desorption (ESD) yields and a sufficient (preferably distributed) pumping speed. Second, we should reduce the secondary electrons with a lower secondary electron yield (SEY) material.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Nanomolar Sensitivity Chirality Transfer from Designed Helical Repeat Proteins to Achiral CdS Nanorods

Bridging chirality across length scales with inorganic− organic hybrid materials is a rapidly expanding area of research. Here, we establish asymmetry at CdS nanorod (NR) interfaces using a designed helical repeat protein bearing four cysteine residues (DHR- 4Cys). Hydrophobic NRs are transferred into water with glycine, and then glycine is displaced by DHR-4Cys, leveraging the thiophilicity of cadmium. Circular dichroism (CD) in the visible, coincident with CdS electronic transitions, reveals a chiral DHR-4Cys:CdS interface. Here, the dissymmetry factor [g-factor = 4.5 × 10 −4 (short NRs) and 5.0 × 10 −4 (long NRs)] is weakly dependent on the NR length, and CD persists at nanomolar protein loadings. Additionally, control experiments demonstrate that DHR-4Cys:CdS NR chirality is dictated by the local coordination of Cys with no significant contribution from the chiral secondary structure of the protein (g-factors of short and long Cys:CdS NRs are 4.8 × 10 −4 and 4.0 × 10 −4 , respectively). Together with far-UV CD and transmission electron microscopy, which provide evidence of preserved protein structure, these results provide the first demonstration that a structurally defined protein can induce chirality in CdS nanocrystals while maintaining protein structure at biologically relevant concentrations.

Cadmium sulfide↗
DOE OSTI2020

Modeling the Impact of Flexible CHP on the Future Electric Grid In California

Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States. Typically fueled with natural gas, a CHP system combines a prime mover (such as a reciprocating engine) with a generator and heat recovery equipment, allowing operation at very high efficiencies (65–85%). Traditionally, CHP systems have been configured to serve local electrical and thermal loads at the sites where they are deployed. Units are sized to ensure a high capacity factor for the equipment, and the electricity generated tends to be used on site. CHP units in the United States already generate over 12% of the nation’s electricity. However, CHP’s potential benefits could be much greater if power generated could be used beyond the site, because the analysis was performed under the assumption that sites could use all the thermal output. Analysis of a few key sectors confirmed that this assumption is valid (for more information, see Appendix E). Those benefits could include improved grid reliability and resilience, as well as lower-cost options for providing energy and other grid services. The potential benefits also align well with grid modernization objectives, as shown in Combined heat and power (CHP) systems provide electricity and process heat at more than 4,400 industrial and commercial facilities across the United States., and greater electrification of loads, driven by carbon reduction priorities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Understanding the Origin of Negative Temperature Dependence and Activity of N-Coordinated Cobalt Sites During Ethylene Dimerization

The on-demand production of short-chain linear alpha olefins (LAOs; C4-C8) via C2H4 dimerization and oligomerization is industrially attractive, prompting extensive research on designing active, selective, and stable catalysts for industrial use. Cobalt supported on ammoniated carbon (Co(NH3)x/C) catalysts have shown remarkable activity and selectivity in this process. However, critical aspects such as the active phase, active site structure, the role of the catalyst support, cobalt loading effects, and the inverse correlation of the reaction rate with temperature remain inadequately understood. This study systematically explores these factors using a combination of steady-state differential catalytic tests, in situ molecular characterization including diffuse reflectance UV-Vis (DR-UV-Vis), Infrared, and Raman spectroscopies, and ex situ X-ray diffraction (XRD) and high annular aberration-corrected dark field transmission electron microscopy (HAADF-STEM). Various supports (SiO2, Al2O3, NH4-ZSM-5, g-C3N4, and C) and cobalt loadings (1.0-3.0 Co nm-2) were studied to determine the optimal catalyst composition and identify the active phase and sites. Carbon-supported catalysts uniquely produce C4-8 LAOs during C2H4 dimerization, with site-time-yield remaining constant (~10-3 s-1) for 1.0-4.0 Co nm-2 at prolonged reaction times (24-48?h time-on-stream). At higher loadings of 6.0 Co nm-2, the formation of crystalline CoO and Co3O4 phases reduces catalytic activity and LAO selectivity. Our findings show that active catalysts lack crystalline cobalt oxides and instead feature dispersed Co2+ sites, tetra-coordinated to a mix of N/NH3 and O/H2O ligands, which catalyze C2H4 dimerization via the Cossee-Arlman mechanism, exhibiting 1st order dependence on C2H4 concentration. The observed inverse rate-temperature correlation is attributed to compensation effects (i.e., presence of Cremer-Constable relationship) linked to changes in adsorption enthalpic and entropic factors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sparse Control Synthesis for Uncertain Responsive Loads With Stochastic Stability Guarantees

In this report, recent studies have demonstrated the potential of flexible loads in providing frequency response services, predominantly due to their availability and cost-effectiveness. However, uncertainty and variability in various weather-related and end-use behavioral factors often impact the reliability of demand-side control performance. This work addresses this problem with the design of a demand-side control to achieve frequency response under load uncertainties. Our approach involves modeling the load uncertainties via stochastic processes that appear as both multiplicative and additive in the power system dynamics. Recently developed mean square exponential stability (MSES) results for continuous-time linear stochastic systems are applied to pose the control synthesis problem which results in an LMI-based optimization problem. Additional costs and constraints are added to the LMI-based controller synthesis to ensure MSES, improve closed-loop transient performance, maximize tolerable uncertainties, and promote sparsity in the controller. Additionally, the fundamental limitations between the tolerable uncertainties and control efforts while ensuring MSES are discussed. Further, the control synthesis problem for the case of the full-state measurement is generalized to the case of partial-state measurements. The proposed control synthesis is illustrated on an IEEE 39 bus system with rigorous studies to demonstrate the role of sparsity, closed-loop transient performance, tolerable uncertainties, and control efforts while ensuring MSES and achieving frequency response.

42 ENGINEERING↗
DOE OSTI2025

Factors influencing recent trends in retail electricity prices in the United States

This study analyzes the primary drivers of recent state-level trends in U.S. retail electricity prices. We summarize pricing trends, explore descriptive relationships, and employ regression models to quantify the influence of various factors. Although the recent national rise in retail prices has largely tracked inflation, state-level trends vary widely. We identify a number of factors that explain trends in subsets of states. States with the greatest price increases typically exhibited shrinking customer loads—partially linked to growth in net metered behind-the-meter solar—and had renewables portfolio standards (RPS) in concert with relatively costly incremental renewable energy supplies. By contrast, recent utility-scale wind and solar deployment that occurred outside RPS programs (but that benefited from tax incentives) had no discernible impact on increased retail prices. Hurricanes, storms and wildfires also contributed to sizable price increases in some states, most notably in California, where wildfire risk mitigation and liability insurance were major cost drivers. Fluctuations in natural gas prices—particularly following the onset of the Ukraine-Russia war—further contributed to sharp price increases through 2022–2023 in many states, with moderation in 2024. The relative influence of these factors varies across states and over time, and relationships may change in the future. Nonetheless, the findings underscore the diverse set of price determinants and highlight the need for continued research to inform effective policy and ensure customer affordability.

Customer load↗
DOE OSTI2022

A Data Quality-Aware Framework to Reliably Forecast Photovoltaic Generation and Consumer Load for an Improved Resilience of Microgrids

Photovoltaic (PV) power and consumer load forecasting plays a critical role to ensure operational resilience of the electric grid. Most data-driven forecasting algorithms rely heavily on the continuous availability of good quality data for periodic training and validation. When deployed at the grid’s edge, prolonged disruptions to communications during extreme events degrade data quality. Factors such as missing observations, epistemic uncertainties, data drift, and concept drift are manifestations of data quality that impact the generalization of such field-deployed forecasting models. Currently, there exists no mechanism in the literature to dynamically switch between models under varying degrees of data quality as quantified by certain metrics for each factor highlighted above. This paper addresses this shortcoming by conceptually introducing a data qualityaware framework for reliable PV generation and consumer load forecasting. The framework’s design incorporates components of missing values, divergence tests, and continuous monitoring of generalization performance to detect changes in data quality caused by communications disruptions and trigger specific classes of forecasting models grouped under three use cases (UC1- UC3). As a first step towards validating this framework, real data collected from an actual field microgrid system is used to demonstrate the viability of the three use cases. Results show that the performance is the best in UC1 with an unadjusted R-square value of 0.954, followed by 0.939 for UC2 and 0.757 for UC3.

Sundararajan, Aditya↗
DOE OSTI2022

Estimation of process steady state with autoregressive models and Bayesian inference

To improve efficiency, separations engineers will typically design process circuits containing recirculating streams, which mix one or more of the process outputs with the feed material. Doing so can improve efficiency, but will cause a delay in the system reaching steady state conditions until the recirculating load mass flows stabilize. In testing separation circuits, engineers will often test a variety of factors and complete an analysis from sample results. Knowledge of if a process is at steady state, as well as the steady state conditions of a process, is essential for a valid techno-economic analysis. However, the definition of process steady state is often poorly defined, or does not include uncertainty quantification. If the performance of a process operating under two different sets of conditions are compared, an engineer who does not test for steady state or quantify steady state conditions risks producing a faulty analysis. In this work, a Bayesian statistical method for testing if all streams are at steady state is further motivated and then derived. Then after testing for steady state, the same model is used with a prior distribution that enforces a steady state assumption to estimate steady state conditions. Further, these methods were validated in a solvent extraction pilot plant where steady state conditions for all outflows were inferred with uncertainty quantification. Analysis is completed with functions available to the reader as part of the BayesMassBal (V 1.1.0) software package written in R.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Supersaturation, buoyancy, and deep convection dynamics

Motivated by recent discussions concerning differences of convective dynamics in polluted and pristine environments, the so-called convective invigoration in particular, this paper provides an analysis of factors affecting convective updraft buoyancy, such as the in-cloud supersaturation, condensate and precipitation loading, and entrainment. We use the deep convective period from simulations of daytime convection development over land discussed in our previous publications. An entraining parcel framework is used in the theoretical analysis. We show that for the specific case considered here, finite (positive) supersaturation noticeably reduces pseudo-adiabatic parcel buoyancy and cumulative convective available potential energy (cCAPE) in the lower troposphere. This comes from keeping a small fraction of the water vapor in a supersaturated state and thus reducing the latent heating. Such a lower-tropospheric impact is comparable to the effects of condensate loading and entrainment in the idealized parcel framework. For the entire tropospheric depth, loading and entrainment have a much more significant impact on the total CAPE. For the cloud model results, we compare ensemble simulations applying either a bulk microphysics scheme with saturation adjustment or a more comprehensive double-moment scheme with supersaturation prediction. We compare deep convective updraft velocities, buoyancies, and supersaturations from all ensembles. In agreement with the parcel analysis, the saturation-adjustment scheme provides noticeably stronger updrafts in the lower troposphere. For the simulations predicting supersaturation, there are small differences between pristine and polluted conditions below the freezing level that are difficult to explain by standard analysis of the in-cloud buoyancy components. By applying the piggybacking technique, we show that the lower-tropospheric buoyancy differences between pristine and polluted simulations come from a combination of temperature (i.e., latent heating) and condensate loading differences that work together to make polluted buoyancies and updraft velocities slightly larger when compared to their pristine analogues. Overall, the effects are rather small and contradict previous claims of a significant invigoration of deep convection in polluted environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

U.S. Distribution Transformer Demand Phase III - Key Drivers and Managing Demand [Slides]

This presentation demonstrates a significant analysis, on forecasting the demand for distribution transformers. The analysis is conducted for the United States, estimating the initial in-service capacity of these assets, and forecasting demand for these assets through 2050 with several sensitivities conducted. It examines not only demand for these assets, but importantly, how utility planning practices can impact the demand for theses assets in time. Under load growth scenarios, whether utilities practice like-for-like replacement strategies as failures occur, or whether they practice proactive up-sizing, anticipating electric load growth, can have major impacts on future demand. It also examines several other growth factors, such as the increasing demand for step-up transformers, which share many of the same characteristics as distribution transformers, and the demand for specific transformers for large project growth from data centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Use of Novel Diglycolamide Extractants in Liquid-liquid Separations of Light Rare Earths

Creation of a novel extractant that can improve rare earth separations both economically and environmentally will be pivotal for industry progression. Diglycolamide (DGA) extractants provide chemistries that support this goal by serving as an extractant with high affinity for lanthanides and improved separation factors for light rare earths as compared to current extractants like PC88A. Initial organic phase loading capacity and phase dispersion tests performed with various modified DGAs generated results that were unfavorable for industrial processing, but further modification of the DGA alkyl chain substituents have resulted in new structures with promising results. Dispersion time measurements taken in small scale batch contacts of the extractant with a simulated leach liquor containing La, Ce, Nd, and Pr support implementation in both mixer-settlers and centrifugal contactors for larger scale separations. Furthermore, this confirmation allowed for preliminary flowsheet design using extraction equilibria at various organic to aqueous flow ratios (O/A) for extraction, scrubbing, and stripping stages. These values along with expected product/effluent compositions for each section aid in the testing for specific distribution ratios and final flowsheet design. Implementation of the DGA extractant into solvent extraction equipment will provide essential information for the next steps of this project and how this extractant may be optimized for future applications.

42 ENGINEERING↗
DOE OSTI2024

Results of High Order Modes Spectra Measurements in 1.3 GHz Cavities for LCLS-II

Fermilab recently completed production and testing of 1.3 GHz cryomodules for the LCLS-II project. Each cryomodule consists of eight TESLA-shaped superconducting elliptical cavities equipped with two High Order Mode (HOM) coupler ports. Measurement of the HOM spectrum is part of the incoming quality control of cavities at room temperature and the final qualification cold test of cryomodules at the Cryomodule Test Facility (CMTF). In this paper we describe the procedure for measuring the HOM spectrum along with further data processing. Finally, we present accumulated statistics of individual HOM frequencies and quality factors related to various cavity vendors and discuss the possible contribution of HOMs to heat loads and beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Micromechanical properties of spherical and facetted He bubble loaded copper

Exploring new irradiation resistant materials requires understanding their mechanical responses to irradiation. Resistance to helium bubble formation and understanding bubble effects on the mechanical response of candidate materials are crucial factors to qualify materials as irradiation resistant. Here, in this paper, we explore the effect of spherical and facetted helium bubbles on the mechanical response of copper via in-situ micromechanical tensile testing at room temperature. Bubble formation and shape effects on strength and ductility, and their behavior on grain boundaries are discussed and compared to literature. Loading Cu with helium bubbles is shown here to increase strength but decrease ductility.

42 ENGINEERING↗
DOE OSTI2024

Geomagnetically Induced Current Field Test on Large Grid-Connected Power Transformers: Analysis, Model Development, and Simulations

Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.

EMTDC↗
DOE OSTI2021

Microbe-Encapsulated Silica Gel Biosorbents for Selective Extraction of Scandium from Coal Byproducts

Establishing an inexpensive and environmentally friendly scandium (Sc) supply is critical for the development of clean energy technologies. However, refining Sc from Sc-bearing sources using current technologies poses economic and environmental challenges due to its low concentration relative to base metals and chemically similar lanthanides. In this work, we developed a biosorption-based flow-through process for extraction of Sc from low-grade feedstocks. A novel biosorbent material was synthesized by encapsulating Arthrobacter nicotianae, a bacterium that selectively adsorbs Sc, within a porous silica matrix. Through the use of several complementary microscopy techniques, we demonstrated a highly porous biosorbent structure with a high cell-loading density and a homogenous cell distribution. Batch adsorption assays revealed selective Sc adsorption over lanthanides and common based metals, with the exception of Fe(III), as evidenced by separation factors greater than 50. The MESG particles were packed into fixed-bed columns to enable adsorption under flow-through conditions, which demonstrated effective Sc extraction at flow rates up to 0.08 cm/s and high stability for reuse; greater than 95% of the adsorption capacity was maintained after 10 consecutive adsorption/desorption cycles. When applied to a lignite coal leachate, whose Fe content was depleted through pH-mediated precipitation, the MESG particles yielded Sc breakthrough at 30 bed volumes, whereas all other metals broke through after only a few bed volumes. Following desorption, an eluate with a 124-fold increase in Sc purity was achieved relative to the lignite leachate with Sc constituting 96.4% of the total REEs. This study established a rapid, facile, and scalable cell immobilization approach that enables the use of microbial biomass for Sc recovery from low-grade sources.

Dong, Ziye↗
DOE OSTI2020

Characterization and CST Batch Contact Equilibrium Testing of Modified Tank 9H Process Supernate Samples in Support of TCCR

The Tank Closure Cesium Removal (TCCR) system uses ion exchange columns filled with crystalline silicotitanate (CST) media to process radioactive waste solutions for the removal of ¹³⁷Cs. TCCR currently focuses on dissolving Savannah River Site (SRS) radioactive tank waste (primarily sodium saltcake solids) within Tank 10H followed by at-tank ion exchange column treatment. Two supernate batches from Tank 10H have been processed through the TCCR unit and processing of a third batch is expected soon. After processing of this supernate batch, plans are to replace the CST columns and process dissolved salt solution from Tank 9H through Tank 10H and then through the new CST columns installed in the TCCR unit. The new columns are expected to contain either a media similar to an archived CST batch (IE-911) or the R9120-B CST media used in the current TCCR columns (the two materials are fundamentally the same; just different specifications, product names, and preconditioning steps). Samples of Tank 9H dissolved saltcake were received at the Savannah River National Laboratory (SRNL) and characterized. The Tank 9H supernate contained a high sodium concentration (~9.6 M Na⁺) and will require dilution to near 6 M [Na⁺] prior to processing through the TCCR unit. The cesium concentration in Tank 9H is currently significantly higher than was observed with Tank 10H. Three dilutions of the Tank 9H supernate were conducted to mimic possible dilutions that could be conducted in the tank farm prior to TCCR processing using inhibited water, sodium hydroxide, and sodium nitrate solutions. Dilution #1 was prepared by diluting the Tank 9H supernate by a factor of 1.6 with inhibited water, Dilution #2 was prepared by diluting the Tank 9H supernate by a factor of 3.7 with a mixed sodium hydroxide/sodium nitrate diluent, and Dilution #3 was prepared by also diluting by a factor of 3.7 but with sodium hydroxide only. All three dilutions have similar Na⁺ concentrations (~6 M), but Dilutions #2 and #3 contain significantly less cesium. Major and key minor components of the diluted Tank 9H supernate samples are provided in Table ES-1. Batch contact equilibrium tests were conducted with the Tank 9H dilutions and the two different CST media batches being considered for use in the new TCCR columns. Results are summarized in Table ES-2 and compared to ZAM model predictions. The highest cesium distribution coefficient and percent removal were observed with Dilution #3. IE-911 CST (an archived CST media batch) was more effective at removing cesium than the more recently prepared R9120-B CST media, though both media samples removed >88% of the cesium and the differences may not be statistically different considering the overall uncertainty. Based on the results, maximum cesium loadings were calculated for each CST media type and Tank 9H dilution. In general, maximum cesium loadings from dilutions of this supernate batch are quite high (approaching 0.1 mmol total Cs⁺/g CST for Dilution #1). The highest calculated maximum ¹³⁷Cs loading for the Tank 9H dilutions using the ZAM model with input of the tank compositions and batch contact results was 207 Ci/kg CST (Dilution #1 with IE-911 CST). In all cases, higher maximum cesium loading values were predicted for IE-911 CST versus R9120-B, although the differences varied considerably between the dilutions. The maximum loading value for IE-911 CST with Tank 9H Dilution #1 was only 7% higher than the maximum loading for R9120-B. The maximum loading value for IE-911 CST with Dilution #3 was 24% higher than the maximum loading for R9120-B. Dilution #2 was intermediate between these values. Note that these maximum loading values are the theoretical calculated values, and actual operating conditions will cause differences. A CST binder dilution (correction) factor near 0.7 (relative to pure powder CST) was required for each batch contact test with IE-911 engineered CST using the three Tank 9H dilutions. Correction factors calculated for R9120-B CST ranged from 0.56 to 0.66 for the three dilutions. Following the batch contact tests, the CST samples were isolated from the Tank 9H solution, washed, dried, and digested in acid following established procedures. The analysis results are provided in Table ES-3. Total cesium loading values determined by CST digestion were similar to the calculated loading values based on solution analysis (Table ES-2) for all samples. In addition, the CST was observed to load calcium (R9120-B sample only), iron, strontium, lead, uranium, and plutonium after contact with the waste supernate, as has been observed previously.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Best Practices for Smart Grid-Interactive Efficient Building Ready Performance Contracts

Grid-interactive efficient building (GEB) measures reduce costs and optimize energy use for additional grid services by coordinating building energy loads and providing continuous demand management. Incorporating GEB energy conservation measures (ECMs) in performance contracts is reliant upon multiple factors. These factors include site selection with utility tariffs and incentives favorable to GEB, the identification of GEB as a priority in the initial stages of the contracting process, integration of GEB within comprehensive performance contracts with multiple other ECMs, and careful consideration of GEB measurement and verification (M&V) for energy savings performance contracts (ESPCs) and performance assurance for utility energy service contracts (UESCs).

building energy loads↗
DOE OSTI2020

Assessment of Demographic, Genetic, and Imaging Variables Associated With Brain Resilience and Cognitive Resilience to Pathological Tau in Patients With Alzheimer Disease

Importance: Better understanding is needed of the degree to which individuals tolerate Alzheimer disease (AD)-like pathological tau with respect to brain structure (brain resilience) and cognition (cognitive resilience). Objective: To examine the demographic (age, sex, and educational level), genetic (APOE-ε4 status), and neuroimaging (white matter hyperintensities and cortical thickness) factors associated with interindividual differences in brain and cognitive resilience to tau positron emission tomography (PET) load and to changes in global cognition over time. Design, setting, an participants: In this cross-sectional, longitudinal study, tau PET was performed from June 1, 2014, to November 30, 2017, and global cognition monitored for a mean [SD] interval of 2.0 [1.8] years at 3 dementia centers in South Korea, Sweden, and the United States. The study included amyloid-β-positive participants with mild cognitive impairment or AD dementia. Data analysis was performed from October 26, 2018, to December 11, 2019. Exposures: Standard dementia screening, cognitive testing, brain magnetic resonance imaging, amyloid-β PET and cerebrospinal fluid analysis, and flortaucipir (tau) labeled with fluor-18 (18F) PET. Main outcomes and measures: Separate linear regression models were performed between whole cortex [18F]flortaucipir uptake and cortical thickness, and standardized residuals were used to obtain a measure of brain resilience. The same procedure was performed for whole cortex [18F]flortaucipir uptake vs Mini-Mental State Examination (MMSE) as a measure of cognitive resilience. Bivariate and multivariable linear regression models were conducted with age, sex, educational level, APOE-ε4 status, white matter hyperintensity volumes, and cortical thickness as independent variables and brain and cognitive resilience measures as dependent variables. Linear mixed models were performed to examine whether changes in MMSE scores over time differed as a function of a combined brain and cognitive resilience variable. Results: A total of 260 participants (145 [55.8%] female; mean [SD] age, 69.2 [9.5] years; mean [SD] MMSE score, 21.9 [5.5]) were included in the study. In multivariable models, women (standardized β = -0.15, P = .02) and young patients (standardized β = -0.20, P = .006) had greater brain resilience to pathological tau. Higher educational level (standardized β = 0.23, P < .001) and global cortical thickness (standardized β = 0.23, P < .001) were associated with greater cognitive resilience to pathological tau. Linear mixed models indicated a significant interaction of brain resilience × cognitive resilience × time on MMSE (β [SE] = -0.235 [0.111], P = .03), with steepest slopes for individuals with both low brain and cognitive resilience. Conclusions and relevance: Results of this study suggest that women and young patients with AD have relative preservation of brain structure when exposed to neocortical pathological tau. Interindividual differences in resilience to pathological tau may be important to disease progression because participants with both low brain and cognitive resilience had the most rapid cognitive decline over time.

60 APPLIED LIFE SCIENCES↗