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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 1,675 records · Page 93
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Moist Potential Vorticity Model for Midlatitude Long-Lived Mesoscale Convective Systems over Land

Mesoscale convective systems (MCSs) bring large amounts of rainfall and strong wind gusts to the midlatitude land regions, with significant impacts on local weather and hydrologic cycle. However, weather and climate models face a huge challenge in accurately modeling the MCS life cycle and the associated precipitation, highlighting an urgent need for a better understanding of the underlying mechanisms of MCS initiation and propagation. From a theoretical perspective, a suitable model to capture the realistic properties of MCSs and isolate the bare-bones mechanisms for their initiation, intensification, and eastward propagation is still lacking. To simulate midlatitude MCSs over land, we develop a simple moist potential vorticity (PV) model that readily describes the interactions among PV perturbations, air moisture, and soil moisture. Multiple experiments with or without various environmental factors and external forcing are used to investigate their impacts on MCS dynamics and mesoscale circulation vertical structures. The result shows that mechanical forcing can induce lower-level updraft and cooling, providing favorable conditions for MCS initiation. A positive feedback among surface winds, evaporation rate, and air moisture similar to the wind-induced surface heat exchange over tropical ocean is found to support MCS intensification. Both background surface westerlies and vertical westerly wind shear are shown to provide favorable conditions for the eastward propagation of MCSs. Last, our result highlights the crucial role of stratiform heating in shaping mesoscale circulation response. In conclusion, the model should serve as a useful tool for understanding the fundamental mechanisms of MCS dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

HPC4Mfg with Carbon Inc.

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

42 ENGINEERING↗
DOE OSTI2021

Development of a Multi-physics Model to Optimize Continuous Liquid Interface Production (CLIP) for Additive Manufacturing (Carbon3D HPC4Mfg Final Report)

Continuous Liquid Interface Production (CLIP) is poised to bring additive manufacturing to multiple American manufacturing sectors owing to its unique combination of rapid print speeds and material options that resemble injection molding thermoplastics. In spite of these benefits, CLIP is still a maturing process. To improve our understanding and control of the process, this project developed a multi-physics computational model that encompasses the coupled chemical-physical processes of photopolymerization and fluid flow to predict part outcomes. A physically predictive model can enable rapid optimization of CLIP and reduce the current cycle time and waste associated with optimization by four-fold. Ultimately, this effort will help open the U.S. $400B plastic manufacturing industry to the key benefits of additive manufacturing, namely mass customization, unlimited design space, and a cost- and energy-effective path to mainstream manufacturing. In the course of the project we produced a model which coupled fluid-flow, species transport, and photochemistry to model the Carbon CLIP process. As the development proceeded, we validated the code against theory and experiments. The resulting code was transferred to Carbon, and we expect it to be a useful part of their modeling capability. Future work includes improvements to the fluid solver’s robustness and performance, along with the addition of additional physics models.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The STAT7 Code for Statistical Propagation of Uncertainties in Steady State Thermal Hydraulics Analysis of Plate Fueled Reactors

The STAT7 software was developed to perform steady-state thermal hydraulic analyses. Application of the software is for non-power research and test reactors, including conversion to low-enriched uranium fuel of U.S. High-Performance Research Reactors such as MITR-II. Since it can be necessary to repeat analysis during fuel reloading, STAT7 accommodates flexibility in analyzing many realistic aspects of reactor fuel management. STAT7 uses a Monte Carlo approach to model common fabrication parameters and other key reactor analysis uncertainties required for research and test reactor thermal hydraulic analyses. These safety calculations are ultimately intended to protect against high fuel plate temperatures due to critical heat flux or departure from nucleate boiling or onset of flow instability; but additional margin is obtained by basing the limiting safety settings on avoiding onset of nucleate boiling. STAT7 can simultaneously analyze all of the axial nodes of all of the fuel plates and all of the coolant channels for one lateral stripe of a fuel element. The stripes run the length of the fuel, from the bottom to the top. Power splits are calculated for each axial node of each plate to determine how much of the power goes out each face of the plate. By running STAT7 multiple times, full core analysis can be performed by analyzing the margin to onset of nucleate boiling and onset of flow instability for each axial node of each stripe of each plate of each element in the core.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1985

ENCOMPASS: A SAGA based environment for the compositon of programs and specifications, appendix A

ENCOMPASS is an example integrated software engineering environment being constructed by the SAGA project. ENCOMPASS supports the specification, design, construction and maintenance of efficient, validated, and verified programs in a modular programming language. The life cycle paradigm, schema of software configurations, and hierarchical library structure used by ENCOMPASS is presented. In ENCOMPASS, the software life cycle is viewed as a sequence of developments, each of which reuses components from the previous ones. Each development proceeds through the phases planning, requirements definition, validation, design, implementation, and system integration. The components in a software system are modeled as entities which have relationships between them. An entity may have different versions and different views of the same project are allowed. The simple entities supported by ENCOMPASS may be combined into modules which may be collected into projects. ENCOMPASS supports multiple programmers and projects using a hierarchical library system containing a workspace for each programmer; a project library for each project, and a global library common to all projects.

Terwilliger, Robert B.↗
DOE OSTI2023

Evaluating U.S. Natural Gas Environmental Performance

This work summarizes the U.S. Department of Energy National Energy Technology Laboratory's (NETL) modeling and analysis of natural gas environmental performance. Over the past year, NETL updated its U.S. natural gas supply chain life cycle baseline model to incorporate 2020 data, regionalize the transmission and distribution network into six regions, incorporate improved gathering and boosting stage and distribution stage emissions factors, and assign environmental burdens among the various co-products (i.e., crude oil, natural gas liquids, natural gas) of the natural gas supply chain. The updated natural gas model helps generate more comprehensive and regionalized natural gas profiles, mapping production basins to the relevant transmission and distribution regions downstream. The work incorporates data from multiple peer reviewed measurement-based studies to achieve the objective of providing a comprehensive understanding of emissions from the U.S. natural gas supply chain. This presentation also explores future work by NETL to develop a platform that enables stakeholders to customize key parameters within the natural gas LCA model and observe the corresponding effects on the carbon intensity of the overall supply chain. The platform aims to offer a convenient method for stakeholders to obtain relevant insights from the updated model, without diving deep into the intricacies of the NETL natural gas model with hundreds of parameters and linkages.

Khutal, Harshvardhan↗
DOE OSTI2024

TRISO Fuel for High-Temperature Passively-Safe Nuclear Reactors

The poster entitled "TRISO Fuel for High-Temperature Passively-Safe Nuclear Reactors" presents reasons why TRISO fuel is a safe nuclear fuel. The poster contains four blocks: Multiple barriers to fission product release, Thermal stability, Chemical compatibility and Safety and Performance. Each block present information on the TRISO fuel in terms of the mechanical, chemical and thermal properties. In summary the safety and performance of the TRISO fuel based on the experimental results is shown.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska" DOI: 10.1088/1748-9326/ac4362.The dataset contains "ecosys" model outputs reported in Shirley et al. (2022) that explored how climate warming will shift carbon cycle seasonality in Alaska. The study used analysis of seasonal dynamics to support the prediction that high-latitude ecosystems are carbon sinks and will continue to accumulate carbon throughout the century. The study predicts surprisingly large increases in spring net carbon uptake that result in larger net carbon uptake in spring than in summer by year 2100. Included as *.nc files are modeled daily net ecosystem exchange (NEE), net primary productivity (NPP), heterotrophic respiration (Rh), autotrophic respiration (Ra), gross primary productivity (GPP), and plant nitrogen uptake. The output is provided (1) at 25 km resolution across Alaska; (2) for years 2010 through 2100. Scripts to generate publication figures included as text files (*.m) from MATLAB. A user guide included as *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Numerical Simulations of Orographic Convection across Multiple Gray Zones

Idealized simulations are used to determine the sensitivity of moist orographic convection to horizontal grid spacing Δ h . In simulated mechanically (MECH) and thermally (THERM) forced convection over an isolated ridge, Δ h is varied systematically over both the deep-convection (Δ h ~ 10 –1 km) and turbulence (Δ h ~ 1 km–100 m) gray zones. To aid physical interpretation, a new parcel-based bulk entrainment/detrainment diagnosis for horizontally heterogeneous flows is developed. Within the deep-convection gray zone, the Δ h sensitivity is dominated by differences in parameterized versus explicit convection; the former initiates convection too far upstream of the ridge (MECH) and too early in the diurnal heating cycle (THERM). These errors stem in part from a large underprediction of parameterized entrainment and detrainment. Within the turbulence gray zone, sensitivities to Δh arise from the representation of both subcloud- and cloud-layer turbulence. As Δ h is decreased, MECH exhibits stronger cloud-layer entrainment to enhance the convective mass flux M co , while THERM exhibits stronger detrainment to suppress Mco and delay convection initiation. The latter is reinforced by increased subcloud turbulence at smaller Δ h , which leads to drying and diffusion of the central updraft responsible for initiating moist convection. Numerical convergence to a robust solution occurs only in THERM, which develops a fully turbulent flow with a resolved inertial subrange (for Δ h ≤ 250 m). In MECH, by contrast, turbulent transition occurs within the orographic cloud, the details of which depend on both physical location and Δ h .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

Studies of Trace Gas Chemical Cycles Using Inverse Methods and Global Chemical Transport Models

We report progress in the first year, and summarize proposed work for the second year of the three-year dynamical-chemical modeling project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for long lived gases important in ozone depletion and climate forcing, (b) utilization of inverse methods to determine these source/sink strengths using either MATCH (Model for Atmospheric Transport and Chemistry) which is based on analyzed observed wind fields or back-trajectories computed from these wind fields, (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple titrating gases, and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important goals include determination of regional source strengths of methane, nitrous oxide, methyl bromide, and other climatically and chemically important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal protocol and its follow-on agreements and hydrohalocarbons now used as alternatives to the restricted halocarbons.

Prinn, Ronald G.↗
DOE OSTI2023

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A systematic exploration of the hydrolysis products of the uranium trioxide polymorphs and their optical vibrational spectra

Study of the uranium trioxide (UO 3 )-water system is complex with inconclusive results and limited details in the literature. The UO 3 system is home to at least seven structural polymorphs and an amorphous phase. The proposed hydrolysis products of UO 3 are just as numerous, yet investigations of these alteration products are sporadic and generally antiquated, thus requiring systematic investigations. Recent developments in the understanding of UO 3 phase space, aided by improvements in analytical and computational techniques, necessitate more modern investigations into the uranyl hydroxide family and their naturally occurring mineral counterparts. We present findings from a systematic investigation of the products formed via hydrothermal reactions of common UO 3 polymorphs and discuss how the equatorial coordination of the uranyl/uranyl-like ions within the UO 3 precursors leads to differences in the optical vibrational spectra of the resulting hydrolysis products. The hypo-stochiometric nature of α-UO 2 (OH) 2 allows for the formation of multiple unique uranyl sites and a distortion of the unit cell to a lower symmetry. This study provides, for the first time, an analysis of β-UO 2 (OH) 2 using modern techniques and instrumentation (Raman/infrared spectroscopy and powder x-ray diffraction) and lays a foundation for future time-dependent investigations into the structural dependence of the hydrolysis kinetics of the UO 3 phases. In conclusion, given the prevalence of UO 3 at both ends of the nuclear fuel cycle, an understanding of its behavior with water has applications ranging from nuclear forensics to waste management and environmental transport.

Uranium trioxide↗
DOE OSTI2024

Multifunctional entinostat enhances the mechanical robustness and efficiency of flexible perovskite solar cells and minimodules

Flexible perovskite solar cells (F-PSCs), prized for their nature of soft and high power-weight compatibility, have attracted intensive attention. However, inferior buried perovskite-substrate interfaces due to low interfacial adhesion between perovskites and substrates and large deformation of flexible substrates have greatly limited the performance of F-PSCs. Here, we add organic molecule Entinostat (ET) into hole extraction material Poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA) to enhance the adhesion at the perovskite/substrate interface using the interactions of ET with perovskites, PTAA and indium tin oxide (ITO) through its multiple function groups. Meanwhile, ET added into perovskites reduces the voids at the bottom perovskite film, due to its capability to tune the crystallization of perovskites by forming adduct with lead. Consequently, the inverted small area F-PSCs achieved an efficiency of 23.4%. The flexible perovskite minimodule with an area of 9 cm 2 achieved an aperture efficiency of ~19.0% certified by National Renewable Energy Laboratory. Furthermore, the optimized unencapsulated flexible minimodule retained 84% of the initial efficiency after 5000 bending cycles and retained 90% of the initial PCE (T90) after light soaking for >750 hours.

14 SOLAR ENERGY↗
DOE OSTI2022

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi

Abstract Background Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing—SIP—remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance—the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling. Results Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to 13 C-AMF hyphosphere DNA from a 13 CO 2 plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10–33 atom% 13 C), even though the soils’ overall enrichment was low (1.8 atom% 13 C). We assembled 212 13 C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived 13 C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera . Conclusions Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP—fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat—generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs’ phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Scanning Mobility Particle Sizer (SMPS)-Aerodynamic Particle Sizer (APS) Merged Size Distribution (mergedsmpsaps) Value-Added Product Report

Aerosol particles influence the Earth’s radiation balance directly by absorbing and scattering light and indirectly by influencing cloud formation, properties, and lifetimes. Measurements of aerosol particle optical properties, mass loading, size distributions, microphysical properties, cloud formation properties, and chemical composition are important for understanding the aerosol life cycle and for validating earth system models that predict these quantities. The Atmospheric Radiation Measurement (ARM) user facility’s Aerosol Observing System (AOS) is a highly instrumented platform designed to house instruments that measure many of these aerosol properties in situ. Currently, ARM operates at least four different instruments that measure a portion of the ambient aerosol size distribution. Most users are interested in the entire size distribution or a portion of the size distribution that extends across the measurement range of multiple instruments. However, merging these distributions is not trivial as the instruments employ different measurement principals and, in most cases, report data as a function of different representations of the aerosol diameter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Seeing is Believing: Autonomous Microscopy and the Data Revolution in Materials Science

This presentation explores the transformative potential of autonomous electron microscopy and artificial intelligence (AI) in accelerating materials science discovery, particularly for energy applications and materials operating in extreme environments. We discuss pioneering self-driving laboratories at NREL designed to intelligently probe material synthesis and degradation across multiple scales, aiming to rapidly bridge the gap between atomic-level understanding and the development of high-performance, reliable materials. Utilizing advanced machine learning techniques, such as few-shot learning and multimodal analysis integrating imaging and spectroscopy, we demonstrate methods to extract actionable descriptors for material behavior, quantify complex microstructural evolution, and statistically link synthesis parameters to defect populations. This AI-driven approach promises to accelerate the creation of predictive materials tailored for specific missions, enabling faster development cycles and enhanced material assurance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Impacts of Biofuel Blending on MCCI Ignition Delay with Review of Methods for Defining Cycle-by-Cycle Ignition Points from Noisy Cylinder Pressure Data

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process. Bench experiments can evaluate the expected ignition delay of a fuel via cetane number (CN) or alternative methods such as the indicated cetane number (ICN); however, neither CN nor ICN correlate perfectly with the ignition delay measured in actual engine experiments. Furthermore, there is no standardized methodology on how to quantify MCCI ignition delay from engine cylinder pressure measurements, creating difficulties in cross-study comparison. In this study, several engine ignition delay calculation methods are evaluated for robustness in deriving ignition delay on both a cycle-averaged and cycle-to-cycle basis. Eight biofuel blends with varying ICN, oxygen concentration and other fuel properties were used to study the different methods. This yields a thorough analysis of how certain biofuel blends affect ignition delay and the entire MCCI process, as well as a thorough evaluation of the differences between the ID calculation methods. Many of these methods are equally valid, but the choice of method has a significant impact on the resulting ID, which must be carefully considered when evaluating results across multiple studies.

47 OTHER INSTRUMENTATION↗