Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “SHIFT PROCESSES”

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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Additive Manufacturing: A New Paradigm for the Next Generation of High-Power-Density Direct-Drive Electric Generators: Preprint

In recent years, there has been a growing demand for high-power-density direct-drive generators in the wind industry owing to their high reliability, torque per-unit volume, and conversion efficiencies. However, direct-drive wind turbine generators are very large, low-speed electric machines, which pose remarkable design and manufacturing issues that challenge their upscaling potential and cost of implementation. With air-gap tolerance as the main design driver, the need for high stiffness shifts the focus toward support-structure design that forms a significant portion of the generator's total mass. Existing manufacturing processes allow the use of segmented-steel-weldment disk or spoke-arm assemblies that yield stiffer structures per unit mass but tend to be heavier and more expensive to build. As a result, there is a need for a transformative approach to realize lightweight designs that can also facilitate series production at competitive costs. Inspired by recent developments in metal additive manufacturing (AM), we explore a new freedom in the structural design space with a high potential for weight savings in direct-drive generators. This includes the feasibility of using nonconventional complex geometries, such as lattice-based structures as structurally efficient options. Powder-binder jetting of a sand-cast mold was identified as the most feasible AM technology to produce large-scale generator rotor structures with complex geometry. A parametric optimization study was performed and optimized results within deformation and mass constraints were found for each design. The response to the maximum Maxwell stress due to unbalanced magnetic pull was also explored for each design. Further, a topology optimization was applied for each parameter-optimized design to validate results and provide insights into further mass reduction. These novel designs catered for AM are compared in both deflection and mass to conventional rotor designs using NREL's systems engineering design tool, GeneratorSE. The optimized lattice design with a Ubeam truss resulted in a 24% reduction in structural mass of the rotor and 60% reduction in radial deflection. It is demonstrated that additive manufacturing shifts the focus from manufacturability constraints toward lower mass.

17 WIND ENERGY↗
DOE OSTI2018

Additive Manufacturing: A New Paradigm for the Next Generation of High-Power-Density Direct-Drive Electric Generators

In recent years, there has been a growing demand for high-power-density direct-drive generators in the wind industry owing to their high reliability, torque per unit volume, and conversion efficiencies. However, direct-drive wind turbine generators are very large, low-speed electric machines, which pose remarkable design and manufacturing issues that challenge their upscaling potential and cost of implementation. With air-gap tolerance as the main design driver, the need for high stiffness shifts the focus toward support-structure design that forms a significant portion of the generator's total mass. Existing manufacturing processes allow the use of segmented-steel-weldment disk or spoke-arm assemblies that yield stiffer structures per unit mass but tend to be heavier and more expensive to build. As a result, there is a need for a transformative approach to realize lightweight designs that can also facilitate series production at competitive costs. Inspired by recent developments in metal additive manufacturing (AM), we explore a new freedom in the structural design space with a high potential for weight savings in direct-drive generators. This includes the feasibility of using nonconventional complex geometries, such as lattice-based structures as structurally efficient options. Powder-binder jetting of a sand-cast mold was identified as the most feasible AM technology to produce large-scale generator rotor structures with complex geometry. A parametric optimization study was performed and optimized results within deformation and mass constraints were found for each design. The response to the maximum Maxwell stress due to unbalanced magnetic pull was also explored for each design. Further, a topology optimization was applied for each parameter-optimized design to validate results and provide insights into further mass reduction. These novel designs catered for AM are compared in both deflection and mass to conventional rotor designs using NREL's systems engineering design tool, GeneratorSE. The optimized lattice design with a U-beam truss resulted in a 24% reduction in structural mass of the rotor and 60% reduction in radial deflection. It is demonstrated that additive manufacturing shifts the focus from manufacturability constraints toward lower mass.

17 WIND ENERGY↗
DOE OSTI2011

Fractional dynamics in the light scattering intensity fluctuation in dusty plasma

Light scattering intensity fluctuation in dusty plasma system is studied. The scattered electric field of the laser light is treated as a stationary stochastic process. A nonstandard form of fractional Langevin equation is solved using Green's function approach to obtain the so-called fractional Ornstein-Uhlenbeck process. The empirical correlation function of light intensity fluctuation is fitted with four model correlation functions which are representative of different mechanisms for monodisperse particle transport, namely, the kinetic (ballistic) model, the hydrodynamical (diffusive) model, the hybrid kinetic-hydrodynamic model, and the fractional kinetic model for polydisperse particles. The shifted fractional derivative index is found to be related to power-law exponent of polydisperse dust mass distribution. It is shown that the correlation model based on fractional Ornstein-Uhlenbeck process may provide a novel insight into the complex transport behaviors in dusty plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Dissolution Behavior and Phase Evolution During Aluminum Oxide Dissolution in BOF Slag

Basic oxygen furnace (BOF) slag is a byproduct in the steel making process and is produced in considerable amounts. Thus, its valorization is important. Additives such as Al{sub 2}O{sub 3} can be utilized to modify the composition and mineralogy of the slag provided that a fast and effective dissolution of these additives in molten slags can be ensured. With this in mind, the dissolution of Al{sub 2}O{sub 3} particles in molten BOF slag has been investigated between 1500 and 1600 °C. In all cases, a dissolution zone forms around the dissolving particle which limits the dissolution rate in the melt under natural convection conditions. The dissolution in the current system is found to be an indirect process, wherein crystalline reaction products like CaAl{sub 4}O{sub 7} (CA{sub 2}) and CaAl{sub 2}O{sub 4} (CA) form on the surface of the particles. CA forms at 1500 °C and CA{sub 2} at 1600 °C. These reaction products form a continuous layer on the surface of the dissolving particles but the thickness of this reaction layer remains limited. The experimental data have been utilized to evaluate the dissolution paths. Near the Al{sub 2}O{sub 3}/slag interface, the inter-diffusion of Al{sub 2}O{sub 3} and CaO occurs due to which the dissolution path shifts towards the Al{sub 2}O{sub 3}-CaO binary system. A phenomenological model is presented to explain the evolution of the dissolution process in the current system, wherein the kinetics of the process is used to explain the reaction products formed at 1500 °C and 1600 °C.

36 MATERIALS SCIENCE↗
DOE OSTI2013

On the phase shift between electric potential and plasma density fluctuations in the edge turbulence

In some cases, the phase shift between fluctuations of the electric potential and plasma density helps to identify the instability that governs the turbulent state. In this paper, the basic experimental and theoretical results that denote the possibility (or impossibility) of such identification are briefly discussed. The experimental data based on measurements of the phase shift between the floating potential and ion saturation current fluctuations in the L-2M stellarator-a system with externally imposed magnetic surfaces-are presented (Shchepetov, Kholnov, Fedyanin, et al., Plasma Phys. Controlled Fusion 50, 045001 (2008)). It is shown that the observed phase shift {Omega} varies in a wide range from {pi} to 0, gradually decreasing with deepening inside the plasma. A number of arguments are presented suggesting that {Omega} Almost-Equal-To {pi} can indicate that the process is nonlocal, i.e., oscillations at a given spatial point are driven and mainly determined by the processes localized outside of the observation point. We note that, within the framework of the magnetohydrodynamic theory, plasma was definitely unstable with respect to resistive interchange modes in all cases under study. It is demonstrated experimentally that the widespread notion that the phase shift {Omega} Almost-Equal-To {pi}/2 is characteristic of only resistive interchange modes is hardly universal. The experimental results are analyzed on the basis of analytical estimates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2010

Process development and techno-economic analysis of a novel process for MeOH production from CO2 using solar-thermal energy.

Mitigating and overcoming environmental problems brought about by the current worldwide fossil fuel-based energy infrastructure requires the creation of innovative alternatives. In particular, such alternatives must actively contribute to the reduction of carbon emissions via carbon recycling and a shift to the use of renewable sources of energy. Carbon neutral transformation of biomass to liquid fuels is one of such alternatives, but it is limited by the inherently low energy efficiency of photosynthesis with regard to the net production of biomass. Researchers have thus been looking for alternative, energy-efficient chemical routes inspired in the biological transformation of solar power, CO2 and H2O into useful chemicals; specifically, liquid fuels. Methanol has been the focus of a fair number of publications for its versatility as a fuel, and its use as an intermediate chemical in the synthesis of many compounds. In some of these studies, (e.g. Joo et al., (2004), Mignard and Pritchard (2006), Galindo and Badr (2007)) CO2 and renewable H2 (e.g. electrolytic H2) are considered as the raw materials for the production of methanol and other liquid fuels. Several basic PFD diagrams have been proposed. One of the most promising is the so called CAMERE process (Joo et al., 1999 ). In this process, carbon dioxide and renewable hydrogen are fed to a first reactor and transformed according to: H2 + CO2 <=> H2O + CO Reverse Water Gas Shift (RWGS) After eliminating the produced water the resulting H2/CO2/CO mixture is then feed to a second reactor where it is converted to methanol according to: CO2 + 3.H2 <=> CH3OH + H2O Methanol Synthesis (MS) CO + H2O <=> CO2 + H2 Water Gas Shift (WGS) The approach here is to produce enough CO to eliminate, via WGS, the water produced by MS. This is beneficial since water has been proven to block active sites in the MS catalyst. In this work a different process alternative is presented: One that combines the CO2 recycling of the CAMERE process and the use of solar energy implicit in some of the biomass-based process, but in this case with the potential high energy efficiency of thermo-chemical transformations.

08 HYDROGEN↗
NASA NTRS2021

One- and Two-Band Sensors and Algorithms to Derive aCDOM(440) from Global Above- and In-Water Optical Observations

The colored (or chromophoric, depending on the literature) dissolved organic matter (CDOM) spectral absorption coefficient, aCDOM(λ), is a variable of global interest that has broad application in the study of biogeochemical processes. Within the funding for scientific research, there is an overarching trend towards increasing the scale of observations both temporally and spatially, while simultaneously reducing the cost per sample, driving a systemic shift towards autonomous sensors and observations. Legacy aCDOM(λ) measurement techniques can be cost-prohibitive and do not lend themselves toward autonomous systems. Spectrally rich datasets carefully collected with advanced optical systems in diverse locations that span a global range of water bodies, in conjunction with appropriate quality assurance and processing, allow for the analysis of methods and algorithms to estimate aCDOM(440) from spectrally constrained one- and two-band subsets of the data. The resulting algorithms were evaluated with respect to established fit-for-purpose criteria as well as quality assured archival data. Existing and proposed optical sensors capable of exploiting the algorithms and intended for autonomous platforms are identified and discussed. One-band in-water algorithms and two-band above-water algorithms showed the most promise for practical use (accuracy of 3.0% and 6.5%, respectively), with the latter demonstrated for an airborne dataset.

ocean color↗
DOE OSTI2016

Mercury Speciation in Savannah River Site High-Level Waste: Determination and Implications for Waste Handling and Disposal - 16178

As part of a larger program to address mercury issues at the Savannah River Site, a number of samples from across the salt processing flowsheet have been collected and analyzed for several mercury species. The results indicate the presence of organomercury species, predominately methylmercury cation. This result was not expected, and it represents a significant paradigm shift in the understanding of mercury chemistry in high-level tank waste. Concentrations of total and soluble mercury have been measured as high as 0.5 g/L with methylmercury concentrations of at least fifty percent of that value. The distribution of mercury species being observed have ramifications to waste processing strategies. In particular, the mercury behavior across the cesium solvent extraction process has been examined. Leachates, from toxicity testing of the cementitious waste form used for decontaminated salt waste at Savannah River, have been tested and shows methylmercury as the dominant extractable species. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

Cloud Motion in the GOCI COMS Ocean Colour Data

The Geostationary Ocean Colour Imager (GOCI) instrument, on Koreas Communications, Oceans, and Meteorological Satellite (COMS), can produce a spectral artefact arising from the motion of clouds the cloud is spatially shifted and the amount of shift varies by spectral band. The length of time it takes to acquire all eight GOCI bands for a given slot (portion of a scene) is sucient to require that cloud motion be taken into account to fully mask or correct the eects of clouds in all bands. Inter-band correlations can be used to measure the amount of cloud shift, which can then be used to adjust the cloud mask so that the union of all shifted masks can act as a mask for all bands. This approach reduces the amount of masking required versus a simple expansion of the mask in all directions away from clouds. Cloud motion can also aect regions with unidentied clouds thin or fractional clouds that evade the cloud identication process yielding degraded quality in retrieved ocean colour parameters. Areas with moving and unidentied clouds require more elaborate masking algo-rithms to remove these degraded retrievals. Correction for the eects of moving fractional clouds may also be possible. The cloud shift information can be used to determine cloud motion and thus wind at the cloud levels on sub-minute timescales. The benecial and negative eects of moving clouds should be con-sidered for any ocean colour instrument design and associated data processing plans.

Robinson, Wayne D.↗
NASA NTRS2014

A Task Analytic Process to Define Future Concepts in Aviation

A necessary step when developing next generation systems is to understand the tasks that operators will perform. One NextGen concept under evaluation termed Single Pilot Operations (SPO) is designed to improve the efficiency of airline operations. One SPO concept includes a Pilot on Board (PoB), a Ground Station Operator (GSO), and automation. A number of procedural changes are likely to result when such changes in roles and responsibilities are undertaken. Automation is expected to relieve the PoB and GSO of some tasks (e.g. radio frequency changes, loading expected arrival information). A major difference in the SPO environment is the shift to communication-cued crosschecks (verbal / automated) rather than movement-cued crosschecks that occur in a shared cockpit. The current article highlights a task analytic process of the roles and responsibilities between a PoB, an approach-phase GSO, and automation.

single pilot operations↗
DOE OSTI2019

Analysis of the light shift in the hyper-Ramsey scheme of two-level atom interrogation in an optically dense medium

The properties of the Ramsey resonance and its sensitivity to the light shift of the atomic transition frequency are investigated in the case of the hyper-Ramsey interrogation in an optically dense medium of cold atoms. The shape of the interrogating pulses varies significantly due to the processes of absorption and dispersion in the atomic medium, which leads to a distortion of the Ramsey resonance and a periodic change in the central minimum to the maximum and vice versa. The dependence of the position of the central resonance on the light shift of the atomic transition is found with the attenuation of radiation in the medium taken into account. It is shown that in a certain section of the medium this dependence becomes N-shaped. (paper)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2025

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗
DOE OSTI2026

Technology Maturation Plan for Catalytic Membrane Reactors Based on Carbon Molecular Sieve Hollow Fiber Membranes for Sustainable and Modular H 2 Production

The overarching objective of the proposed project was to demonstrate a process-intensified approach to economically viable, modular H 2 production from waste biomass using catalytic membrane reactors (CMRs) based on carbon molecular sieve (CMS) hollow-fiber membranes. Specifically, the CMRs were developed to selectively remove H 2 during the high-temperature water-gas shift (WGS) reaction to circumvent thermodynamic limitations on converting CO to CO 2 and H 2 . To this end, our core technical activities were to (1) develop high-performance CMRs based on thermally stable, processible polymer-derived CMS membranes and (2) design and prepare new multicomponent CO 2 -tolerant nano-catalysts using a unique flame-based aerosol process for WGS reaction.

08 HYDROGEN↗
DOE OSTI2018

Impact of magnetic islands in the plasma edge on particle fueling and exhaust in the HSX and W7-X stellarators

The edge magnetic structure in the Helically Symmetric eXperiment (HSX) and Wendelstein 7X (W7-X) stellarators has been shown to have a significant impact on the particle fueling and exhaust of the plasma main species (hydrogen) as well as impurity helium. For HSX, the plasma sourcing to exhaust ratio, quantified by the effective and global particle confinement times τ p * and τ p , H , respectively, increases when a magnetic island chain is located in the plasma edge. The fueling efficiency is reduced by 25% when the plasma boundary is deformed by the magnetic islands. The X-point geometry also yields higher plasma temperatures in front of the main recycling region. When the island is moved radially inward, both τ p * and τ p decrease by 10 % – 25 % depending on plasma density. The τ p , H results rely heavily on EMC3-EIRENE modeling which confirms reduced fueling efficiency due to more rapid ionization in the outward shifted island position. These findings suggest that for a helically optimized system like HSX, the plasma fueling from the recycling source, as well as from active gas injection, can be controlled by the magnetic island chain in the plasma edge—which is a basic requirement for a divertor system. This process is also effective for the control of effective helium exhaust times, as τ p , H e * measured by perturbative gas puff experiments is reduced by up to 40% when the islands are shifted inwards. For Wendelstein 7-X, a similar reduction of τ p , H e * was inferred when magnetic islands were moved from the far plasma edge into the confined plasma region. Finally, however, the effective confinement features of H as the main plasma species were not affected due to the non-optimal position of the magnetic islands with respect to the highly localized ionization domain during the limiter startup campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Hydra: computer vision for data quality monitoring

Hydra, initially developed for Hall-D in 2019, is a system that utilizes computer vision to perform near real time data quality monitoring. Since then, it has been deployed across all experimental halls at Jefferson Lab, with the CLAS12 collaboration in Hall-B being the first outside of GlueX to fully utilize Hydra. The system comprises back end processes that manage the models, their inferences, and the data flow. Finally, the front-end components, accessible via web pages, allow detector experts and shift crews to view and interact with the system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Singular value decomposition utilizing parallel algorithms on graphical processors

One of the current challenges in underwater acoustic array signal processing is the detection of quiet targets in the presence of noise. In order to enable robust detection, one of the key processing steps requires data and replica whitening. This, in turn, involves the eigen-decomposition of the sample spectral matrix, Cx = 1/K xKX(k)XH(k) where X(k) denotes a single frequency snapshot with an element for each element of the array. By employing the singular value decomposition (SVD) method, the eigenvectors and eigenvalues can be determined directly from the data without computing the sample covariance matrix, reducing the computational requirements for a given level of accuracy (van Trees, Optimum Array Processing). (Recall that the SVD of a complex matrix A involves determining V, , and U such that A = U VH where U and V are orthonormal and is a positive, real, diagonal matrix containing the singular values of A. U and V are the eigenvectors of AAH and AHA, respectively, while the singular values are the square roots of the eigenvalues of AAH.) Because it is desirable to be able to compute these quantities in real time, an efficient technique for computing the SVD is vital. In addition, emerging multicore processors like graphical processing units (GPUs) are bringing parallel processing capabilities to an ever increasing number of users. Since the computational tasks involved in array signal processing are well suited for parallelization, it is expected that these computations will be implemented using GPUs as soon as users have the necessary computational tools available to them. Thus, it is important to have an SVD algorithm that is suitable for these processors. This work explores the effectiveness of two different parallel SVD implementations on an NVIDIA Tesla C2050 GPU (14 multiprocessors, 32 cores per multiprocessor, 1.15 GHz clock - peed). The first algorithm is based on a two-step algorithm which bidiagonalizes the matrix using Householder transformations, and then diagonalizes the intermediate bidiagonal matrix through implicit QR shifts. This is similar to that implemented for real matrices by Lahabar and Narayanan ("Singular Value Decomposition on GPU using CUDA", IEEE International Parallel Distributed Processing Symposium 2009). The implementation is done in a hybrid manner, with the bidiagonalization stage done using the GPU while the diagonalization stage is done using the CPU, with the GPU used to update the U and V matrices. The second algorithm is based on a one-sided Jacobi scheme utilizing a sequence of pair-wise column orthogonalizations such that A is replaced by AV until the resulting matrix is sufficiently orthogonal (that is, equal to U ). V is obtained from the sequence of orthogonalizations, while can be found from the square root of the diagonal elements of AH A and, once is known, U can be found from column scaling the resulting matrix. These implementations utilize CUDA Fortran and NVIDIA's CUB LAS library. The primary goal of this study is to quantify the comparative performance of these two techniques against themselves and other standard implementations (for example, MATLAB). Considering that there is significant overhead associated with transferring data to the GPU and with synchronization between the GPU and the host CPU, it is also important to understand when it is worthwhile to use the GPU in terms of the matrix size and number of concurrent SVDs to be calculated.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗