Search NASA⌕ Search

SEARCH · Search NASA

Results for “transport modes”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Analysis of gas storage and transport in Eagle Ford shale using pressure pulse decay measurements with He, Kr and CO 2

Detailed characterization of gas transport and storage in low-permeability and organic-rich shales is associated with an array of challenges due to the complex morphology of the pore space, representing a broad range of pore sizes, combined with the heterogeneous fabric of the shale matrix. These factors, and their interplay during gas transport and sorption, complicate a) the analysis of shale samples at the laboratory scale (~ up to a ft. In length), and b) the prediction of natural gas production and carbon sequestration potential at larger scales. Here, in this work, tandem experiments with inert (helium – He) and adsorbing (krypton - Kr and carbon dioxide - CO 2 ) gases were performed and analyzed to develop an efficient workflow for characterizing and modeling transport and sorption at the laboratory scale. In particular, pressure pulse-decay (PPD) measurements were conducted on an Eagle Ford shale core sample at room temperature using He, Kr, and CO 2 . PPD measurements with He (a non-sorbing gas) were employed to probe the overall porosity, including natural fractures, microcracks, mesopores, and micropores. A triple-porosity model (TPM) was adopted to interpret the gas transport in the shale sample: The pore space is represented by three interacting continua, including macropores (larger fractures), mesopores (including microcracks), and micropores. To facilitate the application of the TPM, a modified analytical approach is introduced to extract effective transport parameters (in terms of the characteristic time for transport at relevant porosity levels) directly from the PPD measurements with He. To validate the modeling approach, model parameters extracted from two He PPD measurements are demonstrated to provide excellent agreement with a 3rd He PPD measurement performed at a higher pressure. The effective transport parameters, extracted from the He experiments, were subsequently converted for application to the Kr and CO 2 PPD experiments, by accounting for relevant transport modes and differences in fluid properties. Excess adsorption isotherms were extracted from the equilibrium pressures of the Kr and CO 2 PPD experiments using the He pore volume as a baseline. These adsorption isotherms were then integrated into the TPM to predict combined gas transport and sorption for Kr and CO 2 , with transport coefficients translated from the He measurements. The predictions for Kr and CO 2 are demonstrated to be in excellent agreement with the experimental observations. This, in turn, demonstrates that the proposed analytical approach provides for an effective characterization of mass transfer rates in shales, that can be applied directly in a TPM representation of mass transfer and sorption.

58 GEOSCIENCES↗
DOE OSTI2025

Statistical distributions for transient transport

Here, this paper introduces the use of statistical distributions based on transport differential equations for clear distinction of transport modes within transient kinetic experiments. More specifically, novel techniques are developed for the transient data obtained through the Temporal Analysis of Products (TAP) reactor and are applicable to experiments where pulse response into a gas flow is used. The methodology allows distinguishing between two domains of diffusion transport in heterogeneous catalytic systems, i.e., Knudsen and non-Knudsen diffusion, using statistical fingerprints, and finding the transition domain. Two distribution parameters were obtained that directly result in coefficients that correspond to the concentration and the rate of transport. Using a linear relationship between the rate and concentration coefficients, Knudsen diffusion is revealed when the rate of transport is constant and non-Knudsen diffusion is confirmed when the rate of transport coefficient is a function of the concentration coefficient. As a result, accurate transport information can be extracted from experimental data even in the presence of comprising instrument drift or noise particularly when analyzing higher pressure pulse responses with complex transport. This enables more direct investigation of experiments influenced by gas-phase reactions.

TAP reactor↗
DOE OSTI2020

A Self‐Consistent Model for Sorption and Transport in Polyimide‐Derived Carbon Molecular Sieve Gas Separation Membranes

Abstract Demand for energy‐efficient gas separations exists across many industrial processes, and membranes can aid in meeting this demand. Carbon molecular sieve (CMS) membranes show exceptional separation performance and scalable processing attributes attractive for important, similar‐sized gas pairs. Herein, we outline a mathematical and physical framework to understand these attributes. This framework shares features with dual‐mode transport theory for glassy polymers; however, physical connections to CMS model parameters differ from glassy polymer cases. We present evidence in CMS membranes for a large volume fraction of microporous domains characterized by Langmuir sorption in local equilibrium with a minority continuous phase described by Henry's law sorption. Using this framework, expressions are provided to relate measurable parameters for sorption and transport in CMS materials. We also outline a mechanism for formation of these environments and suggest future model refinements.

Sanyal, Oishi↗
DOE OSTI2025

Summary of Carbon Dioxide Pipeline Systems and Incident Data in North America

Pipelines are historically seen as the primary transportation mode for carbon dioxide (CO 2 ) streams in the context of carbon capture and storage (CCS) and oil and gas industries. Pipeline transmission of CO 2 over longer distances is regarded as most efficient and economical when the CO 2 is in the dense phase, i.e., in liquid or supercritical regime, due to transporting CO 2 in dense phase that allows for a smaller-diameter pipeline to move a given flow, which optimizes project cost.

42 ENGINEERING↗
DOE OSTI2022

System Analysis Modeling and Intermodal Transportation for Commercial Spent Nuclear Fuel

The United States Department of Energy (DOE) has long term goals to develop solutions for managing the nation’s spent nuclear fuel (SNF) and high-level waste (HLW) inventory. The Integrated Waste Management (IWM) program under the DOE office of Nuclear Energy (DOE-NE) is employing system-level engineering and analysis principles to inform potential future waste management system architectures. Managing the spent nuclear waste requires the use of system-level analysis software that takes various aspects of the fuel cycle into account like waste generation, on-site/centralized storage, transportation infrastructure, and long-term disposal. The Next Generation System Analysis Model (NGSAM) is an agent-based model that was developed to simulate the transportation and storage of SNF and HLW. As an agent-based model, NGSAM has the capability to detail the interaction and movement of individual components and groups, such as rail cars and casks. The SNF inventory from commercial nuclear reactors is currently in temporary storage at multiple locations spread across the United States. Shipping of SNF from these locations relies on one of three transportation modes: rail, heavy-haul truck, or barge. Out of the three modes identified, rail is generally the most preferred due to the size of the canisters and casks the SNF would be shipped in. However, under some scenarios, a direct rail route might not be readily available to a reactor site or improving the rail infrastructure at shutdown sites might be too cost-prohibitive for utilities to opt for a direct rail transfer. Under such scenarios, using a barge or heavy haul truck to de-inventory the site and transfer the SNF to a nearby intermodal transfer site with adequate rail infrastructure where the payload could be transferred to a rail car might prove to be an attractive option. This work initially presents the various intermodal transportation options that could be used to transfer SNF from reactor sites to rail cars. This is followed by exploring the operational steps in each of these modes to move the SNF from a reactor site and transfer it to a rail car. This work also presents the procedure of implementing the intermodal transfer methodology in NGSAM using various Java methods. Finally, the process times for accomplishing each of the individual steps are furnished. The implementation ideology, assumptions, and future steps are presented in this work.

Gadey, Harish Reddy↗
DOE OSTI2024

Agent-based modeling for multimodal transportation of CO 2 for carbon capture, utilization, and storage: CCUS-agent

Here, to understand the system-level interactions between the entities in Carbon Capture, Utilization, and Storage (CCUS), an agent-based foundational modeling tool, CCUS-Agent, is developed for a large-scale study of transportation flows and infrastructure in the United States. Key features of the tool include (i) modular design, (ii) multiple transportation modes, (iii) capabilities for extension, and (iv) testing against various system components and networks of small and large sizes. Five matching algorithms for CO 2 supply agents (e.g., powerplants and industrial facilities) and demand agents (e.g., storage and utilization sites) are explored: Most Profitable First Year (MPFY), Most Profitable All Years (MPAY), Shortest Total Distance First Year (SDFY), Shortest Total Distance All Years (SDAY), and Shortest distance to long-haul transport All Years (ACAY). Before matching, the supply agent, demand agent, and route must be available, and the connection must be profitable. A profitable connection means the supply agent portion of revenue from the 45Q tax credit must cover the supply agent costs and all transportation costs, while the demand agent revenue portion must cover all demand agent costs. A case study employing over 5500 supply and demand agents and multimodal CCUS transportation infrastructure in the contiguous United States is conducted. The results suggest that it is possible to capture over 9 billion tonnes (GT) of CO 2 from 2025 to 2043, which will increase significantly to 22 GT if the capture costs are reduced by 40 %. The MPFY and SDFY algorithms capture more CO 2 earlier in the time horizon, while the MPAY and SDAY algorithms capture more later in the time horizon.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Preliminary Evaluation of Removing SNF from Nuclear Power Plant Sites - Pilgrim Site Visit - 20048

The U.S. Department of Energy Office of Integrated Waste Management (DOE-IWM)a conducted an evaluation of removing spent nuclear fuel (SNF) from the Pilgrim site on November 4-8, 2019. The Pilgrim site is located on the western shore of Cape Cod Bay in the Town of Plymouth, Massachusetts, about 61 km southeast of Boston and 71 km east of Providence, Rhode Island. Participants in the site visit included the U.S. Department of Energy, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, the state of Massachusetts, the Federal Railroad Administration, the U.S. Coast Guard, the U.S. Army Corps of Engineers, the Mashpee Wampanoag Tribe, the Consolidated Group of Tribes and Organizations, the Council of State Governments-Eastern Regional Conference, the Pilgrim Nuclear Decommissioning Citizens Advisory Panel, and the Massachusetts Coastal Railroad. The Pilgrim site was found to have two transportation mode options for the removal of SNF, offsite rail access and onsite barge access. Two offsite heavy haul truck to rail transload locations were evaluated, one in Middleborough, Massachusetts, about 35-47 km from the Pilgrim site, and a second location in Middleborough about 36-43 km from the Pilgrim site. A passenger railroad terminates in Plymouth, Massachusetts, about 11 km from the Pilgrim site; however, this location is not suitable for freight rail involving large SNF transportation casks. There is also an onsite barge facility located on the Pilgrim site that was used during construction and would require refurbishment to be used. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Next Generation System Analysis Model: Recently Added Features and Future Plans

To better enable informed decision-making regarding the back-end of the nuclear fuel cycle, the Integrated Waste Management System (IWMS) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste (HLW).With these tools, IWMS architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool expressly designed to be capable of modeling features within various IWMS architectures. NGSAM imports data from Oak Ridge National Laboratory (ORNL)’s unified database (e.g., historic assembly information, thermal profiles for assembly heat, and at-reactor dry storage loadings) to ensure that each simulation initializes with a realistic representation of the state of commercial SNF in the U.S. Recent major enhancements implemented into NGSAM in the period since NGSAM was last presented at the WM2019 conference include: • Tracking of railroad escort car acquisition and buffer car acquisition • The addition of heavy haul truck (HHT) and barge routes for some sites, as well as support for user-defined inter-modal routes • Updates to the logic that checks the transportation cask thermal limit maps prior to package transport • An allocation method that predicts when reactor sites would pack assemblies from their spent fuel pools for dry storage, and prioritizes shipments directly from the pools of those reactor sites in the preceding periods (before the predicted loadings to dry storage), thus reducing the number of casks loaded into dry storage at reactor sites • The addition of “reactor site family” operational limits to restrict the number of loads of SNF taken from the pool and from dry storage at a given reactor site each year • Added support for multiple canister loading map options and packages with multiple compatible transportation overpacks • Updates to the handling of non-commercial SNF, including a new database that contains data to support the updates • Updates to allow analysis of hypothetical scenarios which include repackaging at reactor sites, e.g., for possible comparative analysis with other scenarios • Implementation of additional output reports, or modification of existing ones • The ability to generate and implement user edits via the NGSAM website • The ability to model loading SNF from pool storage at an interim storage facility (ISF) into dry storage at the ISF • The ability to model consolidating SNF from different existing storage containers at a DOE site into the same DOE standard canister • The ability to model transferring SNF casks from one transportation mode to another, e.g., from HHT to rail, referred to as transloading. These new features have improved NGSAM capabilities and users’ experience with the model. Preliminary NGSAM requirements for modeling advanced reactor fuels, reprocessing, treatment, and conditioning were considered, and this paper describes them at a high level. Other nuclear fuel cycle system analysis tools developed under sponsorship of DOE-NE, like the VISION code developed at Idaho National Laboratory, might be better suited for initial high-level analysis of those technologies and advanced fuel cycles. As technologies are developed and system concepts evolve, NGSAM could provide value by providing more detailed modeling of transport, storage, and disposal of spent fuel and wastes from advanced reactors and advanced fuel cycles at the fuel element and waste container level.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Potential-induced wetting and dewetting in pH-responsive block copolymer membranes for mass transport control

Wetting and dewetting behavior in channel-confined hydrophobic volumes is used in biological membranes to effect selective ion/molecular transport. Artificial biomimetic hydrophobic nanopores have been devised utilizing wetting and dewetting, however, tunable mass transport control utilizing multiple transport modes is required for applications such as controllable release/transport, water separation/purification and energy conversion. Here, we investigate the potential-induced wetting and dewetting behavior in a pH-responsive membrane composed of a polystyrene-b-poly(4-vinylpyridine) (PS-b-P4VP) block copolymer (BCP) when fabricated as a hierarchically-organized sandwich structure on a nanopore electrode array (NEA), i.e. BCP@NEA. At pH < pK a (P4VP) (pK a ~ 4.8), the BCP acts as an anion-exchange membrane due to the hydrophilic, protonated P4VP cylindrical nanodomains, but at pH > pK a (P4VP), the P4VP domains exhibit charge-neutral, hydrophobic and collapsed structures, blocking mass transport via the hydrophobic membrane. However, when originally prepared in a dewetted condition, mass transport in the BCP membrane may be switched on if sufficiently negative potentials are applied to the BCP@NEA architecture. When the hydrophobic BCP membrane is introduced on top of 2-electrode-embedded nanopore arrays, electrolyte solution in the nanopores is introduced, then isolated, by exploiting the potential-induced wetting and dewetting transitions in the BCP membrane. The potential-induced wetting/dewetting transition and the effect on cyclic voltammetry in the BCP@NEA structures is characterized as a function of the potential, pH and ionic strength. Additionally chronoamperometry and redox cycling experiments are used to further characterize the potential response. The multi-modal mass transport system proposed in this work will be useful for ultrasensitive sensing and single-molecule studies, which require long-time monitoring to explore reaction dynamics as well as molecular heterogeneity in nanoconfined volumes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comparative analysis of energy deposition modes available in Serpent 2 within the framework of the supercritical water reactor - Fuel qualification test reactor physics benchmark

A joint European Canadian Chinese development of a supercritical water-cooled small modular reactor (SCW-SMR) technology is in progress since September 2020 in the framework of a Horizon 2020 project called ECC-SMART. As a main purpose of the project, proper estimates of energy deposition and its spatial distribution are prerequisites for the accurate analysis of safety related parameters of the SCW-SMR concept under development. A supercritical water reactor fuel computational benchmark model, provided by Canadian Nuclear Laboratories, was applied for detailed comparison of different energy deposition calculation options available in the Serpent 2 Monte Carlo code. The effect of energy deposition options on the normalization of the results as well as on the spatial distribution of the energy deposition are discussed. Consistent energy deposition calculation methods are presented between three Monte Carlo codes, viz., Serpent 2, MCNP6 and OpenMC. Although resource-intensive, the use of the coupled neutron-photon transport mode of Serpent 2 is recommended for accurate spatial and quantitative characterization of energy deposition in the SCW-SMR fuel assemblies, accounting for both neutron and photon heating of all the materials. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

The Role of Mobility Data Hubs in an Integrated Decarbonized Transportation Future

The landscape for connected mobility ecosystems is evolving rapidly as information and communication technologies lower the cost and complexity of connecting people to places, integrating transportation modes and collecting data regarding such movements. These developments have been key to unlocking new business opportunities, particularly through mobility services. While the mechanisms for data collection, processing, and transfer have made significant advances in the past decade, the broader landscape of mobility data architectures and data users remains largely unresolved. It is unclear as to whether the result will converge towards a framework that resembles a coherent quilt or a disjointed patchwork of competing visions. Initial approaches to mobility data collection and provisioning have been largely siloed - by mode or software - or held for exclusive use, however several key players are quickly realizing the need and opportunities enabled through integrated mobility data eco-systems, or mobility data hubs as referred to in this paper. As the business case for hosting mobility data hubs evolves, there is great uncertainty regarding their impact to either advance or exacerbate sustainable mobility (e.g., seamless connectivity across modes, decreased energy consumption and greenhouse gas emissions, etc.). Groups such as the United Nations and World Bank have identified data platforms as a key enabler of realizing environmental and social benefits. If designed with decarbonization in mind, we hypothesize that enhanced observability provided by these ever-expanding mobility data hubs can facilitate energy and emissions reductions that are otherwise limited by transactional barriers and knowledge asymmetry that is inherent to a more siloed approach. In this sense, integration of mobility data can help to create a competitive playing field where value is not determined by exclusivity of data, but rather the quality and uniqueness of a given service. The goals of this paper are to 1) identify key players and data architectures that are emerging in a service-based mobility market, 2) explore several use cases where mobility data hubs have enabled greater sustainability outcomes, and 3) discuss key issues that will need to be resolved to fully leverage emerging mobility data hubs towards a sustainable transportation future.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2025

Bifurcation from L-mode to internal transport barrier triggered by a magnetic island in tokamak plasmas

Magnetic islands are believed to be responsible for triggering the internal transport barrier (ITB) around the rational surface and hence improves confinement in magnetic confinement fusion plasma, for more than two decades. Although some recent theoretical or modelling works support this hypothesis, the direct experimental demonstration on the ITB triggered by a magnetic island is still missing. Here, we report the first experimental observation that the increase in the magnetic island width triggers the bifurcation of the plasma transport state from a low confinement mode (L-mode) to an ITB mode in tokamak plasma. At medium island widths, the bifurcation appears with a dithering phase, i.e. plasma transitions from L-mode to ITB or vice versa quasi-periodically. As the island width further increases, the dithering ITB transitions into a steady ITB. The electron temperature gradient inside the ITB increases with island width. The trigger of the ITB and further enhancement of the ITB performance are also demonstrated by locking the island via applying a resonant magnetic perturbation field. The reduction of density fluctuations in the ITB region is observed and indicates turbulence suppression during ITB formation. These findings offer new insights for understanding ITB formation and robust ITB control.

internal transport barrier↗
DOE OSTI2024

Learning From User Behavior: A Survey-Assist Algorithm for Longitudinal Mobility Data Collection

GPS-based travel surveys are widely used in mobility studies to gather crucial qualitative data, like purpose, transportation mode and replaced mode. However, survey response still poses a burden to users, especially in long-term mobility studies, leading to response fatigue. We explore a survey-assist strategy to ease this burden by a novel, user-level modeling approach that leverages past responses from each user to predict responses for new trips, without relying on external data sources like GIS data. We investigate three main algorithms for predicting responses: (i) clustering trips and extrapolating responses for similar trips, (ii) using random forest classification, and (iii) clustering that uses a hybrid algorithm to determine spatial structure, which is then fed as input to a classic random forest classifier. The clustering approach can flexibly predict responses for even complex qualitative survey questions; it achieved F-scores of 65%. The random forest pipeline uses architecture that restricts it to predicting three predetermined survey questions: trip purpose, mode, and replaced mode. However, it achieved F-scores of 78%. While the survey-assist approach has been implemented by several proprietary systems, to our knowledge, this is the first exploration in the academic literature. It follows that this is also the first rigorous evaluation of multiple algorithms that can implement the approach. The evaluation uses a large scale, publicly available, longitudinal dataset consisting of ~ 92k trips from 235 users over a period of roughly one and a half years. With this approach, travel surveys can be pre-filled with the predicted responses for each trip, thus streamlining the survey process for users. Combined with an active learning system that requests user input on low-confidence predictions, models can be updated and improved over time to better support the long-term collection of longitudinal qualitative data.

clustering↗
DOE OSTI2022

How to Get the Best Gas Separation Membranes from State-of-the-Art Glassy Polymers

Herein we focus on fundamental polymer science factors in membrane-based gas separation to open another chapter on this important topic. Realistically thinking about nano and angstrom scale matrix attributes that are translatable into higher performance thin glassy polymer asymmetric membrane layers in practical large-scale devices is crucial. Such thinking should be guided by expertise in both polymer and membrane communities to advance the state of the art. Polymer structures, membrane morphologies and effects of operating conditions are discussed here, using specific examples to illustrate key issues. Rubbery polymers are not the focus of this discussion, since they lack diffusive discrimination for size-similar penetrants, which glassy polymers provide and make them the focus here. Four scalable subtopics guide necessary thinking: (i) plasticization; (ii) anti-plasticization†2; (iii) dual-mode transport involving saturation of unrelaxed free volume, and (iv) non-uniform free volume and stress profiles in thin skin glassy polymer asymmetric or composite membranes. Furthermore, using these subtopics in the context of macromolecular science we discuss issues needed to expand the state-of-the-art in gas separation membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Nanopores with dynamic pore opening diameter

Solid state nanopores have emerged as model systems for understanding transport properties on the nanoscale. They serve as templates for both preparing mimics of biological channels and designing biological sensors. Unlike their biological inspirations, the majority of nanopores prepared thus far, however, have been structurally static devices such that the pore opening diameter is fixed. If we could prepare nanopores whose opening diameter fluctuated in time with controlled amplitude at known locations in the pore, we could create ionic memristors as well as achieve new transport modes. Here we present ∼10 nm diameter single nanopores drilled through a 10 nm thick gold layer positioned on top of a 30 nm thick silicon nitride film. Two types of devices were prepared; one containing single stranded DNA and the other containing hairpin DNA attached to the discrete layer of gold using thiol chemistry. When an external electric field was applied across a nanopore with single stranded DNA, the nanoconfined DNA molecules exhibited steric and electrical constraints that led to memristor-like behavior in the current–voltage curves. The degree of hysteresis was controlled by salt concentration, magnitude of voltage and pore diameter. In contrast, nanopores containing DNA hairpins conducted similar currents in forward and reverse bias in agreement with the rigidity of the hairpin molecule. The experiments are explained by Brownian dynamics simulations that reveal voltage and salt concentration induced changes in DNA extension. The degree of DNA extension was also found to be dependent on the location of the molecules along the pore axis. The nanopores presented here provide the first steps towards preparation of non-equilibrium nanopore systems.

Vlassiouk, Ivan [ORNL] (ORCID:0000000254940386)↗