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At least 433 records · Page 24

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DOE OSTI2022

Parametric Testing and Evaluation of a Novel Biphasic Absorption Process for Post-Combustion Carbon Capture

A novel biphasic CO2 absorption process (BiCAP) is being developed at the University of Illinois. BiCAP is enabled by using a new class of biphasic solvents developed based on multi-property criteria for postcombustion carbon capture. The process was previously demonstrated at the lab-scale, including in 10 kWe absorption and desorption column systems. In the current study, the process has been scaled up by building and testing a 40 kWe integrated capture skid at a power plant. Parametric tests for two biphasic solvents were conducted with the synthetic flue gas made of bottle CO2 gas and air to validate the performance and operational flexibility of the unit with respect to varying process or operating conditions. Operation of the phase separator, which is unique equipment to BiCAP, was verified to be stable and efficient. Two liquid phases could be separated via static settlement based on a density difference and >90% of the CO2 absorbed was concentrated in the separated CO2-rich phase. Results of parametric tests showed that the minimum heat duty appeared at the optimal stripping pressure. A higher stripping temperature was more favourable to improve overall energy performance. Introducing a secondary cold solvent feed stream to the top of the stripper via bypassing the cross heat exchanger helped reduce the heat loss carried with water vapour. Test results also revealed that the heat duty requirement was comparable when the CO2 concentration in flue gas decreased from ~11 to 4 vol.% as the phase separation decoupled the absorption and desorption steps in BiCAP. Under typical steady-state conditions, both biphasic solvents lowered the process heat duty by >40% compared with the reference 30 wt.% monoethanolamine solvent.

Absorption↗

DOE OSTI2026

ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation

A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which constitutes the core content of the metrics and diagnostics package in section 2, and a user's guide documenting the workflow/structure of the version 1.0 codes, and including step-by-step instruction for running the package in section 3.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Distributed Grid-Sensing Service Layer: A System Architecture Blueprint

In this report, a scalable, decentralized, sensor-oriented communication blueprint is introduced. The proposed architecture has been specifically designed to support the mass deployment of sensors and also enable data consumers to access the underlying data streams using a distributed systems approach. With the proposed approach, sensors and data clients can be decoupled from the physical communication infrastructure and migrated into a modern, software-defined infrastructure ecosystem that can be configured to suit the end application’s requirements. In its current iteration, this blueprint defines the interactions, processes, and expected outcomes that each individual component within the architecture must support the overall ecosystem’s needs. Within this work, such an assembly of services is called the data bus; it represents the heart of the distributed grid sensing services architecture, a multiyear project that aims to design, implement, and test a reference sensor-data dissemination network that can support the needs of the extended grid state. We expect this blueprint to guide our future implementation efforts

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Deep Reinforcement Learning for Automatic Generation Control of Wind Farms

This paper provides a model-free framework for real-time control of wind farms to accurately track a power reference signal. This problem requires tractable dynamical models for capturing the aerodynamic interaction between wind turbines and controllers that can make decisions in realtime given varying atmospheric conditions. In this paper, we propose a deep reinforcement learning framework to provide real-time yaw control of a wind farm. Modifications have been made to FLOw Redirection and Induction in Steady State (FLORIS), a modeling tool that incorporates transient wake behavior. The control problem is formulated to track a synthetic power reference signal based on historical atmospheric (wind speed and direction) information, price signals, and regulation deployment data from U.S. regional transmission operators. Results indicate that a wind farm, with this control paradigm, can achieve good tracking performance when tested with real atmospheric data.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Microgrids Toward 100% Renewable Penetration: Preprint

This paper investigates microgrid transient stability with mixed generation - synchronous generator (SG), grid-forming (GFM) and grid-following (GFL) inverters - under increasing penetration levels toward a 100% renewable generation microgrid. Specifically, the dynamics of a microgrid with an SG and GFL inverter(s), an SG with GFM inverter(s), and an SG with GFM and GFL inverters under each penetration are evaluated with an electromagnetic transient study with two critical dynamic events: unplanned islanding and switching in a pumped induction motor load. Analysis and simulation results indicate that the microgrid with GFL inverters running in parallel with the SG can provide a faster power response than the GFM inverters to compensate for the deviations of the frequency and voltage. The scenario with the mixed SG, GFM, and GFL inverter has the best transient and steady-state stability toward 100% inverter-based resource (IBR) penetration. This comprehensive study provides helpful references for microgrid engineers to understand the microgrid stability when facing various choice of installing IBRs (GFL, GFM, or mixed).

droop control↗

DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Microgrids Toward 100% Renewable Penetration

droop control↗

DOE OSTI2020

Evaluating long-term model-based scenarios of the energy system

Energy-economic models are used to provide science-based decision support in a variety of contexts. Analyses using these tools often involve defining a “reference” scenario, which serves as a counterfactual against which alternative scenarios are compared. Evaluating scenarios, including reference scenarios, is critical for establishing the credibility of the analyses these models support. We propose a framework for evaluating energy system scenarios which consists of three parts – a qualitative storyline, quantitative metrics, and evaluation criteria. We apply this framework to the reference scenario for GCAM-USA, a version of the global human-Earth system model GCAM (Global Change Assessment Model) with state-level detail in the United States, focusing on the evolution of the electric power sector. We develop new visual analytic tools to facilitate the evaluation of model outcomes in 51 sub-national regions, and demonstrate how scenario performance can be tracked and compared across four quantifications of the GCAM-USA reference scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Modeling Riverine Dissolved and Particulate Organic Carbon Fluxes from Two Small Watersheds in the Northeastern United States

The coupled carbon (C) cycle across terrestrial and aquatic environments at the watershed scale has been identified as an important, but poorly constrained component of the global carbon budget. Here, we extended Soil and Water Assessment Tool (SWAT) with coupled riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) modules (referred to as SWAT-C hereafter). Results show that SWAT-C reproduced daily POC and DOC fluxes well in two watersheds in the Northeastern United States. We found that SWAT-C tended to underestimate high flows and peak DOC and POC fluxes. Uncertainty analysis indicated flux uncertainties associated with POC and DOC simulation were larger than those for flow simulation. Sensitive parameters controlling POC and DOC biogeochemical processes were identified along with how these parameters influence mechanisms underlying C cycling. We anticipate that the tool developed and applied here will inform C related ecosystem services in watershed assessment and planning.

Dissolved organic carbon, Particulate organic carb↗

DOE OSTI2025

Rotated-Droop Control for Enhanced Stability and Power Decoupling in Microgrids With Complex Line Impedances

Classical droop control in microgrids predominantly assumes inductive line impedance, which simplifies implementation but causes power coupling and steady-state errors in systems with resistive and inductive lines. This paper proposes a rotated-droop control strategy for grid-forming inverters that reformulates the power equations by incorporating the magnitude and angle of the line impedance within a rotated reference frame. This method enhances the decoupling of active and reactive power dynamics without increasing complexity or requiring communication links. A small-signal state-space model was created to capture the dynamic behavior of the system under varying impedance parameters, preserving the original droop gains by rotating the power control structure. This allows eigenvalue-based stability analysis and enhances damping and transient performance. Simulation and experimental results validated the improved power-sharing performance, faster response, and robustness of the proposed method under different impedance conditions. This approach maintains the decentralized structure of the conventional droop control while enabling greater adaptability and scalability, making it suitable for modern inverter-based microgrids with dynamic topologies.

Campo-Ossa, Daniel Dario [Univ. of Puerto Rico, Ag↗

DOE OSTI2025

Plutonium Oxidation State Distribution under WIPP Relevant Conditions (Rev. 2)

The oxidation state of plutonium in the Waste Isolation Pilot Plant (WIPP) environment has been a topic of interest since the initial compliance certification application. Plutonium (Pu) was initially expected to be present primarily as Pu(IV), but since the presence of Pu(III) could not be ruled out, it was also included in performance assessment (PA) calculations. The redox of the other variant actinides, uranium (U) and neptunium (Np), are also coupled to the plutonium redox. This led to a position in performance assessment calculations that is commonly referred to as “50/50”. In which half of the PA realizations assume solubility is dominated by the low oxidation state [U(IV), Np(IV), Pu(III)] and the other half assume solubility is dominated by the higher oxidation state [U(VI), Np(V), Pu(IV)]. Recently, a joint group of WIPP project participants from Los Alamos National Laboratory (LANL), Sandia National Laboratories (SNL), and the Department of Energy’s Carlsbad Field Office (DOE-CBFO) agreed on a new path forward for the oxidation state model in PA which will decouple the redox active actinides and will instead consider their redox as a function of E h . This will take the current binary approach and turn it into a system with four possible redox states.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

51 V NMR evidence for interlayer-modulated charge order and a first-order low-temperature transition in CsV 3 ⁢Sb 5

Charge order in the kagome superconductor CsV 3 ⁢Sb 5 exhibits a complex three-dimensional organization and intermediate-temperature anomalies whose bulk character has remained unsettled. We use orientation-dependent 51 V NMR as a site-selective probe to determine the stacking of the charge density wave (CDW) state and its thermal evolution. Below 𝑇 CDW ≈ 94K, the field-linear splitting of the 51 V central transition together with the anisotropy of the Knight shift tensor identify an interlayer-modulated 3⁢𝑞 CDW whose local environments are consistent with a four-layer 2 × 2 × 4 stacking with mixed trihexagonal/Star-of-David distortions, in agreement with synchrotron x-ray determinations. For comparison, RbV 3 ⁢Sb 5 serves as a reference exhibiting a uniform trihexagonal 2 × 2 × 2 stacking, allowing us to isolate features unique to the 2 × 2 × 4 state in CsV 3 ⁢Sb 5 . With 𝐻 0 ∥ 𝑐, the 51 V quadrupolar satellites through the intermediate temperature scale near 𝑇 CO ≈ 65K reorganize into two well-resolved electric-field-gradient manifolds that coexist over a finite interval; their relative spectral weights interchange on cooling while the total integrated satellite intensity remains conserved and 𝜈 𝑄 within each manifold is nearly temperature independent. The coexistence without critical broadening, together with conserved intensity, provides bulk evidence consistent with a first-order charge-order transition near 𝑇 CO . Our measurements do not resolve whether this lower-temperature transition corresponds to a distinct in-plane order or a reorganization of the 3⁢𝑞 state; rather, they delimit this window and provide bulk, site-resolved constraints that connect prior reported anomalies to a thermodynamic first-order transition.

Wang, Xiaoling [California State Univ., East Bay, ↗

DOE OSTI2025

Generation of a fluorescent short-lifetime oxygen nanosensor by coupling of an exciplex forming dye pair

Typical oxygen-sensitive dyes have lifetimes in the μs-ms regime for sensitive oxygen detection based on molecular quenching. Due to the long triplet-state lifetimes and poor quenching efficiency of these probes, it has been difficult to develop short lifetime probes. We have developed oxygen sensors using a short-lifetime dye (∼30–60 ns) that forms an anthracene-aniline exciplex, which is quenched by molecular oxygen through an excited-state charge transfer mechanism. To achieve measurements in aqueous systems, we have tethered the dyes together via a C3 alkyl linker to facilitate greater exciplex formation at low dye concentration (20 μg mL −1 ) and encapsulated the resulting compound into polymeric nanoparticles to form an aqueous-dispersible short-lifetime oxygen nanosensor. The sensors emit at 420 nm (unfolded dye) and 500 nm (exciplex), and the ratiometric Stern-Volmer Constant is 1.52 ± 0.02 L mol −1 , showing good sensitivity from 0 % to 40 % dissolved oxygen without the tradeoff of a long lifetime needed for direct molecular quenching. In this paper, we characterize this sensor for both lifetime-based measurements using time-correlated single-photon counting and ratiometric intensity-based measurements using the unfolded dye emission as an internal reference peak.

Biological and medical sciences↗

DOE OSTI2025

Taylor limit studies for local helicity injection plasma startup

Solenoid-free tokamak startup techniques can simplify the design and reduce the cost of tokamak-based fusion energy systems. The newly commissioned Pegasus-III spherical tokamak provides a dedicated platform for developing a scalable solenoid-free startup approach. Local helicity injection (LHI) is one promising technique being developed on Pegasus-III, which uses compact edge current sources to drive open field line current I inj that is redistributed via helicity-conserving instabilities to initiate tokamak plasmas. These instabilities relax the system toward a minimum energy state described by Taylor relaxation theory. This relaxation process imposes a global current limit for LHI plasmas, referred to as the Taylor limit I TL ⁠, which can dictate the plasma current I p evolution. Experiments on Pegasus and Pegasus-III show that increasing this limit leads to more effective utilization of the available helicity input and higher I p plasmas. Initial Pegasus-III experiments have verified the expected I TL $\varpropto$ ( I inj B T ) 1/2 scaling holds for B T and I inj up to 0.3 T on axis and 12 kA ⁠, respectively. Additionally, data from different injector arrays show that the width of the injector aperture directly alters I TL and can be leveraged for future injector design optimization. Throughout these scaling studies, discharges were overdriven at I p = I TL by providing excess helicity input. Intermittent bursts of n = 1 magnetic activity consistent with large-scale reconnection events occurred more often as the system was increasingly overdriven leading to a flattening of the λ = μ 0 J ∥ / |B| profile, where J ∥ is the parallel current density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Exploring non-adiabaticity to CO reduction reaction through ab initio molecular dynamics simulation

Non-adiabatic chemical reaction refers to the electronic excitation during reactions. This effect cannot be modeled by the ground-state Born-Oppenheimer molecular dynamics (BO-MD), where the electronic structure is at the ground state for every step of ions' movement. Although the non-adiabatic effect has been explored extensively in gas phase reactions, its role in electrochemical reactions, such as water splitting and CO 2 reduction, in electrolyte has been rarely explored. On the other hand, electrochemical reactions usually involve electron transport; thus, a non-adiabatic process can naturally play a significant role. In this work, using one-step CO 2 reduction as an example, we investigated the role of the non-adiabatic effect in the reaction. The reaction barriers were computed by adiabatic BO-MD and non-adiabatic real-time time dependent density functional theory (rt-TDDFT). We found that by including the non-adiabatic effect, rt-TDDFT could increase the reaction barrier up to 6% compared to the BO-MD calculated barrier when the solvent model is used to represent water. Simulations were carried out using explicit water molecules around the reaction site under different overpotentials, and similar non-adiabatic effects were found.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Correlating AGP on a quantum computer

For variational algorithms on the near term quantum computing hardware, it is highly desirable to use very accurate ansatze with low implementation cost. Recent studies have shown that the antisymmetrized geminal power (AGP) wavefunction can be an excellent starting point for ansatze describing systems with strong pairing correlations, as those occurring in superconductors. In this work, we show how AGP can be efficiently implemented on a quantum computer with circuit depth, number of CNOTs, and number of measurements being linear in system size. Using AGP as the initial reference, we propose and implement a unitary correlator on AGP and benchmark it on the ground state of the pairing Hamiltonian. Furthermore, the results show highly accurate ground state energies in all correlation regimes of this model Hamiltonian.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Colloquium : Quantum anomalous Hall effect

The quantum Hall (QH) effect, quantized Hall resistance combined with zero longitudinal resistance, is the characteristic experimental fingerprint of Chern insulators—topologically nontrivial states of two-dimensional matter with broken time-reversal symmetry. In Chern insulators, nontrivial bulk band topology is expressed by chiral states that carry current along sample edges without dissipation. Here, the quantum anomalous Hall (QAH) effect refers to QH effects that occur in the absence of external magnetic fields due to spontaneously broken time-reversal symmetry. The QAH effect has now been realized in four different classes of two-dimensional materials: (i) thin films of magnetically (Cr- and/or V-) doped topological insulators in the (Bi,Sb) 2 T 3 family, (ii) thin films of the intrinsic magnetic topological insulator MnBi 2 Te 4 , (iii) moiré materials formed from graphene, and (iv) moiré materials formed from transition-metal dichalcogenides. In this Colloquium, the physical mechanisms responsible for each class of QAH insulator are reviewed, with both differences and commonalities highlighted, and potential applications of the QAH effect are commented upon.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Active Reconditioning of Retired Lithium-ion Battery Packs from Electric Vehicles for Second Life Applications

Utilizing the remaining capacity in retired lithium-ion (Li-ion) batteries from electric vehicles (EVs) for second-life applications has shown economic and environmental benefits. However, achieving homogeneity among the capacities of cells before their second life is critical to exploit the benefits. This article proposes a new active reconditioning approach with the potential to make short-term reconditioning of batteries before second life feasible. A control objective map determines each cell's state-of-charge (SOC) operating window based on its capacity relative to other cells. The SOC reference translates into distinct differential currents through the cells, wherein the higher-capacity cells undergo more frequent and deep charge and discharge cycles than their lower-capacity counterparts. The proposed solution achieves capacity homogeneity within the battery pack with low reconditioning time and minimal fade in the overall pack capacity. The feasibility of the reconditioning approach under varying load and environmental conditions is assessed through simulations, encompassing factors such as the number of cycles per day, depth-of-discharge, battery pack temperature, and cell resting time at different SOCs. Furthermore, the simulation model employs a battery pack with sixteen series-connected 75 Ah Kokam lithium nickel manganese cobalt oxide (NMC) cells with a 3.6% initial capacity imbalance. A reconditioning time of 1.3 months is achieved with a final capacity imbalance of 0.1% and an overall capacity fade of 0.005%, thereby confirming the viability of the reconditioning process. Moreover, experimental validation using eight retired battery cells from a Nissan Leaf demonstrates a substantial decrease in the capacity imbalance of cells from 9.4% to 2.15% within 78 days, effectively affirming the efficacy of the proposed reconditioning scheme.

25 ENERGY STORAGE↗