Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “DER”

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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Enhancement of interlayer exchange in an ultrathin two-dimensional magnet

Following the recent isolation of monolayer CrI 3 , many more two-dimensional van der Waals magnetic materials have been isolated. Their incorporation in van der Waals heterostructures offers a new platform for spintronics, proximity magnetism and quantum spin liquids. A primary question in this field is how exfoliating crystals to the few-layer limit influences their magnetism. Studies of CrI 3 have shown a different magnetic ground state for ultrathin exfoliated films compared with the bulk, but the origin is not yet understood. Here, we use electron tunnelling through few-layer crystals of the layered antiferromagnetic insulator CrCl 3 to probe its magnetic order and find a tenfold enhancement of the interlayer exchange compared with bulk crystals. Moreover, temperature- and polarization-dependent Raman spectroscopy reveals that the crystallographic phase transition of bulk crystals does not occur in exfoliated films. This results in a different low-temperature stacking order and, we hypothesize, increased interlayer exchange. In conclusion, our study provides insight into the connection between stacking order and interlayer interactions in two-dimensional magnets, which may be relevant for correlating stacking faults and mechanical deformations with the magnetic ground states of other more exotic layered magnets such as RuCl 3 .

36 MATERIALS SCIENCE↗
DOE OSTI2020

Superconductivity and strong correlations in moiré flat bands

Strongly correlated systems can give rise to spectacular phenomenology, from high-temperature superconductivity to the emergence of states of matter characterized by long-range quantum entanglement. Low-density flat-band systems play a vital role because the energy range of the band is so narrow that the Coulomb interactions dominate over kinetic energy, putting these materials in the strongly-correlated regime. Experimentally, when a band is narrow in both energy and momentum, its filling may be tuned in situ across the whole range, from empty to full. Recently, one particular flat-band system—that of van der Waals heterostructures, such as twisted bilayer graphene—has exhibited strongly correlated states and superconductivity, but it is still not clear to what extent the two are linked. As a result, we review the status and prospects for flat-band engineering in van der Waals heterostructures and explore how both phenomena emerge from the moiré flat bands.

Balents, Leon↗
DOE OSTI2023

Bond-dependent anisotropy and magnon decay in cobalt-based Kitaev triangular antiferromagnet

Following tremendous success of the graphene-derived fundamental and applied research, the magnetic van der Waals materials that can be cleaved into monolayer two-dimensional atomic crystals have emerged as a new platform in the studies of low-dimensional physics and in the design of artificial heterostructures with novel properties. Because of that, the family of dihalides and trihalides of the 3d transition group receive a strong renewed interest. Together with our experimental collaborators, we have investigated the novel dynamical properties of one of such promising material CoI 2 , and demonstrated that spin excitations in it are prone to substantial breakdown and complex level repulsion, the important quantum effects whose theoretical understanding has been significantly advanced by our group in the last two decades. Both phenomena are dramatically revealed by experiments and verified by the theory in our joint study, published in Nature Physics. Altogether, our results pave the way toward a new research direction for the magnetic van der Waals materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Twisted-layer boron nitride ceramic with high deformability and strength

Moiré superlattices formed by twisted stacking in van der Waals materials have emerged as a new platform for exploring the physics of strongly correlated materials and other emergent phenomena. However, there remains a lack of research on the mechanical properties of twisted-layer van der Waals materials, owing to a lack of suitable strategies for making three-dimensional bulk materials. Here we report the successful synthesis of a polycrystalline boron nitride bulk ceramic with high room-temperature deformability and strength. This ceramic, synthesized from an onion-like boron nitride nanoprecursor with conventional spark plasma sintering and hot-pressing sintering, consists of interlocked laminated nanoplates in which parallel laminae are stacked with varying twist angles. The compressive strain of this bulk ceramic can reach 14% before fracture, about one order of magnitude higher compared with traditional ceramics (less than 1% in general), whereas the compressive strength is about six times that of ordinary hexagonal boron nitride layered ceramics. The exceptional mechanical properties are due to a combination of the elevated intrinsic deformability of the twisted layering in the nanoplates and the three-dimensional interlocked architecture that restricts deformation from propagating across individual nanoplates. The advent of this twisted-layer boron nitride bulk ceramic opens a gate to the fabrication of highly deformable bulk ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Online real-time learning of dynamical systems from noisy streaming data

Abstract Recent advancements in sensing and communication facilitate obtaining high-frequency real-time data from various physical systems like power networks, climate systems, biological networks, etc. However, since the data are recorded by physical sensors, it is natural that the obtained data is corrupted by measurement noise. In this paper, we present a novel algorithm for online real-time learning of dynamical systems from noisy time-series data, which employs the Robust Koopman operator framework to mitigate the effect of measurement noise. The proposed algorithm has three main advantages: (a) it allows for online real-time monitoring of a dynamical system; (b) it obtains a linear representation of the underlying dynamical system, thus enabling the user to use linear systems theory for analysis and control of the system; (c) it is computationally fast and less intensive than the popular extended dynamic mode decomposition (EDMD) algorithm. We illustrate the efficiency of the proposed algorithm by applying it to identify the Van der Pol oscillator, the chaotic attractor of the Henon map, the IEEE 68 bus system, and a ring network of Van der Pol oscillators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Semi-empirical model for Henry’s law constant of noble gases in molten salts

Henry’s law constant, which describes the proportionality of dissolved gas to partial pressure of free gas in liquid–gas equilibrium systems, can also be applied to mass transport applications. In this work, we investigated an approach for determining the solubility of noble gases in a molten salt liquid utilizing the equilibrium concept of Henry’s gas constant. Henry’s gas constant is described as a mathematical function dependent on the van der Waals radius of the noble gas and the temperature of the molten salt. The alteration in Gibbs free energy encompasses contributions from both surface and volume energies. Enthalpy and entropy are deduced from these surface and volume energies in the Gibbs free energy formulation. A comparative analysis was conducted between the conventional method and our proposed model. Moreover, useful chemical properties can be determined from examination of surface and volume energies. Our findings provide an accurate and general theory of Gibbs free energy that can be validated experimentally based on the model proposed herein. This work unifies the prediction of Henry gas constant and subsequently the entropy and enthalpy calculation for noble gases in a molten salt solution to a single functional form using van der Waals radius of the gas and temperature of the system. This functional form is then used to perform a multiple regression method to find two parameters corresponding to the surface energy and volume energy. These two parameters are consistent between all combinations of noble gas and molten salt.

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

Thickness-dependent spin bistable transitions in single-crystalline molecular 2D material

Abstract The advent of two-dimensional (2D) crystals has led to numerous scientific breakthroughs. Conventional 2D systems have in-plane covalent bonds and a weak out-of-plane van-der-Waals bond. Here we report a new type of 2D material composed of discrete magnetic molecules, where anisotropic van-der-Waals interactions bond the molecules into a 2D packing. Through mechanical exfoliation, we can obtain single-crystalline molecular monolayers, which can be readily integrated into other 2D systems. Optical spectroscopy suggests the few-layered molecules preserve the temperature-induced spin-crossover switching observed in the bulk form but show a drastic increase in thermal hysteresis unique to these thin 2D molecule assemblies. The trapping of spin bistability with decreasing layer number can arise from domain wall dynamics in reduced dimensions. Our results establish molecular solids with strong anisotropy of intermolecular interactions as precursors to a new class of 2D materials, affording possibilities to control molecular functionalities through substrate and interlayer interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Intercalated chalcogenides Fe 1/4 TaS 2 and Fe 1/3 TaS 2 under extreme pressure—temperature conditions

Intercalation is an important strategy for enhancing functionality in complex chalcogenides. This is because layered materials can be endowed with intriguing properties by filling the van der Waals gap with various ions and molecules, which, in addition to their unique chemistry, break symmetry in new ways. In order to explore the properties of intercalated metal dichalcogenides under extreme pressure-temperature conditions, we combine diamond anvil cell techniques, Raman scattering spectroscopy, magnetic susceptibility, and first-principles calculations to reveal the pressure–temperature phase diagram of Fe 1/3 TaS 2 . This system hosts a compression-driven structural phase transition to a polar state as well as remnant charge density wave signatures deriving from the host lamella of the 2H-parent compound. We also explore the role of different A-site patterns and determine that, by comparison, Fe 1/4 TaS 2 is soft and flexible due to the lower metal density inside the van der Waals gap. These findings open the door to entirely new states of matter with exciting property combinations, including metallicity, polarity, chirality, and altermagnetism – depending upon the conditions – that can support a wide range of spintronics and phononics applications.

Materials science↗
DOE OSTI2026

Solid-state thermometry via ionic–electronic coupling in two-dimensional heterostructures

The coupling of ionic and electronic transport in solid-state systems offers new opportunities for realizing compact, energy-efficient sensing technologies, yet practical implementations remain limited. In this article, we introduce a two-dimensional iontronic platform based on field-effect transistors that integrate monolayer MoS 2 channels with van der Waals bimetallic thiophosphates ( AB P 2 X 6 , A = Li, Cu, Ag and so on; B = In, Sc and so on; and X = S and Se) as ionic gate dielectrics to realize on-chip thermometry. Specifically, we exploit thermally activated ion migration within the gate dielectric leading to conductance modulation in the MoS 2 channel for temperature sensing. We achieve ~1–2 °C resolution, fast electronic readout and subpicojoule energy consumption in an ultracompact footprint (~1 µm 2 ). Beyond thermometry, these results establish bimetallic thiophosphates as a versatile platform for solid-state iontronics and broaden the functional design space of van der Waals heterostructures for sensing, actuation and adaptive electronics.

42 ENGINEERING↗
DOE OSTI2017

Hydrogen weakens interlayer bonding in layered transition metal sulfide Fe 1+x S

The presence of interlaminar interstitial defects like hydrogen affects the mechanical properties of van der Waals-bonded layered materials such as transition metal chalcogenides. While the embrittling effect of hydrogen is well understood in metals, the impact of hydrogen defects on the mechanical behavior of layered chalcogenides remained unexplored. In this article, we use density functional calculations to reveal the influence of different hydrogen point defects on important mechanical metrics, including binding energies, elastic moduli and tensile and shear strengths of a prototypical ionic layered material, mackinawite, Fe1+xS. We find that one of the low-energy hydrogen defect structures, interlaminar molecular H2 interstitials, severely degrades the strength of inter-layer van der Waals interactions in the mackinawite crystal. This leads to a significant (over 80%) degradation in the mechanical properties of the mackinawite crystal and enables facile interlayer sliding and exfoliation. This finding suggests the mechanisms for cathodic exfoliation of transition metal chalcogenides like Fe1+xS, and presents a plausible mechanism for the poor protectiveness of layered passive films like mackinawite that undergo failure by spalling or delamination.

Krishnamoorthy, Aravind↗
DOE OSTI2019

Molecular mechanism and binding free energy of doxorubicin intercalation in DNA

The intercalation process of binding doxorubicin (DOX) in DNA is studied by extensive MD simulations. Many molecular factors that control the binding affinity of DOX to DNA to form a stable complex are inspected and quantified by employing continuum solvation models for estimating the binding free energy. The modified MM-PB(GB)SA methodology provides a complete energetic profile of Δ G ele , Δ G vDW , Δ G polar , Δ G non-polar , T Δ S total , Δ G deform , Δ G con , and Δ G ion . To identify the sequence specificity of DOX, two different DNA sequences, d(CGATCG) or DNA1 and d(CGTACG) or DNA2, with one molecule (1 : 1 complex) or two molecule (2 : 1 complex) configurations of DOX were selected in this study. Our results show that the DNA deformation energy (Δ G deform ), the energy cost from translational and rotational entropic contributions ( T Δ S tran+rot ), the total electrostatic interactions (Δ G polar-PB/GB + Δ G ele ) of incorporation, the intramolecular electrostatic interactions (Δ G ele ) and electrostatic polar solvation interactions (Δ G polar-PB/GB ) are all unfavorable to the binding of DOX to DNA. However, they are overcome by at least five favorable interactions: the van der Waals interactions (Δ G vDW ), the non-polar solvation interaction (Δ G non-polar ), the vibrational entropic contribution ( T Δ S vib ), and the standard concentration dependent free energies of DOX (Δ G con ) and the ionic solution (Δ G ion ). Specifically, the van der Waals interaction appears to be the major driving force to form a stable DOX–DNA complex. We also predict that DOX has stronger binding to DNA1 than DNA2. The DNA deformation penalty and entropy cost in the 2 : 1 complex are less than those in the 1 : 1 complex, thus they indicate that the 2 : 1 complex is more stable than the 1 : 1 complex. Here, we have calculated the total binding free energy (BFE) (Δ G t-sim ) using both MM-PBSA and MM-GBSA methods, which suggests a more stable DOX–DNA complex at lower ionic concentration. The calculated BFE from the modified MM-GBSA method for DOX–DNA1 and DOX–DNA2 in the 1 : 1 complex is –9.1 and –5.1 kcal mol –1 respectively. The same quantities from the modified MM-PBSA method are –12.74 and –8.35 kcal mol –1 respectively. The value of the total BFE Δ G t-sim in the 1 : 1 complex is in reasonable agreement with the experimental value of –7.7 ± 0.3 kcal mol –1 .

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

Reversible assembly of silica nanoparticles at water–hydrocarbon interfaces controlled by SDS surfactant

Achieving reversible and tunable assembly of silica nanoparticles at liquid–liquid interfaces is vital for a wide range of scientific and technological applications including sustainable subsurface energy applications, catalysis, drug delivery and material synthesis. In this study, we report the mechanisms controlling the assembly of silica nanoparticles (dia. 50 nm and 100 nm) at water–heptane and water–toluene interfaces using sodium dodecyl sulfate (SDS) surfactant with concentrations ranging from 0.001–0.1 wt% using operando ultrasmall/small-angle X-ray scattering, cryogenic scanning electron microscopy imaging and classical molecular dynamics simulations. The results show that the assembly of silica nanoparticles at water–hydrocarbon interfaces can be tuned by controlling the concentrations of SDS. Silica nanoparticles are found to: (a) dominate the interfaces in the absence of interfacial SDS molecules, (b) coexist with SDS at the interfaces at low surfactant concentration of 0.001 wt% and (c) migrate toward the aqueous phase at a high SDS concentration of 0.1 wt%. Energetic analyses suggest that the van der Waals and electrostatic interactions between silica nanoparticles and SDS surfactants increase with SDS concentration. However, the favorable van der Waals and electrostatic interactions between the silica nanoparticles and toluene or heptane decrease with increasing SDS concentration. As a result, the silica nanoparticles migrate away from the water–hydrocarbon interface and towards bulk water at higher SDS concentrations. These calibrated investigations reveal the mechanistic basis for tuning silica nanoparticle assembly at complex interfaces.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Structures and localized vibrational states of defects in graphite by tight-binding calculations

The structural and vibrational properties of pristine graphite and point defects in graphite are studied by tight-binding (TB) calculations using a three-center TB potential model. We showed that the three-center TB potential without ‘‘ad hoc’’ van der Waals interaction corrections can accurately describe the inter-layer distance of graphite and the lowest-energy structures and stabilities of typical point defects in graphite. The results from our TB calculations are in good agreement with those from density-functional theory calculations with van der Waals interaction corrections. We also investigated the vibrational properties to gain better understanding on the localization of vibrational states induced by the point defects. Our calculation results show that although localized or quasi-localized vibrational modes can be found in all defected graphite, the localization induced by Frenkel pair, dual-vacancy, and dual-interstitial defects is much stronger. Atomic displacements associated with the localized vibrational modes induced by these three point defects are also analyzed

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

Consequences of the failure of equipartition for the p – V behavior of liquid water and the hydration free energy components of a small protein

Earlier we showed that in the molecular dynamics simulation of a rigid model of water it is necessary to use an integration time-step δ t ≤ 0.5 fs to ensure equipartition between translational and rotational modes. Here we extend that study in the NVT ensemble to NpT conditions and to an aqueous protein. We study neat liquid water with the rigid, SPC/E model and the protein BBA (PDB ID: 1FME) solvated in the rigid, TIP3P model. We examine integration time-steps ranging from 0.5 fs to 4.0 fs for various thermostat plus barostat combinations. We find that a small δ t is necessary to ensure consistent prediction of the simulation volume. Hydrogen mass repartitioning alleviates the problem somewhat, but is ineffective for the typical time-step used with this approach. The compressibility, a measure of volume fluctuations, and the dielectric constant, a measure of dipole moment fluctuations, are also seen to be sensitive to δ t . Using the mean volume estimated from the NpT simulation, we examine the electrostatic and van der Waals contribution to the hydration free energy of the protein in the NVT ensemble. These contributions are also sensitive to δ t . In going from δ t = 2 fs to δ t = 0.5 fs, the change in the net electrostatic plus van der Waals contribution to the hydration of BBA is already in excess of the folding free energy reported for this protein.

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

Active Learning of Microgrid Frequency Dynamics Using Neural Ordinary Differential Equations

Accurate frequency modelling of inverter‐based resource (IBR)‐dominated power systems is crucial for ensuring stable, reliable and resilient operations, particularly given their inherent low‐inertia characteristics and fast dynamics that traditional swing equation‐based models inadequately capture. This paper explores neural ordinary differential equations (Neural ODEs) as a computationally efficient, data‐driven framework for modelling power system frequency dynamics, specifically within microgrids integrating high penetrations of distributed energy resources (DERs). The developed neural ODEs framework incorporates a neural network architecture designed to capture input dynamics. By actively perturbing the system with a known signal, the Python‐based neural ODEs framework was trained using measured system states and inputs, without the need for detailed system information. The framework, tested on a model of the Cordova, AK, microgrid, achieved a goodness of fit ranging from 60% to 99% across different state variables and maintained a mean square error in the 10 -6 p.u. range under square and step excitation signals. The proposed approach demonstrated robustness to measurement noise and initial condition variations while maintaining low computational complexity suitable for real‐time power system control applications. Furthermore, transfer learning enabled the neural ODEs model to adapt to the following changes in system topology or generator dispatch, highlighting its effectiveness for dynamic microgrids with frequently evolving configurations and diverse DERs.

Aryal, Tara [South Dakota State Univ., Brookings, ↗
DOE OSTI2022

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗
DOE OSTI2019

Distributed energy management for community microgrids considering phase balancing and peak shaving

Here, a distributed energy management for community microgrids considering phase balancing and peak shaving is introduced. In each iteration, the house energy management system (HEMS) installed in each house minimises its electricity costs and the costs associated with the discomfort of customers due to deviations in indoor temperature from customers’ set points. At the community level, the microgrid central controller (MCC) schedules the distributed energy resources (DERs) and energy storage based on the received load profiles from customers and the forecast energy price at the point of common coupling. The MCC updates the energy price for each phase based on the amount of unbalanced power between generation and consumption. The updated energy price and unbalanced power for each phase are distributed to the HEMSs on corresponding phases. When the optimisation converges, the unbalanced power of each phase is close to zero. Meanwhile, the schedules of DERs, energy storage systems and the energy consumption of each house are determined by the MCC and HEMSs, separately. Specifically, the phase balancing and peak shaving are considered in the proposed distributed energy management model. The effectiveness of the proposed distributed energy management has been illustrated by case studies.

25 ENERGY STORAGE↗
DOE OSTI2021

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗