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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The hidden value of large-rotor, tall-tower wind turbines in the United States

The significant upscaling of wind turbine size (nameplate capacity, rotor diameter, and tower height) has, to date, been driven primarily by a goal of minimizing the levelized cost of energy. But with wind’s levelized cost of energy now comparable with that of other generating resources, other design considerations besides cost-minimization have grown in importance—particularly as wind’s increasing market penetration begins to impose challenges on the electric grid. We find that taller towers and larger rotors (relative to nameplate capacity) can enhance the value of wind energy to the electricity system and provide other “hidden” benefits. Specifically, in regions where wind penetration has reached around 20%, we find a boost in wholesale market value of US$2–US$3/MWh. This is augmented by transmission, balancing, and financing benefits that sum to roughly US$2/MWh. The aggregate potential value enhancement of US$4–US$5/MWh is comparable with a 10%–15% reduction in levelized costs.

17 WIND ENERGY↗
DOE OSTI2024

Mechanisms in the Synthesis of S -Alcohols with 1,4-NADH Biomimetic Co-factor N-Benzyl-1,4-dihydronicotinamide using Horse Liver Alcohol Dehydrogenase: A Hybrid Computational Study

The enantioselective reduction of prochiral ketones catalyzed by horse liver alcohol dehydrogenase (HLADH), was investigated via a hybrid computational approach, for molecular reactions involved in chiral synthesis of S-alcohols, when the natural co-factor, 1,4-dihyronicotinamide adenine dinucleotide, 1,4-NADH, was replaced with biomimetic co-factor, N-benzyl-1,4-dihydronicotinamide, 1. We surmised that different hydride and proton transfer mechanisms were involved using co-factor, 1. An alternative mechanism, where the hydride transfer step occurred, via an η 1 -keto-S-η 2 -5,6-1,4-dihydronicotinamide-Zn(II) complex, was previously investigated with a model of the HLADH-Zn(II) catalytic site (J. Organometal. Chem. 2021, 943, 121810). Presently, we studied canonical and alternative mechanisms compared to models of the entire enzyme structure. We disproved the η 2 -Zn(II) complex, and discovered a canonical hydride transfer from biomimetic 1,4-NADH, 1, to the Zn(II) bound prochiral ketone substrate, followed by a new proton relay, consisting of a water chain connecting His51 to Ser48 that accomplished the S-alkoxy anion's protonation to yield the final S-alcohol product. The HLADH catalysis, with biomimetic co-factor, 1, that replaced the ribose group, the 5'-diphosphate groups, and the adenine nucleotide with a N-benzyl group, has provided a new paradigm for the design of other structures of 1,4-NADH biomimetic co-factors, including their economic value in biocatalysis reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

RAIS ICRP 107 Dose Conversion Factors for Radionuclides

Radionuclide dose conversion factors, also known as dose coefficients, are used for radionuclide dose calculations. Routes included are oral, inhalation, and external exposure. Separate datasets are maintained for ICRP 107, 60, and 30. The dose conversion factors from the ICRP 107 (https://rais.ornl.gov/cgibin/tools/TOX_search?select=rad107) are updated values from FGR 13 supplement using ICRP 107 decay data. The derivation and values are in “Calculations of Slope Factors and Dose Coefficients” (ORNL, 2014).

Noto, Katie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2021

Magnetic Damping in Polycrystalline Thin-Film Fe-V Alloys

Here, we report on the magnetic damping properties of polycrystalline Fe-V alloy thin films that are deposited at room temperature. By varying the concentration of V in the alloy, the saturation magnetization can be adjusted from that of Fe to near zero.We show that exceptionally low values of the damping parameter can be maintained over the majority of this range, with a minimum damping at approximately 15%–20% V concentration. Such a minimum is qualitatively reproduced with ab initio calculations of the damping parameter, although at a concentration closer to 10% V. The measured intrinsic damping has a minimum value of (1.53±0.08)×10 –3 , which is approximately a factor of 3 higher than our calculated value of 0.48×10 –3 . From first-principles theory, we outline the factors that are mainly responsible for the trend of the damping parameter in these alloys. In particular, the band structure and resulting damping mechanism is shown to change at V concentrations greater than approximately 35% V content.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Computing rank‐revealing factorizations of matrices stored out‐of‐core

This paper describes efficient algorithms for computing rank-revealing factorizations of matrices that are too large to fit in main memory (RAM), and must instead be stored on slow external memory devices such as disks (out-of-core or out-of-memory). Traditional algorithms for computing rank-revealing factorizations (such as the column pivoted QR factorization and the singular value decomposition) are very communication intensive as they require many vector-vector and matrix-vector operations, which become prohibitively expensive when data is not in RAM. Randomization allows to reformulate new methods so that large contiguous blocks of the matrix are processed in bulk. The paper describes two distinct methods. The first is a blocked version of column pivoted Householder QR, organized as a “left-looking” method to minimize the number of the expensive write operations. The second method results employs a UTV factorization. It is organized as an algorithm-by-blocks to overlap computations and I/O operations. As it incorporates power iterations, it is much better at revealing the numerical rank. Numerical experiments on several computers demonstrate that the new algorithms are almost as fast when processing data stored on slow memory devices as traditional algorithms are for data stored in RAM.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Can a shock-induced phonon up-pumping model relate to impact sensitivity of molecular crystals, polymorphs and cocrystals?

Impact sensitivity engineering of high-energy molecular crystals requires accurate predictive models. For this purpose, the promising multi-phonon based approach is selected, assessing a bit more its strengths and weaknesses. Presently used with high-quality phonon calculations of 22 molecular crystals, using a physics-based criterion to determine the phonon bath extent, the resulting intrinsic shock sensitivity index (SSI) is compared to the most common marker of impact sensitivity, h 50 , as determined from drop-weight impact tests. Selecting a data subset from experiments performed under very similar conditions (2.5 kg hammer with grit and 30–40 mg samples), the model can predict h 50 values for mono-molecular crystals with very good accuracy, including the ability to discriminate the polymorphs of HMX and CL20. This very good agreement validates an initial indirect up-pumping mechanism occurring under these conditions, where the doorway modes also interact with the phonon bath. However, the phonon bath criterion for mono-molecular crystals does not transfer well to cocrystals. Owing to the vibrational coupling of the co-molecules, it seems a broader phonon bath should be considered. Additionally recalling experimental uncertainty and various experimental factors affecting h 50 values for a given compounds, we recommend that the density of the sample, granularity and morphology be systematically considered and reported along with measurements, which will in turn allow for more systematic data and predictive capabilities for sensitivity models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identified charged-hadron production in 𝑝+Al, 3 He + Au, and Cu + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and in U + U collisions at $\sqrt{s_{NN}}$ = 193 GeV

The PHENIX experiment has performed a systematic study of identified charged-hadron (𝜋 ± , 𝐾 ± , 𝑝, $\bar{𝑝}$) production at midrapidity in 𝑝 + Al, 3 He + Au, and Cu + Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and U + U collisions at $\sqrt{s_{NN}}$ = 193 GeV. Identified charged-hadron invariant transverse-momentum (𝑝 𝑇 ) and transverse-mass (𝑚 𝑇 ) spectra are presented and interpreted in terms of radially expanding thermalized systems. The particle ratios of 𝐾/𝜋 and 𝑝/𝜋 have been measured in different centrality ranges of large (Cu + Au and U + U) and small (𝑝 + Al and 3 He + Au) collision systems. The values of 𝐾/𝜋 ratios measured in all considered collision systems were found to be consistent with those measured in 𝑝+𝑝 collisions. However, the values of 𝑝/𝜋 ratios measured in large collision systems reach the values of ≈0.6, which is a factor of ≈2 larger than in 𝑝 + 𝑝 collisions. These results can be qualitatively understood in terms of the baryon enhancement expected from hadronization by recombination. Identified charged-hadron nuclear-modification factors (𝑅 𝐴⁢𝐵 ) are also presented. Enhancement of proton 𝑅 𝐴⁢𝐵 values over meson 𝑅 𝐴⁢𝐵 values was observed in central 3 He + Au, Cu + Au, and U + U collisions. Finally, the proton 𝑅 𝐴⁢𝐵 values measured in the 𝑝 + Al collision system were found to be consistent with 𝑅 𝐴⁢𝐵 values of 𝜙, 𝜋 ± , 𝐾 ± , and 𝜋 0 mesons, which may indicate that the size of the system produced in 𝑝 + Al collisions is too small for recombination to cause a noticeable increase in proton production.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A Hydro-based MCMC Analysis of SNR 0509–67.5: Revealing the Explosion Properties from Fluid Discontinuities Alone

Using Hubble Space Telescope/ACS Hα images of SNR 0509–67.5 taken ~10 yr apart, we measure the forward shock (FS) proper motions (PMs) at 231 rim locations. The average shock radius and velocity are 3.66 ± 0.036 pc and 6315 ± 310 km s –1 . Hydrodynamic simulations, recast as similarity solutions, provide models for the supernova remnant’s expansion into a uniform ambient medium. These are coupled to a Markov chain Monte Carlo (MCMC) analysis to determine explosion parameters, constrained by the FS measurements. For our baseline model, the MCMC posteriors yield an age of 315.5 ± 1.8 yr, a dynamical explosion center at 5 h 09 m 31. s 16, $-67^\circ 31^{\prime} 17\buildrel{\prime\prime}\over{.} 1$ and ambient medium densities at each azimuth ranging over 3.7–8.0 × 10 –25 g cm –3 . The age uncertainty can be an order of magnitude larger when considering other models, or subsets of the data. We detect stellar PMs corresponding to speeds in the Large Magellanic Cloud ≥ 770 km s –1 . Five stars in the remnant show measurable PMs but none are moving radially from the dynamical center. There are four stars 1."4 from the center, including three faint, previously unidentified ones. Using coronal [Fe XIV ] λ5303 emission as a proxy for the reverse shock location, we constrain the explosion energy (for a compression factor of 4) to a value of E = (1.30 ± 0.41) × 10 51 erg for the first time from shock kinematics alone. Higher compression factors (7 or more) are strongly disfavored based on multiple criteria, arguing for inefficient particle acceleration in the Balmer shocks of SNR 0509–67.5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Exciton Fine Structure in 2D Perovskites: The Out‐of‐Plane Excitonic State

2D Ruddlesden‐Popper metal‐halide perovskites feature particularly strong excitonic effects, making them a fascinating playground for studying exciton physics. A complete understanding of the properties of this quasi‐particle is crucial to fully exploit the tremendous potential of 2D perovskites (2DP) in light emission applications. Despite intense investigations, some of the exciton properties remain elusive to date, for example, the energy‐ordering of the exciton states within the so‐called fine structure manifold. Using optical spectroscopy, it demonstrates that in the archetypical 2DP (PEA) 2 PbI 4 , in contradiction to theoretical predictions, the energy of the bright out‐of‐plane exciton state is higher than that of two in‐plane states. Having elucidated the order of exciton fine structure, it determines the g ‐factor of the dark exciton transition, together with the values of the electron and hole g ‐factors in the direction parallel to the c ‐axis of the crystal. In this way, it provides for the first time, a complete picture of the exciton fine structure in (PEA) 2 PbI 4 2DP.

2D perovskites↗
DOE OSTI2024

Detection of a Cobalt-Containing Interphase at the Li 6 PS 5 Cl-NMC111 Interface by In Situ μ XANES and EIS

Sulfide electrolyte all-solid-state lithium batteries (ASLBs) with uncoated Li-Ni x Mn y Co 1–x–y O 2 (NMC) cathodes suffer from a large capacity loss during initial cycling and an increase in cell impedance. Decomposition reactions are known to occur at the Li 6 PS 5 Cl-NMC111 interface due to incompatibility between the two materials. If a stabilizing coating is applied to the NMC, it delivers full capacity during initial charge. However, the loss in capacity during discharge still occurs. The interface was studied by μ XANES and through EIS analysis. A chemically-formed interphase was detected by μ XANES, evident from reduction of Co at an uncoated NMC particle surface. This interphase was produced by decomposition at rest. To study the effect of the interphase on electrochemically active surface area, piecewise in situ EIS was performed and the data was modeled using a transmission line model (TLM). The charge transfer resistance R CT was used to estimate the volume specific active surface area (a act ). The median value for a act was 296 cm –1 , a factor of 7.5 lower than the theoretical value of 2216 cm –1 . This provided evidence of a lower electrochemically active surface area in the ASLB.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Progress on Demonstration of a MOOSE-Based Coupled Capability for Hot Channel Factors in Fast Reactors

Hot channel factors (HCFs) are computed values that account for the impact on predicted peak fuel, cladding, and coolant temperatures due to uncertainties in the as-built reactor’s material properties and geometry as well as uncertainties due to modeling approximations. Reduction in computed HCF values via reduction or elimination of modeling approximations may translate to significant economic savings if the reactor power can be raised due to the extra temperature margin gained. While limited historical datasets exist for sodium-cooled fast reactors (SFRs), there are no available HCF data for lead-cooled fast reactors (LFRs) outside of work generated previously within NEAMS. The computation of HCFs involves insights from reactor physics, thermal fluids and heat conduction calculations to determine how the peak temperatures respond to various uncertainties in the design. Due to the significant advantages for multi-physics coupling offered by the MOOSE framework, Griffin (MOOSE-based reactor physics code), MOOSE Heat Conduction Module, and Cardinal (MOOSE-wrapped multi-physics application which includes the NekRS thermal fluids code) are being coupled together using the MOOSE MultiApp System to develop a highfidelity multi-physics modeling capability for HCF simulations. This high-fidelity coupling workflow may also be beneficial for other fast reactor applications in the future. In previous work, Griffin and NekRS were individually assessed to ensure the necessary capabilities were in place. This work describes initial efforts to couple the codes (including folding in the MOOSE Heat Conduction Module) and determining the workflow for the perturbed calculations which will leverage the Stochastic Tools Module (STM). To our knowledge, this is the first coupling of Griffin and NekRS as well as the first exploratory use of Stochastic Tools Module for Cardinal. In this report, the neutronics code Griffin, the heat conduction solver in MOOSE, and the MOOSE-wrapped application containing NekRS (Cardinal) are linked together to demonstrate the coupled capability. Griffin and Cardinal are linked dynamically by specifying shared libraries. Different coupling hierarchies are tested for selecting the most appropriate coupling strategy. A coupling scheme is selected based on the efficiency of calculation and ease of data communication. Multiple tests are performed to choose suitable mesh structure, model configurations, scheme setup and boundary conditions to avoid loss of energy due to data interpolation between different modules or weak imposition of fluxes in finite element codes. Computational experiments are performed to study the tolerance control of each type of iteration to avoid false convergence. The coupled capability is demonstrated in both single pin and 7-pin models based on LFR materials and geometry. The study finds that the use of too large a time step size in the heat conduction module can lead to temperature oscillation even though the heat conduction equation does not have a time-derivative kernel, but only the time-dependent boundary condition. A 7-pin model without duct region achieved good convergence in the coupled calculation while a 7 pin model with duct region experienced data communication issues which need to be resolved.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Implementation of AI/DEEP learning disruption predictor into a plasma control system

Abstract This paper reports on advances in the state‐of‐the‐art deep learning disruption prediction models based on the Fusion Recurrent Neural Network (FRNN) originally introduced in a 2019 NATURE publication [ https://doi.org/10.1038/s41586‐019‐1116‐4 ]. In particular, the predictor now features not only the “disruption score,” as an indicator of the probability of an imminent disruption, but also a “sensitivity score” in real time to indicate the underlying reasons for the imminent disruption. This adds valuable physics interpretability for the deep learning model and can provide helpful guidance for control actuators now implemented into a modern plasma control system (PCS). The advance is a significant step forward in moving from modern deep learning disruption prediction to real‐time control and brings novel AI‐enabled capabilities relevant for application to the future burning plasma ITER system. Our analyses use large amounts of data from JET and DIII‐D vetted in the earlier NATURE publication. In addition to “when” a shot is predicted to disrupt, this paper addresses reasons “why” by carrying out sensitivity studies. FRNN is accordingly extended to use more channels of information, including measured DIII‐D signals such as (i) the “n1rms” signal that is correlated with the n = 1 modes with finite frequency, including neoclassical tearing mode and sawtooth dynamics; (ii) the bolometer data indicative of plasma impurity control; and (iii) “q‐min”—the minimum value of the safety factor relevant to the key physics of kink modes. The additional channels and interpretability features expand the ability of the deep learning FRNN software to provide information about disruption subcategories as well as more precise and direct guidance for the actuators in a PCS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Temperature-responsive smart tracers for field-measurement of inter-well thermal evolution: Heterogeneous kinetics and field demonstration

Temperature-responsive smart tracers enable advanced warning of a “premature thermal breakthrough” and may therefore improve reservoir management and reduce financial risk. A successful calculation of inter-well fluid temperatures requires that temperature-dependent kinetics are known, which typically result from homogeneous batch reactor experiments. However, recent meso-scale field experiments at the Altona Field Laboratory involving fluid flow in a discretely-fractured reservoir suggest that silica-fluid interfaces may accelerate hydrolysis kinetics. Here, the Arrhenius parameters of phenyl acetate hydrolysis are investigated under heterogeneous reaction conditions in packed-bed column experiments. The breakthrough curve of the reaction product is compared to an inert reference tracer (carbon-cored nanoparticles). Temperatures experienced during field testing ranging from 10 to 40 °C were studied using a phosphate buffer solution to maintain a near-neutral pH, as found in the reservoir. The empirically-determined pre-exponential factor and activation energy values are subsequently used in a first-order kinetic model to improve calculations of effective reservoir temperatures for these meso-scale field tests. Here, the results suggest that hydrolysis reactions can directly monitor inter-well reservoir temperatures, but only if the influence of solid-fluid interactions are carefully accounted for.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures

The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Estimating the CO 2 Fertilization Effect on Extratropical Forest Productivity From Flux‐Tower Observations

Abstract The land sink of anthropogenic carbon emissions, a crucial component of mitigating climate change, is primarily attributed to the CO 2 fertilization effect on global gross primary productivity (GPP). However, direct observational evidence of this effect remains scarce, hampered by challenges in disentangling the CO 2 fertilization effect from other long‐term confounding drivers, particularly climatic changes. Here, we introduce a novel statistical approach to separate the CO 2 fertilization effect on photosynthetic carbon uptake using eddy covariance (EC) records across 38 extratropical forest sites. We find the median stimulation rate of GPP to be 3.2 ± 0.9 gC m −2 yr −1 ppm −1 (or 16.4 ± 4.2% per 100 ppm) under increasing atmospheric CO 2 across these sites, respectively. To validate the robustness of our findings, we test our statistical method using factorial simulations of an ensemble of process‐based land surface models. We address additional factors, including nitrogen deposition and land management, that may impact plant productivity, potentially confounding the attribution to the CO 2 fertilization effect. Assuming these site‐specific effects offset to some extent across sites as random factors, the estimated median value still reflects the strength of the CO 2 fertilization effect. However, disentanglement of these long‐term effects, often inseparable by timescale, requires further causal research. Our study provides direct evidence that the photosynthetic stimulation is maintained under long‐term CO 2 fertilization across multiple EC sites. Such observation‐based quantification is key to constraining the long‐standing uncertainties in the land carbon cycle under rising CO 2 concentrations.

Environmental Sciences & Ecology↗
DOE OSTI2024

Investigation of core transport changes in DIII-D discharges with off-axis T e profile peaks

Abstract DIII-D discharges that transition to H-mode solely with off-axis electron cyclotron heating (ECH) often exhibit strong off-axis peaking of electron temperature profiles at the heating location. Electron heat transport properties near these off-axis temperature peaks have been studied using modulated ECH. The Fourier analyzed electron temperature data have been used to infer electron thermal diffusivity. Comparisons with numerical solutions of the time-dependent electron thermal equation find that the data are consistent with a narrow region with electron diffusivity χ e an order of magnitude lower than the average value across the plasma, suggesting an electron internal transport barrier (ITB) near the ECH heating location. Detailed profile analysis and equilibrium reconstructions suggest that the formation of these ITBs are correlated with off-axis values of the safety factor q being near 1. Furthermore, the ECH driven H-mode discharges demonstrate more rapid electron heating rate near the ECH deposition location than L-mode discharges with higher auxiliary ECH heating power. Additional modeling attributes this difference to the modification of electron heat transport in the core at the L-H transition, which also sustains the off-axis electron temperature peaks.

Physics↗
DOE OSTI2023

A prescription for the asteroseismic surface correction

In asteroseismology, the surface effect refers to a disparity between the observed and the modelled frequencies in stars with solar-like oscillations. It originates from improper modelling of the surface layers. Correcting the surface effect usually requires using functions with free parameters, which are conventionally fitted to the observed frequencies. On the basis that the correction should vary smoothly across the H–R diagram, we parameterize it as a simple function of surface gravity, effective temperature, and metallicity. We determine this function by fitting a wide range of stars. The absolute amount of the surface correction decreases with luminosity, but the ratio between it and νmax increases, suggesting the surface effect is more important for red giants than dwarfs. Applying the prescription can eliminate unrealistic surface correction, which improves parameter estimations with stellar modelling. Using two open clusters, we found a reduction of scatter in the model-derived ages for each star in the same cluster. As an important application, we provide a new revision for the Δν scaling relation that, for the first time, accounts for the surface correction. The values of the correction factor, f Δν , are up to 2 percent smaller than those determined without the surface effect considered, suggesting decreases of up to 4 percent in radii and up to 8 percent in masses when using the asteroseismic scaling relations. This revision brings the asteroseismic properties into an agreement with those determined from eclipsing binaries. The new correction factor and the stellar models with the corrected frequencies are available at https://www.github.com/parallelpro/surface.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Commensuration Effects in Layered Nanoparticle Solids.

We have developed a hierarchical nanoparticle transport simulator (HINTS) and adapted it to study commensuration effects in two classes of nanoparticle (NP) solids: (1) a bilayer NP solid (BNS) with an energy offset and (2) a BNS as part of a field effect transistor (FET). HINTS integrates the ab initio characterization of single NPs with the phonon-assisted tunneling transition model of the NP-NP transitions into a kinetic Monte Carlo based simulation of the charge transport in NP solids. First, we studied a BNS with an interlayer energy offset Delta, possibly caused by a fixed electric field. Our results include the following. First, in the independent energy-offset model, we observed the emergence of commensuration effects when scanning the electron filling factor (FF) across integer values. These commensuration effects were profound as they reduced the mobility by several orders of magnitude. We analyzed these commensuration effects in a five-dimensional parameter space, as a function of the on-site charging energy E-C, energy offset Delta, disorder D, the electron FF, and temperature k(B)T. We demonstrated the complexity of our model by showing that at integer FFs commensuration effects are present in some regions of the parameter space, while they vanish in other regions, thus defining distinct dynamical phases of the model. We determined the phase boundaries between these dynamical phases. Second, using these results as a foundation, we shifted our focus to the experimentally much-studied NP-FETs. NP-FETs are also characterized by an interlayer energy offset Delta, which, in contrast to our first model, is set by the gate voltage V-G and thereby related to the electron FF. We repeated many of our simulations and again demonstrated the emergence of commensuration effects and distinct dynamical phases in these NP-FETs. Notably, the commensuration effects in the NP-FETs showed many similarities to those in the independent energy-offset BNS.

Qu, Luman↗