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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Spectroscopic Investigation into P(NDI2OD-T2) Charge Localization

P(NDI2OD-T2), commonly referred to as N2200, stands out as a promising electron-transporting (n-type) polymer for low-cost, flexible (photo)electrochemical applications due to its reversible two-electron reduction and high electron mobility. UV–vis spectroelectrochemistry in the tetrabutyl ammonium hexafluorophosphate/acetonitrile electrolyte shows two sets of chemically reversible redox signals in the cyclic voltammetry corresponding to the reduction of the neutral polymer film to polaronic and bipolaronic species. These electrochemical signatures suggest a distinct electronic reorganization upon reduction (polaron/bipolaron formation), highlighting the need for molecular-level insights into how charges are accommodated within the polymer backbone. While it has been previously hypothesized that charge predominantly localizes on the naphthalene diimide (NDI) unit during reductive charging, specific changes in atomic environments that confirm this localization have not been characterized in n-type polymers. Herein, we use near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe electronic transitions in an electrochemically charged polymer to deduce charge localization. The O K-edge (1s) spectra exhibit two distinct π* peaks; the intensity of the lower-energy π* a peak that corresponds to an excitation to a largely localized carbonyl state decreases with reductive potentials relative to the higher-energy π* b peak. We corroborate this with Raman spectroscopy at different potentials, which shows a decrease in intensity on the C–C/C═C and C═O stretching bands of NDI as well as a red shift of the carbonyl band due to the formation of a polaron on the NDI. Additionally, new Raman active NDI signals associated with elongated C═O and C═C bonds are observed at lower energy during the formation of charged states. Together with theoretical calculations, these findings show that the injected charge spatially localizes on the NDI units and is dominantly distributed on the carbonyl groups. In conclusion, the combination of NEXAFS, optical and vibrational spectroscopies, and theoretical calculations is generalizable to other pi-conjugated polymers and can identify charge localization for the further development of organic semiconductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Local Chemical Ordering and Negative Thermal Expansion in PtNi Alloy Nanoparticles

An atomic insight into the local chemical ordering and lattice strain is particular interesting to recent emerging bimetallic nanocatalysts such as PtNi alloys. Here in this paper, we reported the atomic distribution, chemical environment and lattice thermal evolution in full-scale structural description of PtNi alloy nanoparticles (NPs). The different segregation of elements in the well-faceted PtNi nanoparticles is convinced by extended X-ray absorption fine structure (EXAFS). Atomic pair distribution function (PDF) study evidences the co-existence of the face-centered cubic and tetragonal ordering parts in the local environment of PtNi nanoparticles. Further reverse monte carlo (RMC) simulation with PDF data obviously exposed the segregation as Ni and Pt in the centers of {111} and {001} facets respectively. Layer-by-layer statistical analysis up to 6 nm for the local atomic pairs revealed the distribution of local tetragonal ordering on the surface. This local coordination environment facilitates the distribution of heteroatomic Pt-Ni pairs, which plays an important role in the negative thermal expansion of Pt 41 Ni 59 NPs. The present study on PtNi alloy NPs from local short-range coordination to long-range average lattice provides a new perspective on tailoring physical properties in nanomaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Locality of correlation in density functional theory

The Hohenberg-Kohn density functional was long ago shown to reduce to the Thomas-Fermi (TF) approximation in the non-relativistic semiclassical (or large-Z) limit for all matter, i.e., the kinetic energy becomes local. Exchange also becomes local in this limit. Numerical data on the correlation energy of atoms support the conjecture that this is also true for correlation, but much less relevant to atoms. We illustrate how expansions around a large particle number are equivalent to local density approximations and their strong relevance to density functional approximations. Analyzing highly accurate atomic correlation energies, we show that E{sub C} → −A{sub C} ZlnZ + B{sub C}Z as Z → ∞, where Z is the atomic number, A{sub C} is known, and we estimate B{sub C} to be about 37 mhartree. The local density approximation yields A{sub C} exactly, but a very incorrect value for B{sub C}, showing that the local approximation is less relevant for the correlation alone. This limit is a benchmark for the non-empirical construction of density functional approximations. We conjecture that, beyond atoms, the leading correction to the local density approximation in the large-Z limit generally takes this form, but with B{sub C} a functional of the TF density for the system. The implications for the construction of approximate density functionals are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

We report that local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. Finally, we also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Probing many-body localization on a noisy quantum computer

A disordered quantum system of interacting particles exhibits localized behavior when the disorder is large compared to the interaction strength. Studying this phenomenon on a quantum computer with no, or limited, error correction is challenging because even weak coupling to a thermal environment destroys most signatures of localization. Fortunately, spectral functions of local operators are known to contain features that can survive the presence of noise. In these spectra, discrete peaks and a soft gap at low frequencies compared to the thermal phase indicate localization. Here, we present the computation of spectral functions on a trapped-ion quantum computer for a one-dimensional Heisenberg model with disorder. Further, we design an error-mitigation technique which is effective at removing the noise from the measurement allowing clear signatures of localization to emerge as the disorder increases. Furthermore, we show that spectral functions can serve as a robust and scalable diagnostic of many-body localization on current and future generations of quantum computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Anderson Localization in the Fractional Quantum Hall Effect

The interplay between interaction and disorder-induced localization is of fundamental interest. This article addresses localization physics in the fractional quantum Hall state, where both interaction and disorder have nonperturbative consequences. We provide compelling theoretical evidence that the localization of a single quasiparticle of the fractional quantum Hall state at filling factor ν=n/(2n+1) has a striking quantitative correspondence to the localization of a single electron in the (n+1)th Landau level. By analogy to the dramatic experimental manifestations of Anderson localization in integer quantum Hall effect, this leads to predictions in the fractional quantum Hall regime regarding the existence of extended states at a critical energy, and the nature of the divergence of the localization length as this energy is approached. Within a mean field approximation, these results can be extended to situations where a finite density of quasiparticles is present.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks

Rapid and accurate detection and localization of electronic disturbances simultaneously are important for preventing its potential damages and determining potential remedies. Existing anomaly detection methods are severely limited by the low accuracy, the expensive computational cost and the need for highly trained personnel. There is an urgent need for a scalable online algorithm for in-field analysis of large-scale power electronics networks. Here in this paper, we propose a fast and accurate algorithm for anomaly detection and localization of power electronics networks: stratified colored-node graph (CONGO2). This algorithm hierarchically models the change of correlated waveforms and then correlated sensors using the colored-node graph. By aggregating the change of each sensor with its neighbors’ inputs, we can spontaneously identify and localize the anomaly that cannot be detected by data collected from a single sensor. As our proposed method only focuses on the changes within a short time frame, it is highly computational efficient and only needs small data storage. Thus, our method is ideal for online and reliable anomaly detection and localization of large-scale power electronic networks. Compared to existing anomaly detection methods, our method is entirely data-driven without training data, highly accurate and reliable for wide-spectrum anomalies detection, and more importantly, capable of both detection and localization. Thus, it is ideal for infield deployment for large-scale power electronic networks. As illustrated by a distributed energy resources (DERs) power grid with 37-node, our method can effectively detect and localize various cyber and physical attacks.

42 ENGINEERING↗
DOE OSTI2023

Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

Here this paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Electrochemically modulated single-molecule localization microscopy for in vitro imaging cytoskeletal protein structures

A new concept of electrochemically modulated single-molecule localization super-resolution imaging is developed. Applications of single-molecule localization super-resolution microscopy have been limited due to insufficient availability of qualified fluorophores with favorable low duty cycles. The key for the new concept is that the “On” state of a redox-active fluorophore with unfavorable high duty cycle could be driven to “Off” state by electrochemical potential modulation and thus become available for single-molecule localization imaging. The new concept was carried out using redox-active cresyl violet with unfavorable high duty cycle as a model fluorophore by synchronizing electrochemical potential scanning with a single-molecule localization microscope. The two cytoskeletal protein structures, the microtubules from porcine brain and the actins from rabbit muscle, were selected as the model target structures for the conceptual imaging in vitro. The super-resolution images of microtubules and actins were obtained from precise single-molecule localizations determined by modulating the On/Off states of single fluorophore molecules on the cytoskeletal proteins via electrochemical potential scanning. Importantly, this method could allow more fluorophores even with unfavorable photophysical properties to become available for a wider and more extensive application of single-molecule localization microscopy.

electrochemical modulation↗
DOE OSTI2019

LLOCUS: Learning-based Localization Using crowdSourcing

We propose a novel learning-based system, LLOCUS, enabled by crowdsourcing on mobile devices, for localizing mobile transmitters with unknown transmit power. Our approach carefully tackles several challenges in learning and localizing using a crowdsourced system with both ends’ mobility, the ‘ends’ being the transmitters and the receivers. We decouple the problem of localizing a transmitter with unknown transmit power into two problems, 1) predicting the transmit power of an unknown transmitter, and 2) localizing a transmitter with known transmit power. LLOCUS first estimates the transmit power of the unknown transmitter and then scales the reported RSS values such that the unknown transmit power problem is transparent to the method of localization. We evaluate LLOCUS using four experiments, in different indoor and outdoor environments, with the size of the areas ranging from 225 to 5500 square meters. We find that LLOCUS reduces the localization error by 17-47%, over a number of non-learning methods. LLOCUS also estimates the transmit power of an unknown transmitter with average error in the range of 3-5 dB, across our experiments.

42 ENGINEERING↗
DOE OSTI2015

Modification of the Local Cubic Law of fracture flow for weak inertia, tortuosity, and roughness

The classical Local Cubic Law (LCL) generally overestimates flow through real fractures. We thus developed and tested a modified LCL (MLCL) which takes into account local tortuosity and roughness, and works across a low range of local Reynolds Numbers. The MLCL is based on (1) modifying the aperture field by orienting it with the flow direction and (2) correcting for local roughness changes associated with local flow expansion/contraction. In order to test the MLCL, we compared it with direct numerical simulations with the Navier-Stokes equations using real and synthetic three-dimensional rough-walled fractures, previous corrected forms of the LCL, and experimental flow tests. The MLCL performed well and the effective errors (δ) in volumetric flow rate range from -6.7% to 13.4% with an arithmetic mean of |δ| (<|δ|>) equal to 3.7%. The MLCL is more accurate than previous modifications of the LCL. We also investigated the error associated with applying the Cubic Law (CL) while utilizing modified aperture field. The δ from the CL ranges from -14.2% to 11.2%, with a slightly higher <|δ|> = 6.1% than the MLCL. The CL with the modified aperture field considering local tortuosity and roughness may also be sufficient for predicting the hydraulic properties of rough fractures.

58 GEOSCIENCES↗
DOE OSTI2018

Local Infrasound Variability Related to In Situ Atmospheric Observation

Abstract Local infrasound is widely used to constrain source parameters of near‐surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3‐D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere‐dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

58 GEOSCIENCES↗
DOE OSTI2021

0D Nanocrystals as Light‐Driven, Localized Charge‐Injection Sources for the Contactless Manipulation of Atomically Thin 2D Materials

A contactless charge‐injection scheme that allows the local and quasi‐permanent manipulation of atomically thin 2D materials, such as monolayer (1L‐)MoS 2 , over spatial extents of several tens of micrometers, is reported. The possibility to precisely position and localize the charge‐injection source to the micrometer scale post‐fabrication allows the investigation of local unperturbed electronic structure of the 2D material. Thanks to this novel approach, the important impact of sample inhomogeneity on the charge‐carrier percolation that occurs over the entire extent of the 2D flake and proliferates up to 40 μm away from the localized charge injection is elucidated. The apparent driving force for carrier relocation is the initial inhomogeneous electronic landscape of the 2D material. These studies demonstrate that local and contactless charge injection with submicrometer precision delivers an alternative route for charge injection and indicates that local 2D material electronic structure can serve as a key element for novel nanoscale device design.

Ghini, Michele↗
DOE OSTI2021

In situ and operando force-based atomic force microscopy for probing local functionality in energy storage materials

Electrochemical energy storage is the key enabling component of electric vehicles and solar-/wind-based energy technologies. The enhancement of energy stored requires the detailed understanding of charge storage mechanisms and local electrochemical and electromechanical phenomena over a variety of length scales from atoms to full cells. Classical electrochemical techniques, such as voltammetry, represent the macroscopic electrochemical properties, and consequently do not allow to extract important information about local electrochemical reactions, ions adsorption, intercalations, and transport. Understanding, controlling, and tuning the local electrochemical functionalities in functional energy materials require in situ/operando techniques which limit the use of structural and functional characterization techniques that provide local information. Here, force-based atomic force microscopies (AFMs) have provided novel insights into locally probing electrochemical mechanisms on tens of nanometer and even molecular length scales and provide a viable pathway to probe electrochemical processes in situ/operando. In this review, we highlight the contributions in the development and application of force-based AFM methods to elucidate the local charge storage mechanism in a variety of energy-related materials. We will focus in particular on methods or AFM modalities in a liquid electrolyte environment.

25 ENERGY STORAGE↗
DOE OSTI2016

Thermoplasticity and strain localization in transversely isotropic materials based on anisotropic critical state plasticity

Geomaterials including soils and rocks are inherently anisotropic and sensitive to temperature changes caused by various internal and external processes. They are also susceptible to strain localization in the form of shear bands when subjected to critical loads. In this paper, we present a thermo-plastic framework for modeling coupled thermo-mechanical response and for predicting the inception of a shear band in a transversely isotropic material using the general framework of critical state plasticity and the specific framework of an anisotropic modified Cam-Clay model. The formulation incorporates anisotropy in both elastic and plastic responses under the assumption of infinitesimal deformation. The model is first calibrated using experimental data from triaxial tests to demonstrate its capability in capturing anisotropy in the mechanical response. Subsequently, stress-point simulations of strain localization are carried out under two different conditions, namely, isothermal localization and adiabatic localization. The adiabatic formulation investigates the effect of temperature on localization via thermo-mechanical coupling. Numerical simulations are presented to demonstrate the important role of anisotropy, hardening, and thermal softening on strain localization inception and orientation.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Lymphangiography in the Diagnosis and Localization of Various Chyle Leaks

Purpose: Chyle leaks are rare entities infrequently encountered by most physicians. However, large centers providing advanced surgical care are inevitably confronted with chyle leaks as a complication of surgery, an extension of disease, or as a primary disorder. Regardless of the etiology, proper diagnosis and localization are paramount in the management of any chyle leak. Materials and Methods: Here we present 16 patients with 17 chyle leaks (5 chyluria, 8 chylothorax, and 4 chylous ascites) who underwent bipedal lymphangiography (LAG) and postprocedure computed tomography (CT) imaging. Results: In each case, the source of the chyle leak was identified and properly localized to guide further treatment. Of the 16 patients who underwent LAG and postprocedure CT imaging, the initial LAG alone provided the diagnosis and localized the chyle leak in 4 patients (25%); the postprocedure CT imaging provided the diagnosis and localized the chyle leak in 6 patients (37.5%); and the two modalities were equal in the diagnosing and localizing the chyle leak in the remaining 6 patients (37.5%)ConclusionThese cases highlight the unparalleled abilities of LAG and the added benefit of post-LAG CT imaging in the diagnosis and fine anatomic localization of chyle leaks. In addition, these cases demonstrate the retained utility of LAG in these investigations despite the development of alternative tests involving CT, magnetic resonance imaging, and nuclear medicine imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

The Value of Hybrid Angio-CT in Preoperative Detection and Localization of Insulinomas: A Single-Center Retrospective Study

ObjectiveTo investigate the performance of hybrid angio-CT in preoperative detection and localization for insulinomas.MethodsFifty-four postoperative pathology-confirmed patients from April 2015 to March 2017 were retrospectively reviewed; all patients underwent angio-CT with administration of contrast media in SMA, GDA and SA due to negative, inconclusive or controversial findings by several preoperative diagnostic methods including TAUS, CEUS, EUS, ECT, EMRI and DSA. Surgery was used as gold standard for localization of insulinomas; detection sensitivity and localization accuracy of angio-CT were assessed and compared with other preoperative image options.ResultsFifty-six benign insulinomas (mean diameter, 15.8 mm) in 54 patients (18 men and 36 women) were found according to surgical results; the overall detection sensitivity of TAUS, CEUS, EUS, ECT, EMRI and DSA was 21.4, 78.4, 79.2, 70.0, 79.2 and 72.2%, respectively. The overall localization accuracy was 14.3, 58.8, 68.8, 60.0, 75.0 and 44.4%, respectively. A total of 53 tumors were detected by angio-CT, 51 tumors were accurately located, and the overall detection sensitivity and localization accuracy of angio-CT was 94.4 and 90.7%, which was significantly higher than that of all other preoperative diagnostic methods (p < 0.05). No any serious complications occurred during angio-CT.ConclusionOur study indicates the great potential value of angio-CT in the preoperative detection and localization of insulinomas; angio-CT can be used as a preferred invasive diagnostic method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

U-net architected deep material network training with microstructure local field information

The Deep Material Network (DMN) has recently emerged as a powerful reduced-order modeling framework for simulating the mechanical response of heterogeneous materials such as composites. Unlike most data-driven approaches that directly learn a material’s response under prescribed loading, the DMN acts as a homogenization operator, learning the kinematic constraints and mechanical interactions of the underlying microstructure. However, traditional DMN training relies exclusively on homogenized effective properties derived from Direct Numerical Simulations (DNS), discarding the rich local field data that govern microstructural interactions. In this work, we extend the DMN framework to incorporate such local field information into the offline training process. Utilizing a U-Net architecture, we augment the DMN training objective to include the first and second statistical moments of the local stress fields obtained from linear DNS. This ensures that the learned network topology not only fits the effective stiffness but also accurately reflects the internal local stress and strain partitioning of the microstructure. The results confirm that supervising the localization process during training yields a superior surrogate model, reducing local prediction errors by an order of magnitude and significantly improving generalization to unseen nonlinear constitutive behaviors compared to traditional DMNs.

36 MATERIALS SCIENCE↗