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DOE OSTI2024

Sound-localization-related activation and functional connectivity of dorsal auditory pathway in relation to demographic, cognitive, and behavioral characteristics in age-related hearing loss

Background Patients with age-related hearing loss (ARHL) often struggle with tracking and locating sound sources, but the neural signature associated with these impairments remains unclear. Materials and methods Using a passive listening task with stimuli from five different horizontal directions in functional magnetic resonance imaging, we defined functional regions of interest (ROIs) of the auditory “where” pathway based on the data of previous literatures and young normal hearing listeners ( n = 20). Then, we investigated associations of the demographic, cognitive, and behavioral features of sound localization with task-based activation and connectivity of the ROIs in ARHL patients ( n = 22). Results We found that the increased high-level region activation, such as the premotor cortex and inferior parietal lobule, was associated with increased localization accuracy and cognitive function. Moreover, increased connectivity between the left planum temporale and left superior frontal gyrus was associated with increased localization accuracy in ARHL. Increased connectivity between right primary auditory cortex and right middle temporal gyrus, right premotor cortex and left anterior cingulate cortex, and right planum temporale and left lingual gyrus in ARHL was associated with decreased localization accuracy. Among the ARHL patients, the task-dependent brain activation and connectivity of certain ROIs were associated with education, hearing loss duration, and cognitive function. Conclusion Consistent with the sensory deprivation hypothesis, in ARHL, sound source identification, which requires advanced processing in the high-level cortex, is impaired, whereas the right–left discrimination, which relies on the primary sensory cortex, is compensated with a tendency to recruit more resources concerning cognition and attention to the auditory sensory cortex. Overall, this study expanded our understanding of the neural mechanisms contributing to sound localization deficits associated with ARHL and may serve as a potential imaging biomarker for investigating and predicting anomalous sound localization.

Wu, Junzhi↗

DOE OSTI2026

Improved Spectral Classification of Local K/M Dwarfs in SDSS Surveys. I. Chemodynamic Validation and Metallicity Calibration

An examination of 109,276 spectra of low-mass stars in the Sloan Digital Sky Survey (SDSS) data archive, collected pre-2010, provides a broad collection of K/M (sub)dwarfs tracing the local (d ≲ 250 pc) population of the thin-disk, thick-disk, and halo, based on 3D kinematics. These populations have distinct metallicities and kinematics, which should be reflected in lower-mass members. One complication is measuring metallicities of M dwarfs from low-resolution spectroscopy or photometry alone remains a challenge, even with the availability of Gaia data. To better characterize physical parameters of low-mass stars observed by SDSS, we define a set of 536 improved, empirical K/M dwarf classification templates to more accurately determine spectral subtypes (K5.5–M8.5) and morphology classes (MCs) (0.5–12.5). We select the best-fit template to every archival SDSS spectrum in the range 5000–8000 Å based on minimum χ 2 value. We then use secondary metallicity estimators to calibrate the most likely [Fe/H] values corresponding to the assigned MC. We confirm that the most metal-rich K/M dwarfs have thin-disk kinematics, and we observe the known effect of Galactic radial metallicity migration, which we confirm is strongly imprinted in the chemodynamics of the local disk M dwarfs. Confirmation of these chemodynamic trends validates the precision of our improved templates for estimating [Fe/H] for M (sub)dwarfs, notably at the low-metallicity end (–3 < [Fe/H] < –1). Substructure in the chemodynamics of the most metal-poor K/M subdwarfs begins to distinguish between local Gaia-Enceladus and local in situ halo objects. This methodology opens the door to use the ubiquitous, local K/M (sub)dwarfs to trace local Galactic chemodynamics with the highest possible resolution.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Machine learning predictions for local electronic properties of disordered correlated electron systems

We present a scalable machine learning (ML) model to predict local electronic properties such as on-site electron number and double occupation for disordered correlated electron systems. Our approach is based on the locality principle, or the nearsightedness nature, of many-electron systems, which means local electronic properties depend mainly on the immediate environment. A ML model is developed to encode this complex dependence of local quantities on the neighborhood. We demonstrate our approach using the square-lattice Anderson-Hubbard model, which is a paradigmatic system for studying the interplay between Mott transition and Anderson localization. We develop a lattice descriptor based on the group-theoretical method to represent the on-site random potentials within a finite region. The resultant feature variables are used as input to a multilayer fully connected neural network, which is trained from data sets of variational Monte Carlo (VMC) simulations on small systems. We show that the ML predictions agree reasonably well with the VMC data. Our work underscores the promising potential of ML methods for multiscale modeling of correlated electron systems.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Electrically‐Driven Metal‐Insulator Transitions Emerging from Localizing Current Density and Temperature

Negative differential resistance (NDR) is a key electronic response enabling two‐terminal artificial neurons that can be achieved through different physical phenomena, including phase‐homogeneous current density and temperature (electro‐thermal) localizations and spatially‐localized metal‐insulator phase transitions (MITs). These two effects have been observed to occur sequentially in select electrically‐biased transition metal oxides. However, it is unknown why and under what conditions localizing behaviors precede MITs, particularly as a function of device length scale. To this end, the interplay between phase‐homogeneous electro‐thermal localizations and MITs is investigated in a 3D multiphysics simulation of a lateral thin film device, using the material properties of the prototype MIT material VO 2 . These findings demonstrate that the MIT is nucleated through dynamically localizing current density and temperature. A critical device width (≈0.7 µm in this study) is identified, below which both the electrically‐induced electro‐thermal and phase inhomogeneities cease to appear. It is demonstrated that the formation of spatial inhomogeneities directly relates to device dimensions, and demonstrate the decoupling of NDR from the MIT through device scaling relationships. These results provide insight into the material phenomena underlying the material's electrical responses, clarifying conditions under which spatial inhomogeneities form in electrically‐biased MIT materials.

artificial neuron↗

DOE OSTI2022

Correlating hidden local structural distortion with antiferroelectric-ferroelectric transition in PbZrO 3 -based perovskites

Externally stimulated antiferroelectric-ferroelectric (AFE-FE) transition makes AFE materials attractive for many applications ranging from energy storage to sensing. This transition-mediated macroscopic electrical characteristics have been extensively investigated, yet the underlying structural evolution remains poorly understood. Herein, we study the local- and long-range structural evolutions in the Nb-doped Pb(Zr,Sn,Ti)O 3 perovskites by in-situ X-ray total scattering and diffraction, which show three different types of AFE-FE transitions. The evolution of long-range structure from diffraction and local structure identified by atomic pair distribution function (PDF) are consistent well with the phase transition behavior indicated by macroscopic polarization/strain measurements, while discrepancies exist. Interestingly, frequently employed long-range structure picture that the uniform AFE pseudo-tetragonal to FE rhombohedral transformation is insufficient to understand the distinct composition-dependent AFE-FE transition behaviours. Instead, the reversibility of this transition correlates with the chemically sensitive local atomic displacements revealed by newly developed in-situ PDF. The critical electric field of transition is associated with the local structural differences between the AFE and FE state. The macroscopic electrostrains can be well estimated by the phase transition associated lattice strain and domain alignment from in-situ synchrotron XRD data, while the local strains calculated from in-situ PDFs are found to be much lower. Finally, these results provide a fresh insight into the AFE-FE transition, and advance the understanding of structure-property relationships in AFE materials.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Probing the role of local tunnel variations in early-stage lithiation of α-MnO₂ nanowires via in situ TEM

Understanding lithium-ion transport in tunnel-structured manganese oxides is essential for designing high-performance lithium-ion battery electrode materials. Here, we elucidate the early-stage lithiation mechanism of potassium-stabilized α-MnO 2 nanowires using in situ transmission electron microscopy (TEM) coupled with electron energy-loss spectroscopy (EELS), high-resolution TEM (HRTEM), and geometric phase analysis (GPA). Real-time TEM imaging reveals clear volume expansion at the reaction front, while EELS analysis uncovers lithium-ion diffusion far beyond this region, where no visible expansion is observed, indicating fast, defect-assisted transport. GPA and HRTEM analyses show that localized tensile and compressive strain fields, originating from pre-existing local tunnel structural variations, persist after lithiation. The tensile-strained regions enable lithium-ion insertion with minimal lattice distortion, offering additional free volume that facilitates rapid lithium-ion accommodation ahead of the structural transformation. Our results demonstrate a local tunnel variation-mediated fast diffusion pathway that precedes bulk reaction, underscoring the critical role of local strain in enabling early-stage lithium transport. Given the structural versatility of MnO 2 and its ability to accommodate diverse atomic arrangements beyond the well-known tunnel phases (β-, γ-, δ-, λ-, R-phases), our findings highlight the importance of understanding and engineering local structural environments. This work provides fundamental insights into the interplay between defects, strain, and ion dynamics, and presents defect engineering as a promising approach to enhance both rate performance and structural stability in manganese-based cathodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Experimental evaluation of localized creep deformation in grade 91 steel weldments

Spatially resolved measurement of localized creep deformation in heterogeneous creep resistant steel weldments is crucial but challenging for lifetime assessments of critical steam components in power plants. Here, experimental approaches were established to quantitatively evaluate commonly observed localized creep deformation in multi-pass Grade 91 steel weldments. An in-situ digital image correlation (DIC) system was utilized with a creep testing frame to monitor and measure both full-field strain and localized strain accumulation across the weldments during long-term creep testing at elevated temperatures. The in situ DIC method measured not only the creep deformation behavior of the weld metal, heat affected zone (HAZ), and base metal, but also creep strain evolution for each sub-region within the HAZ itself, including coarse-grained HAZ, fine-grained HAZ (FGHAZ), and intercritical HAZ (ICHAZ). The DIC results revealed that local creep strain in the ICHAZ reached up to 90% strain before final rupture, whereas nominal creep strain measured by the standard extensometer of the tested cross-weld specimen was below 10%, indicative of Type IV cracking of the Grade 91 weld. Microstructural analyses revealed that the faster creep degradation/deformation in the HAZ was caused mainly by accelerated matrix grain recrystallization/growth and a reduced pinning effect from the segregated and coarsened precipitates in the FGHAZ and ICHAZ. The ultimate creep rupture occurred in the ICHAZ owing to its lowest creep resistance induced by the largest recrystallized grain size, the lowest fraction of coincidence site lattice, and the lowest local strain energies/dislocation densities.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Rapid neutron and gamma-ray source localization using machine learning

Rapid localization of radiation sources is critical for applications including nuclear emergency response, safeguards, and security. However, conventional imaging systems such as neutron scatter cameras and Compton cameras depend on rare coincidence events, which often result in long acquisition times. In this work, we address the challenge of rapid source localization by developing a machine learning approach to predict the direction of a single radiation source using only count rates from an array of neutron and gamma-ray detectors. The proposed model is a fully connected neural network (FCNN) trained using Monte Carlo simulation data from a 252 Cf source. The model hyperparameters are optimized with a small set of routine 252 Cf measurements. We benchmarked the performance of the trained and optimized machine learning model using additional 252 Cf , 137 Cs , and PuBe measurements under laboratory conditions with varying source-detector configurations. For these measurements, the machine learning model achieved a mean localization error smaller than 30° with 3 x 10 3 system counts, corresponding to 8 s measurement time for the imaging system used in this work. In this low-statistics regime, the method outperformed traditional scatter-based imaging by more than 75% in localization accuracy for the evaluated measurement configurations. These results demonstrate that a machine learning-based approach can significantly reduce the time required for accurate single-source localization, providing a robust and computationally efficient alternative to traditional imaging systems in time-critical nuclear security and emergency response scenarios.

Gamma-ray imaging↗

DOE OSTI2020

Local structure study on magnetostrictive material Tb 1–x Dy x Fe 2

Tb 1–x Dy x Fe 2 system has attracted more research interest due to the large magnetostrictive effect. The crystal structures and physical properties have been well studied, but research studies on their local structures are still rare. As such, in this work, the local structure of Tb 1–x Dy x Fe 2 samples was studied using the pair distribution function and x-ray absorption spectroscopy techniques. The results demonstrate that the system owns the same local crystal symmetry with its average structure in the ferromagnetic phase, and the crystal lattice of the system is more ordered with increasing Dy content, indicating that the Dy-rich tetragonal phase is more stable than the Tb-rich rhombohedral phase. The different roles of metallic bonds in affecting the crystal lattice are presented. The weak Fe 1 –Fe 2 bonds influenced by the local environment such as local stress from randomly distributed nanodomains could originate the anomalies in the lattice, resulting in the more ordered and stable Dy-rich phase than the Tb-rich phase.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Bandgap analysis and carrier localization in cation-disordered ZnGeN 2

The bandgap of ZnGeN 2 changes with the degree of cation site disorder and is sought in light emitting diodes for emission at green to amber wavelengths. By combining the perspectives of carrier localization and defect states, we analyze the impact of different degrees of disorder on electronic properties in ZnGeN 2 , addressing a gap in current studies, which largely focus on dilute or fully disordered systems. The present study demonstrates changes in the density of states and localization of carriers in ZnGeN 2 calculated using bandgap-corrected density functional theory and hybrid calculations on partially disordered supercells generated using the Monte Carlo method. We use localization and density of states to discuss the ill-defined nature of a bandgap in a disordered material and identify site disorder and its impact on the structure as a mechanism controlling electronic properties and potential device performance. Decreasing the order parameter results in a large reduction of the bandgap. The reduction in bandgap is due, in part, to isolated, localized states that form above the valence band continuum associated with nitrogen coordinated by more zinc than germanium. The prevalence of defect states in all but the perfectly ordered structure creates challenges for incorporating disordered ZnGeN 2 into optical devices, but the localization associated with these defects provides insight into the mechanisms of electron/hole recombination in the material.

36 MATERIALS SCIENCE↗

DOE OSTI2020

MPC-Based Local Voltage Control Strategy of DGs in Active Distribution Networks

The increasing penetration of distributed generators (DGs) exacerbates the voltage violations in active distribution networks (ADNs). The commonly used centralized voltage control may aggravate the burden of computation and communication. Local voltage control can realize fast response to frequent voltage fluctuations. However, effective local control for DGs still needs to be further investigated. In this paper, a model predictive control (MPC)-based local voltage control strategy of DGs is proposed to cope with voltage violation problems and enhance the adaptation to the DG volatility. DGs are regulated with local Q-V control curves to respond to voltage fluctuations rapidly. Based on the dynamic network partition, a unified control curve for DGs is set in the same area to realize efficient operation. To further improve the performance of voltage control, the parameter tuning of control curves is regularly conducted based on decentralized inter-area coordination with the rolling of the control horizon. Finally, case study is verified on the modified IEEE 33-node distribution system. The proposed local control strategy of DGs can effectively improve the voltage profile and reduce power losses of the whole network without high computation and communication burden.

active distribution network (ADN)↗

DOE OSTI2022

Performance Analysis of Speculative Parallel Adaptive Local Timestepping for Conservation Laws

Stable simulation of conservation laws, such as those used to model fluid dynamics and plasma physics applications, requires the satisfaction of the so-called Courant-Friedrichs-Lewy condition. By allowing regions of the mesh to advance with different timesteps that locally satisfy this stability constraint, significant work reduction can be attained when compared to a time integration scheme using a single timestep size. However, parallelizing this algorithm presents considerable difficulty. Since the stability condition depends on the state of the system, dependencies become dynamic and potentially non-local. In this article, we present an adaptive local timestepping algorithm using an optimistic (Timewarp-based) parallel discrete event simulation. We introduce waiting heuristics to limit misspeculation and a semi-static load balancing scheme to eliminate load imbalance as parts of the mesh require finer or coarser timesteps. Last, we outline an interface for separating the physics of the specific conservation law from the temporal integration allowing for productive adoption of our proposed algorithm. We present a misspeculation study for three conservation laws, demonstrating both the productivity of the local timestepping API, for which 74% of the lines of code are reused across different conservation laws, and the robustness of the waiting heuristics—at most 1.5% of element updates are rolled back. Our performance studies demonstrate up to a 2.8× speedup versus a baseline unoptimized local timestepping approach, a 4x improvement in per-node throughput compared to an MPI parallelization of synchronous timestepping, and scalability up to 3,072 cores on NERSC’s Cori Haswell partition.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Real Space Quantum Cluster Formulation for the Typical Medium Theory of Anderson Localization

We develop a real space cluster extension of the typical medium theory (cluster-TMT) to study Anderson localization. By construction, the cluster-TMT approach is formally equivalent to the real space cluster extension of the dynamical mean field theory. Applying the developed method to the 3D Anderson model with a box disorder distribution, we demonstrate that cluster-TMT successfully captures the localization phenomena in all disorder regimes. As a function of the cluster size, our method obtains the correct critical disorder strength for the Anderson localization in 3D, and systematically recovers the re-entrance behavior of the mobility edge. From a general perspective, our developed methodology offers the potential to study Anderson localization at surfaces within quantum embedding theory. This opens the door to studying the interplay between topology and Anderson localization from first principles.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Localized Flexoelectric Effect Around Ba(CuNb) Nano‐Clusters in Epitaxial BiFeO 3 Films for Enhancement of Electric and Multiferroic Properties

Abstract Room‐temperature (RT) multiferroic materials have received significant research attention for various potential applications; however, their properties are not suitable for real‐world implementation. In this study, a nano‐scale localized flexoelectric effect is introduced to enhance the RT multiferroic performance of epitaxial bismuth iron oxide (BiFeO 3 ; BFO) thin films by embedding 10 mol% Ba(Cu 1/3 Nb 2/3 )O 3 (BCN) nano‐clusters into the host BFO film, which originally has a rhombohedral crystal structure. By utilizing nano‐clustering, a large out‐of‐plane coherent strain is localized around the nano‐clusters, resulting in a highly strained tetragonality of the BFO structure; subsequently, the films exhibit peculiar types of domains and domain walls, such as nano‐scale rotational vortices and antiparallel dipole configurations. These peculiar domain structures, which originate from the localized flexoelectric effect at the nano‐scale, enable excellent ferroelectric, ferromagnetic, and RT multiferroic magnetoelectric coupling. This study reveals that the local variation in the localized flexoelectric field around nano‐clusters considerably impacts the formation of unusual domain‐wall structures. This suggests that the controlled introduction of nano‐clusters with different crystal structures is promising for achieving the desired multiferroic properties.

Song, Hyunseok↗

DOE OSTI2022

Probing of Local Structure in Laves Compound TbFe 2

Abstract The Laves compounds Tb 1‐x Dy x Fe 2 have attracted much interest due to the giant magnetostriction effect appearing at their morphotropic phase boundary compositions. Although previous studies have established the relationship between the average structure and magnetostrictive properties in these compounds, there is a lack of characterization of their local structures. In this paper, as a first step toward this goal, the evolution of the local structure of the terminal compound (TbFe 2 ) of this system is reported, in an attempt to provide useful information about interatomic bonding in this system. The pair distribution function (PDF) results suggest that the compound presents the rhombohedral local crystal symmetry. The lattice at the local scale shows abnormal thermal expansion which is different from the long scale structure. The different role of the Tb─Fe bond and Fe─Fe bond in affecting the crystal lattice is revealed. These findings highlight the important role of local structure in determining the magnetostrictive properties of the Laves compounds.

Kou, Ronghui↗

DOE OSTI2023

Reciprocal transplants reveal asymmetric local adaptation of Himalayan Rhododendron approaching elevational range limit

Abstract As plant species expand their upper limits of distribution under current warming, some retain both traditional climate space and biotic environment while others encounter novel conditions. The latter is the case for Rhododendron campanulatum , a woody shrub that grows both above and below treeline at our study site in the Eastern Himalayas where a very conspicuous, stable treeline was defined by a nearly contiguous canopy of tall Abies spectabilis trees, many of which are over a century old. Prior work showed that treeline had remained static in this region while R. campanulatum expanded its elevational range limit. We tested local adaptation of R. campanulatum by performing reciprocal transplants between the species' current elevational range limit (4023 m above sea level [asl]) and just above treeline (3876 m asl). Contrary to expectation, the coldest temperatures of late winter and early mid‐spring were experienced by plants at the lower elevation: R. campanulatum at species' limit (upper site) were covered by snow for a longer period (40 more days) and escaped the coldest temperatures suffered by conspecifics at treeline (lower site). The harsher spring conditions at treeline likely explain why leaves were smaller at treeline (15.3 cm 2 ) than at species limit (21.3 cm 2 ). Contrary to results from equivalent studies in other regions, survival was reduced more by downslope than by upslope movement, again potentially due to extreme cold temperatures observed at treeline in spring. Upslope transplantation had no effect on mortality, but mortality of species limit saplings transplanted downslope was three times higher than that of residents at both sites. A general expectation is that locals should survive better than foreign transplants, but survival of locals and immigrants at our species limit site was identical. However, those species limit saplings that survived the transplant to treeline grew faster than both locals at treeline and the transplants at species limit. Overall, we found asymmetric adaptation: Compared with treeline saplings, those at species limit (147 m above treeline) were more tolerant of extremes in the growing season but less tolerant of extremes in winter and early mid‐spring, displaying local adaptation in a more complex manner than simply home advantage, and complicating predictions about impacts of future regional climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Rhizosphere bacteria containing ACC deaminase decrease root ethylene emission and improve maize root growth with localized nutrient supply

Abstract Localized nutrient supply can enhance maize root proliferation, but also increase root ethylene production. Whether engineering ethylene signalling in the rhizosphere can further enhance root growth and nutrient uptake remains unknown. Here, field and column experiments for maize ( Zea mays . L) were designed as different nutrient treatments (broadcast or localized nutrient supply containing ammonium and phosphorus) with or without inoculation with rhizobacterium Variovorax paradoxus 5C‐2 containing the 1‐aminocyclopropane‐1‐carboxylate (ACC) deaminase. Rhizobacterial inoculation increased shoot biomass by 12% and root length density by 50% with localized nutrient supply. Meanwhile, localized nutrient supply increased root ethylene production by 54% compared with broadcast, and rhizobacterial inoculation prevented the increase in root ethylene. Reduced root ethylene production following V. paradoxus 5C‐2 inoculation was highly associated with a greater proportion of fine root proliferation under localized nutrient supply, which may account for the increased nitrogen and phosphorus uptake. Our work sheds light on the understanding of the interactions between root and microbe through taking hormone into consideration to dissect the relationship between below ground and above ground. It is useful to explore the strategy of soil–crop management by introducing rhizosphere microorganisms to regulate plant ethylene signal and then benefit sustainable agriculture.

Jin, Kemo↗

DOE OSTI2022

A neural network‐enhanced reproducing kernel particle method for modeling strain localization

Abstract Modeling the localized intensive deformation in a damaged solid requires highly refined discretization for accurate prediction, which significantly increases the computational cost. Although adaptive model refinement can be employed for enhanced effectiveness, it is cumbersome for the traditional mesh‐based methods to perform while modeling the evolving localizations. In this work, neural network‐enhanced reproducing kernel particle method (NN‐RKPM) is proposed, where the location, orientation, and shape of the solution transition near a localization is automatically captured by the NN approximation via a block‐level neural network (NN) optimization. The weights and biases in the blocked parameterization network control the location and orientation of the localization. The designed basic four‐kernel NN block is capable of capturing a triple junction or a quadruple junction topological pattern, while more complicated localization topological patters are captured by the superposition of multiple four‐kernel NN blocks. The standard RK approximation is then utilized to approximate the smooth part of the solution, which permits a much coarser discretization than the high‐resolution discretization needed to capture sharp solution transitions with the conventional methods. A regularization of the NN approximation is additionally introduced for discretization‐independent material responses. The effectiveness of the proposed NN‐RKPM is verified by a series of numerical verifications.

Baek, Jonghyuk↗