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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Oxygen aggregation kinetics, thermal donors and carbon-oxygen defect formation in silicon containing carbon and tin

Localized vibrational mode spectroscopy measurements on Czochralski silicon (Cz-Si) samples subjected to isothermal annealing at 450 °C are reported. First, we studied the effect of carbon (C) and tin (Sn) isovalent dopants on the aggregation kinetics of oxygen. It is determined that the reduction rate of oxygen is described by the Johnson-Mehl-Avrami equation in accordance with previous reports. The activation energy related with the reaction rate constant of the process is calculated to increase from Cz-Si, to C-doped Cz-Si (CCz-Si), to Sn-doped Cz-Si contained C (SnCz-Si). This is attributed to the presence of the isovalent dopants that may impact both the kinetics of the oxygen atoms and also may lead to the formation of other oxygen-related clusters. Second, we studied the effect of Sn on the formation and evolution of carbon-oxygen (C-O) defects. It was determined that the presence of Sn suppresses the formation of the C-O defects as indicated by the reduction in the strength of the 683, 626, and 586 cm{sup −1} well-known bands of C{sub s}O{sub i} defect. The phenomenon is attributed to the association of Sn with C atoms that may prevent the pairing of O with C. Third, we investigated the effect of C and Sn on the formation of thermal donors (TDs). Regarding carbon our results verified previous reports that carbon suppresses the formation of TDs. Interestingly, when both C and Sn are present in Si, very weak bands of TDs were observed, although it is known that Sn alone suppress their formation. This may be attributed to the competing strains of C and Sn in the Si lattice.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

A general ansatz for constructing quasi-diabatic states in electronically excited aggregated systems

We present a general method for analyzing the character of singly excited states in terms of charge transfer (CT) and locally excited (LE) configurations. The analysis is formulated for configuration interaction singles (CIS) singly excited wave functions of aggregate systems. It also approximately works for the second-order approximate coupled cluster singles and doubles and the second-order algebraic-diagrammatic construction methods [CC2 and ADC(2)]. The analysis method not only generates a weight of each character for an excited state, but also allows to define the related quasi-diabatic states and corresponding coupling matrix elements. In the character analysis approach, we divide the target system into domains and use a modified Pipek-Mezey algorithm to localize the canonical MOs on each domain, respectively. The CIS wavefunction is then transformed into the localized basis, which allows us to partition the wavefunction into LE configurations within domains and CT configuration between pairs of different domains. Quasi-diabatic states are then obtained by mixing excited states subject to the condition of maximizing the weight of one single LE or CT configuration (localization in configuration space). Different aims of such a procedure are discussed, either the construction of pure LE and CT states for analysis purposes (by including a large number of excited states) or the construction of effective models for dynamics calculations (by including a restricted number of excited states). Applications are given to LE/CT mixing in π-stacked systems, charge-recombination matrix elements in a hetero-dimer, and excitonic couplings in multi-chromophoric systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Computational molecular technology towards macroscopic chemical phenomena-molecular control of complex chemical reactions, stereospecificity and aggregate structures

A new efficient hybrid Monte Carlo (MC)/molecular dynamics (MD) reaction method with a rare event-driving mechanism is introduced as a practical ‘atomistic’ molecular simulation of large-scale chemically reactive systems. Starting its demonstrative application to the racemization reaction of (R)-2-chlorobutane in N,N-dimethylformamide solution, several other applications are shown from the practical viewpoint of molecular controlling of complex chemical reactions, stereochemistry and aggregate structures. Finally, I would like to mention the future applications of the hybrid MC/MD reaction method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Reinforcement learning based hybrid bond-order coarse-grained interatomic potentials for exploring mesoscale aggregation in liquid–liquid mixtures

Exploring mesoscopic physical phenomena has always been a challenge for brute-force all-atom molecular dynamics simulations. Although recent advances in computing hardware have improved the accessible length scales, reaching mesoscopic timescales is still a significant bottleneck. Coarse-graining of all-atom models allows robust investigation of mesoscale physics with a reduced spatial and temporal resolution but preserves desired structural features of molecules, unlike continuum-based methods. Here, we present a hybrid bond-order coarse-grained forcefield (HyCG) for modeling mesoscale aggregation phenomena in liquid–liquid mixtures. The intuitive hybrid functional form of the potential offers interpretability to our model, unlike many machine learning based interatomic potentials. We parameterize the potential with the continuous action Monte Carlo Tree Search (cMCTS) algorithm, a reinforcement learning (RL) based global optimizing scheme, using training data from all-atom simulations. The resulting RL-HyCG correctly describes mesoscale critical fluctuations in binary liquid–liquid extraction systems. cMCTS, the RL algorithm, accurately captures the mean behavior of various geometrical properties of the molecule of interest, which were excluded from the training set. The developed potential model along with the RL-based training workflow could be applied to explore a variety of other mesoscale physical phenomena that are typically inaccessible to all-atom molecular dynamics simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

Measurement of interaction forces between red blood cells in aggregates by optical tweezers

We have fabricated double-beam optical tweezers and demonstrated the possibility of their use for measuring the interaction forces between red blood cells (erythrocytes). It has been established experimentally that prolonged trapping of red blood cells in a tightly focused laser beam does not cause any visible changes in their shape or size. We have measured the interaction between red blood cells in the aggregate, deformed by optical tweezers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Effects of near-field electromagnetic coupling in dimers of nanoparticles with a silver core and a J-aggregate dye shell

We report a theoretical study of the plasmon-exciton coupling effect on the absorption spectra of pairs of closely spaced double-layer hybrid nanoparticles consisting of a metallic core and a J-aggregate dye shell. The effect of frequency conversion of plasmonic lines due to the near-field interaction between plasmons and Frenkel excitons of the organic shell is demonstrated. The effect leads to the appearance of additional spectral lines in the long-wavelength part of the spectrum of the system of hybrid particles. The shapes and the relative intensities of the additional lines exactly reproduce the specific features of the original spectrum of plasmonic absorption bands in uncoated metallic nanoparticles. The discovered phenomenon can be used to design new types of high-sensitivity nanosensors, based on plasmon-exciton effects and principles of near-field optics. (nanophotonics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

From aggregative adsorption to surface depletion: Aqueous systems of C n E m amphiphiles at hydrophilic surfaces

Adsorption of a short-chain nonionic amphiphile (C 6 E 3 ) at the surface of mesoporous silica glass (CPG-10) was studied by a combination of adsorption measurements and mesoscale simulations. Adsorption measurements covering a wide composition range of the C 6 E 3 + water system show that no adsorption occurs up to the critical micelle concentration (cmc), at which a sharp increase of adsorption is observed that is attributed to ad-micelle formation at the pore walls. Intriguingly, as the concentration is increased further, the surface excess of the amphiphile begins to decrease and eventually becomes negative, which corresponds to preferential adsorption of water rather than amphiphile at high amphiphile concentrations. The existence of such a surface-azeotropic point has not previously been reported in the surfactant adsorption field. Dissipative particle dynamics (DPD) simulations were performed to reveal the structural origin of this transition from aggregative adsorption to surface depletion. Finally, the simulations indicate that this transition can be attributed to the repulsive interaction between head groups, causing amphiphilic depletion in the region around the corona of the surface micelles.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Rotation-dependent catastrophic disruption of gravitational aggregates

We carry out a systematic exploration of the effect of pre-impact rotation on the outcomes of low-speed collisions between planetesimals modeled as gravitational aggregates. We use pkdgrav, a cosmology code adapted to collisional problems and recently enhanced with a new soft-sphere collision algorithm that includes more realistic contact forces. A rotating body has lower effective surface gravity than a non-rotating one and therefore might suffer more mass loss as the result of a collision. What is less well understood, however, is whether rotation systematically increases mass loss on average regardless of the impact trajectory. This has important implications for the efficiency of planet formation via planetesimal growth, and also more generally for the determination of the impact energy threshold for catastrophic disruption (leading to the largest remnant retaining 50% of the original mass), as this has generally only been evaluated for non-spinning bodies. We find that for most collision scenarios, rotation lowers the threshold energy for catastrophic dispersal. For head-on collisions, we develop a semi-analytic description of the change in the threshold description as a function of the target's pre-impact rotation rate, and find that these results are consistent with the 'universal law' of catastrophic disruption developed by Leinhardt and Stewart. Using this approach, we introduce re-scaled catastrophic disruption variables that take into account the interacting mass fraction of the target and the projectile in order to translate oblique impacts into equivalent head-on collisions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Increasing aggregate size reduces single-cell organic carbon incorporation by hydrogel-embedded wetland microbes

Abstract Microbial degradation of organic carbon in sediments is impacted by the availability of oxygen and substrates for growth. To better understand how particle size and redox zonation impact microbial organic carbon incorporation, techniques that maintain spatial information are necessary to quantify elemental cycling at the microscale. In this study, we produced hydrogel microspheres of various diameters (100, 250, and 500 μm) and inoculated them with an aerobic heterotrophic bacterium isolated from a freshwater wetland (Flavobacterium sp.), and in a second experiment with a microbial community from an urban lacustrine wetland. The hydrogel-embedded microbial populations were incubated with 13C-labeled substrates to quantify organic carbon incorporation into biomass via nanoSIMS. Additionally, luminescent nanosensors enabled spatially explicit measurements of oxygen concentrations inside the microspheres. The experimental data were then incorporated into a reactive-transport model to project long-term steady-state conditions. Smaller (100 μm) particles exhibited the highest microbial cell-specific growth per volume, but also showed higher absolute activity near the surface compared to the larger particles (250 and 500 μm). The experimental results and computational models demonstrate that organic carbon availability was not high enough to allow steep oxygen gradients and as a result, all particle sizes remained well-oxygenated. Our study provides a foundational framework for future studies investigating spatially dependent microbial activity in aggregates using isotopically labeled substrates to quantify growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Ferrous iron formation following the co-aggregation of ferric iron and the Alzheimer's disease peptide β-amyloid (1–42)

For decades, a link between increased levels of iron and areas of Alzheimer’s disease (AD) pathology has been recognized, including AD lesions comprised of the peptide b-amyloid (Ab). Despite many observations of this association, the relationship between Ab and iron is poorly understood. Using X-ray microspectroscopy, X-ray absorption spectroscopy, electron microscopy and spectrophotometric iron(II) quantification techniques, we examine the interaction between Ab(1–42) and synthetic iron(III), reminiscent of ferric iron stores in the brain. We report Ab to be capable of accumulating iron(III) within amyloid aggregates, with this process resulting in Ab-mediated reduction of iron(III) to a redox-active iron(II) phase. Additionally, we show that the presence of aluminium increases the reductive capacity of Ab, enabling the redox cycling of the iron. These results demonstrate the ability of Ab to accumulate iron, offering an explanation for previously observed local increases in iron concentration associated with AD lesions. Furthermore, the ability of iron to form redox-active iron phases from ferric precursors provides an origin both for the redox-active iron previously witnessed in AD tissue, and the increased levels of oxidative stress characteristic of AD. These interactions between Ab and iron deliver valuable insights into the process of AD progression, which may ultimately provide targets for disease therapies.

redox↗
DOE OSTI2026

Dehydration-Driven Ion Aggregation and the Onset of Gelation in ZnCl2 Solution

A minimal model of ionic aggregation in concentrated ZnCl2 is developed, guided by molecular dynamics simulations with a machine-learned potential. It explicitly incorporates solvent-site depletion, correlated chloride binding, and allows for loops within Zn–Cl clusters. Dehydration drives two coordination-controlled structural changes: a crossover at Z=2 from predominantly isolated Zn-containing species to Cl-bridged clusters and the onset of gelation near Z≈3. The model reproduces the concentration-dependent trends observed in the molecular dynamics simulations with two fitted parameters, while the cluster-size distribution at the highest concentration is consistent with three-dimensional percolation scaling over the accessible range of cluster sizes.

25 ENERGY STORAGE↗
DOE OSTI2017

Aggregation-fragmentation-diffusion model for trail dynamics

We investigate statistical properties of trails formed by a random process incorporating aggregation, fragmentation, and diffusion. In this stochastic process, which takes place in one spatial dimension, two neighboring trails may combine to form a larger one, and also one trail may split into two. In addition, trails move diffusively. The model is defined by two parameters which quantify the fragmentation rate and the fragment size. In the long-time limit, the system reaches a steady state, and our focus is the limiting distribution of trail weights. We find that the density of trail weight has power-law tail P(w)~w –γ for small weight w. We obtain the exponent γ analytically and find that it varies continuously with the two model parameters. In conclusion, the exponent γ can be positive or negative, so that in one range of parameters small-weight trails are abundant and in the complementary range they are rare.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2011

Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

Kalsi, Karanjit↗
DOE OSTI2016

Multilayer spectral graph clustering via convex layer aggregation

Multilayer graphs are commonly used for representing different relations between entities and handling heterogeneous data processing tasks. New challenges arise in multilayer graph clustering for assigning clusters to a common multilayer node set and for combining information from each layer. This paper presents a theoretical framework for multilayer spectral graph clustering of the nodes via convex layer aggregation. Under a novel multilayer signal plus noise model, we provide a phase transition analysis that establishes the existence of a critical value on the noise level that permits reliable cluster separation. The analysis also specifies analytical upper and lower bounds on the critical value, where the bounds become exact when the clusters have identical sizes. Numerical experiments on synthetic multilayer graphs are conducted to validate the phase transition analysis and study the effect of layer weights and noise levels on clustering reliability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claims are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Game-Theoretic Approach for Electricity Pricing Between Distribution System Operator and Load Aggregators

Transactive energy has emerged and gained more and more attention in recent years along with smart grid two-way communication technologies. Electricity pricing strategies play a critical role in influencing and shaping the customers’ energy load profile. In this paper, we investigate the electricity pricing strategy between a distribution system operator (DSO) and load aggregators (LAs) by adopting a bi-level Stackelberg game approach. With the purpose of maximizing its own operating revenue as well as better serving its customers, the upper level DSO will determine the price considering how lower level LAs will respond to it. Peak-to-average ratio of the total demand is modeled as a constraint and peak load is penalized at the upper optimization level. Classical backward induction is used to obtain a Nash equilibrium for the formulated bi-level Stackelberg game. Numerical results demonstrate the effectiveness of the proposed game approach in leveraging flexible demand potential to benefit both DSO and LAs.

Chen, Yang↗
DOE OSTI2025

HexWeather: Hexagonal Spatial Data Aggregation for Weather-Driven Grid Resilience Analysis

Extreme weather accounts for over 8 0 % of major U.S. power outages since 2000, highlighting the need for spatial tools that align weather data with the irregular boundaries of electric infrastructure. This paper introduces HexWeather, a modular, resolution-aware framework for aggregating historical and forecasted weather data using Uber's H3 hexagonal spatial indexing system. Unlike traditional methods that rely on state or county-level grids, HexWeather enables weather analysis across custom geographies such as utility service areas where public datasets are often unavailable or misaligned. Using Open-Meteo data, we evaluate how H3 resolution affects anomaly detection, spatial variability, and forecast uncertainty across three scales: state, county, and utility. Results show that while coarse resolutions suffice for broad trend tracking, finer resolutions are essential for identifying localized variability and operational risks. By applying metrics like Z-score standard deviation and interquartile range, HexWeather quantifies the spatial spread of both historical anomalies and forecasted conditions, allowing users to assess resolution adequacy for each analysis. This framework supports rapid weather data reuse, reproducible anomaly detection, and predictive modeling for infrastructure resilience. By bridging spatial misalignment in traditional datasets and enabling retrospective and forward-looking analysis within the same pipeline, HexWeather lays the groundwork for better post event analysis, outage prediction, and resilience planning.

Morris, Jacob [ORNL]↗
DOE OSTI2013

Modeling and Control of Aggregated Air Conditioning Loads Under Realistic Conditions

Demand-side control is playing an increasingly important role in smart grid control strategies. Modeling the dynamical behavior of a large population of appliances is especially important to evaluate the effectiveness of various load control strategies. In this paper, a high accuracy aggregated model is first developed for a population of HVAC units. The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. Furthermore, the model takes into account the lockout effect of the compressor in order to represent the dynamics of the system under control more accurately. Then, a novel closed loop load control strategy is designed to track a desired demand curve and to ensure a stable and smooth response.

Chang, Chin-Yao↗