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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Anomaly detection for cyber-physical systems

An anomaly detector is configured to construct cyber and/or physical features comprising information configured to characterize the cyber and/or physical state of a cyber-physical system. The physical features may be based on physical and/or physics-based relationships between a plurality of physical state attributes. A health of the cyber-physical system may be based on an error between estimates of one or more of the physical state attributes and measurements of the one or more physical state attributes. The relationships may be incorporated into machine learning membership functions used to classify cyber and/or physical behavior of the system.

Rieger, Craig G.↗
DOE OSTI2026

Are the U.S. Biorefineries Over the Hurdle of 2000 Ton Daily Throughput Yet?

The efficient utilization of lignocellulosic biomass for biofuel and biochemical production is hindered by material handling issues such as clogging and segregation among other challenges. Preprocessing methods such as drying, screening, and milling have improved conversion yield but have not sufficiently enhanced flowability, especially herbaceous biomass. The poor flowability of herbaceous biomass is rooted in some particle attributes that remain less altered by those methods, e.g., irregular particle shape, high roughness, and high compressibility, making it hard to scale up throughput to a key benchmark for a biorefinery – 2000 ton per day. Applying additional preprocessing methods like pelletization and torrefaction to drastically change those particle attributes can improve flow and handling but has not been comprehensively verified through test. The flowability of herbaceous biomass feedstock formats generated by three different preprocessing methods was recently assessed at Idaho National Laboratory’s Biomass Feedstock National User Facility: first, loose particles size reduced from as-received materials; second, pellets produced from an efficient densification process; and third, powders milled from torrefied pellets. Benchmarking tests including static angle of repose, basic flow energy measured in a powder rheometer, and discharge flow in an adjustable hopper, were conducted to evaluate those feedstock formats. Beyond the capacity of existing experimental apparatuses, a digital engineering approach involving flow simulations and AI models were used to identity the material attributes and processing parameters that have dominant influences on flow throughput. Techno-economic analysis focusing on hopper flow as a typical material handling operation was conducted for those feedstock formats. Perspectives will be discussed on whether the 2000-ton daily throughput for a biorefinery is achievable at an acceptable cost by using any of the tested preprocessing methods.

09 - BIOMASS FUELS↗
DOE OSTI2024

The Effect of Air Separations on Fast Pyrolysis Products for Forest Residue Feedstocks

This study investigates the intricate relationship between biomass preprocessing and pyrolysis product yields, employing the air classification technique for the treatment of loblolly pine residues with varying moisture content. A comprehensive exploration of the physicochemical properties of air-classified loblolly pine informs a sophisticated pyrolysis simulation model. Given the complex and multifaceted nature of biomass pyrolysis, operating across diverse temporal and spatial scales, a pyrolysis kinetics-based CFD–DEM simulation method is employed to predict product yields. Results showed that the elevated moisture content amplifies particle adhesiveness, necessitating augmented air velocities for effective separation, thereby influencing the efficiency of the separation process. While carbon and hydrogen contents exhibit relative stability across diverse moisture contents and blower frequencies, the oxygen content undergoes noticeable changes. For example, the oxygen contents were measured as 29.2 and 38.6 wt% in the light fraction of 30% moisture content sample at blower frequencies of 10 and 20 Hz, respectively. An intriguing finding emerges from pyrolysis simulation, indicating that a lower blower frequency in air classification moderately enhances bio-oil yield and significantly improves its quality, particularly in terms of water content. For instance, the water content in the bio-oil was about 1.5% and 10% in the heavy and light fractions, respectively from 10% moisture sample under 15 Hz blower frequency. In summary, a detailed understanding and strategic manipulation of critical material attributes in biomass through efficient fractionation techniques are imperative for advancing fast pyrolysis as a sustainable avenue for renewable energy and chemical production.

09 BIOMASS FUELS↗
DOE OSTI2021

On the Emergence of Human Influence on Surface Air Temperature Changes Over India

Human activities in terms of greenhouse gas (GHG) emissions and aerosols resulting from the combustion of fossil fuels have been shown to have affected the temperature of the Earth on global and continental scales. The surface air temperature (TAS) over India has also been observed to be increasing over the last 100 years. Understanding the underlying causes of regional climate change over India can help in developing appropriate mitigation and adaptation strategies. Differentiating signals of externally forced climate changes from the noise of natural internal variability generally becomes more difficult as spatial scale reduces. Therefore detecting and attributing the influence of external forcings such as GHGs and aerosols is harder at local and regional scales. In this study, we applied a detection and attribution (D&A) method to study annual and seasonal mean TAS over the Indian region. We found that the observed warming over India from 1906 to 2005 cannot be explained by natural climate variability alone. We found that the warming is largely driven by the increase in GHGs, and partially offset by regional anthropogenic emissions of aerosols. These results were confirmed for the shorter 1956–2005 period, but results were sensitive to the choice of observational data set. Furthermore, the changes cannot be explained by internal climate variability or natural external forcings alone, but are compatible with the responses to combined anthropogenic GHG and aerosol forcings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Little influence of Arctic amplification on mid-latitude climate

Observations and model simulations show enhanced warming in the Arctic under increasing greenhouse gases, a phenomenon known as the Arctic amplification (AA), that is likely caused by sea-ice loss. AA reduces meridional temperature gradients linked to circulation, thus mid-latitude weather and climate changes have been attributed to AA, often on the basis of regression analysis and atmospheric simulations. However, other modelling studies show only a weak link. This inconsistency may result from deficiencies in separating the effects of AA from those of natural variability or background warming. In this work, using coupled model simulations with and without AA, we show that cold-season precipitation, snowfall and circulation changes over northern mid-latitudes come mostly from background warming. AA and sea-ice loss increase precipitation and snowfall above ~60° N and reduce meridional temperature gradients above ~45° N in the lower–mid troposphere. However, minimal impact on the mean climate is seen below ~60° N, with weak reduction in zonal wind over 50°–70° N and 150–700 hPa, mainly over the North Atlantic and northern central Asia. These results suggest that the climatic impacts of AA are probably small outside the high latitudes, thus caution is needed in attributing mid-latitude changes to AA and sea-ice loss on the basis of statistical analyses that cannot distinguish the impact of AA from other correlated changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

GrAMME: Semisupervised Learning Using Multilayered Graph Attention Models

Modern data analysis pipelines are becoming increasingly complex due to the presence of multiview information sources. While graphs are effective in modeling complex relationships, in many scenarios, a single graph is rarely sufficient to succinctly represent all interactions, and hence, multilayered graphs have become popular. Though this leads to richer representations, extending solutions from the single-graph case is not straightforward. Consequently, there is a strong need for novel solutions to solve classical problems, such as node classification, in the multilayered case. In this article, we consider the problem of semisupervised learning with multilayered graphs. Though deep network embeddings, e.g., DeepWalk, are widely adopted for community discovery, we argue that feature learning with random node attributes, using graph neural networks, can be more effective. To this end, we propose to use attention models for effective feature learning and develop two novel architectures, GrAMME-SG and GrAMME-Fusion, that exploit the interlayer dependences for building multilayered graph embeddings. Using empirical studies on several benchmark data sets, we evaluate the proposed approaches and demonstrate significant performance improvements in comparison with the state-of-the-art network embedding strategies. The results also show that using simple random features is an effective choice, even in cases where explicit node attributes are not available.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analyzing Potential Failures and Effects in a Pilot-Scale Biomass Preprocessing Facility for Improved Reliability

This study demonstrates a failure identification methodology applied to a preprocessing facility generating conversion-ready feedstocks from biomass meeting conversion process critical quality attribute (CQA) specifications. Failure Modes and Effects Analysis (FMEA) was used as an industrially relevant risk analysis approach to evaluate a logging residue preprocessing system to prepare feedstock for pyrolysis conversion. Risk evaluations considered both system-level and operation unit-level assessments considering process efficiency, product quality, cost, sustainability, and safety. Key outputs included estimations of semi-quantitative risk scores for each failure, identification of the failure impacts, identification of failure causes associated with material attributes and process parameters, ranking success rates of failure detection methods, and speculation of potential mitigation strategies for decreasing failure risk scores. Results showed that deviations from moisture specifications had cascading consequences for other CQAs along with process safety implications. Failures linked to fixed carbon specifications carried the highest risk scores for product quality and process efficiency impacts. As increased throughput can be inversely related to meeting product quality specifications; achieving throughput and other material-based CQAs simultaneously will likely require system optimization or prioritization based on system economics. Ultimately, this work successfully demonstrates FMEA as a risk analysis approach for other bioenergy process systems.

09 BIOMASS FUELS↗
DOE OSTI2024

Effect of Zn Addition on Phase Evolution in AlCrFeCoNiZn High–Entropy Alloy

The addition of Zn to AlCrFeCoNi high-entropy alloy (HEA) poses intriguing questions as to how it would affect phase evolution. Herein, the phase evolution in AlCrFeCoNiZn is studied using a combination of experimental techniques (X-ray diffraction, scanning electron microscopy, energy-dispersive spectroscopy, and differential scanning calorimetry) and computational (density-functional theory [DFT], calculation of phase diagrams, and machine-learning) methods. Mechanically alloyed and spark-plasma-sintered AlCrFeCoNiZn assumes a metastable single-phase, body-centered-cubic (BCC) structure that undergoes diffusion-controlled phase separation upon subsequent heat treatment to form separate (Al, Cr)-rich, (Fe, Co)-rich, and (Zn, Ni)-rich phases. The formation of (Al, Cr)-rich phase, not reported previously in AlCrFeCoNi-based HEAs, is attributed to strong clustering tendency of Cr–Zn and Cr–Ni pairs, combined with the strong ordering of Zn–Ni pair, driving out Cr that in turn combines with Al to form a (Al, Cr)-rich phase. In the DFT results, the formation of thermodynamically stable L1 2 phase is shown wherein Cr–Fe–Zn [Al–Ni-Co] preferably occupy1a (000) [3c (0 ½ ½)] positions. Furthermore, the sluggish diffusional transformation to L1 2 phase from BCC precursors is attributed to the small stacking-fault energy of AlCrFeCoNiZn. The equilibrated HEA exhibits a high microhardness of 8.24 GPa with an elastic modulus of 184 GPa.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Direct Observation of Bandgap Oscillations Induced by Optical Phonons in Hybrid Lead Iodi.de Perovskites

Hybrid organic-inorganic perovskites such as methylammonium lead iodide have emerged as promising semiconductors for energy-relevant applications. The interactions between charge carriers and lattice vibrations, giving rise to polarons, have been invoked to explain some of their extraordinary optoelectronic properties. Here, time-resolved optical spectroscopy is performed, with off-resonant pumping and electronic probing, to examine several representative lead iodide perovskites. The temporal oscillations of electronic bandgaps induced by coherent lattice vibrations are reported, which is attributed to antiphase octahedral rotations that dominate in the examined 3D and 2D hybrid perovskites. The off-resonant pumping scheme permits a simplified observation of changes in the bandgap owing to the A(g) vibrational mode, which is qualitatively different from vibrational modes of other symmetries and without increased complexity of photogenerated electronic charges. The work demonstrates a strong correlation between the lead-iodide octahedral framework and electronic transitions, and provides further insights into the manipulation of coherent optical phonons and related properties in hybrid perovskites on ultrafast timescales.

coherent optical phonons↗
DOE OSTI2020

Excellent cycling stability of sodium anode enabled by a stable solid electrolyte interphase formed in ether-based electrolytes

Sodium (Na)-ion batteries have been considered as one of the most promising power sources beyond Li-ion batteries. Although Na metal anode exhibits a high theoretical capacity of 1165 mAh g-1, its application on Na batteries is largely hindered by dendrite growth and low Coulombic efficiency. Herein, we demonstrate that an electrolyte consists of 1 M sodium tetrafluoroborate in Tetraglyme can enable excellent cycling efficiency (99.9 %) of Na metal anode for more than 1000 cycles. This high reversibility of Na anode can be attributed to a stable solid electrolyte interphase formed on Na surface as revealed by cryogenic transmission electron microscopy and X-ray photoelectron spectroscopy. These electrolytes also enabled excellent cycling stability of Na||hard carbon cells and Na||Na2/3Co1/3Mn2/3O2 cells at high rate with very high coulombic efficiencies.

sodium metal, TEGDME, solid electrolyte interphase↗
DOE OSTI2022

Atomically Precise Single Metal Oxide Cluster Catalyst with Oxygen–Controlled Activity

Single cluster catalysts (SCCs) consisting of atomically precise metal nanoclusters dispersed on supports represent a new frontier of heterogeneous catalysis. However, the ability to synthesize SCCs with high loading and to precisely introduce non-metal atoms to further tune their catalytic activity and reaction scope of SCCs have been longstanding challenges. In this work, a new interface confinement strategy is developed for the synthesis of a high density of atomically precise Ru oxide nanoclusters (Ru 3 O 2 ) on reduced graphene oxide (rGO), attributed to the suppression of diffusion-induced metal cluster aggregation. Ru 3 O 2 /rGO exhibits a significantly enhanced activity for oxidative dehydrogenation of 1,2,3,4-tetrahydroquinoline (THQ) to quinoline with a high yield (≈86%) and selectivity (≈99%), superior to Ru and RuO 2 nanoparticles, and homogeneous single/multiple-site Ru catalysts. In addition, Ru 3 O 2 /rGO is also capable of efficiently catalyzing more complex oxidative reactions involving three reactants. The theoretical calculations reveal that the presence of two oxygen atoms in the Ru 3 O 2 motif not only leads to a weak hydrogen bonding interaction between the THQ reactant and the active site, but also dramatically depletes the density of states near the Fermi level, which is attributed to the increased positive valence state of Ru and the enhanced oxidative activity of the Ru 3 O 2 cluster for hydrogen abstraction.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tuning Surface Acidity of Mixed Conducting Electrodes: Recovery of Si‐Induced Degradation of Oxygen Exchange Rate and Area Specific Resistance

Abstract Metal oxides are an important class of functional materials, and for many applications, ranging from solid oxide fuel/electrolysis cells, oxygen permeation membranes, and oxygen storage materials to gas sensors (semiconducting and electrolytic) and catalysts, the interaction between the surface and oxygen in the gas phase is central. Ubiquitous Si‐impurities are known to impede this interaction, commonly attributed to the formation of glassy blocking layers on the surface. Here, the surface oxygen exchange coefficient ( k chem ) is examined for Pr 0.1 Ce 0.9 O 2‐δ (PCO), a model mixed ionic electronic conductor, via electrical conductivity relaxation measurements, and the area‐specific resistance (ASR) by electrochemical impedance spectroscopy. It is demonstrated that even low silica levels, introduced by infiltration, depress k chem by a factor 4000, while the ASR increases 40‐fold and we attribute this to its acidity relative to that of PCO. The ability to fully regenerate the poisoned surface by the subsequent addition of basic Ca‐ or Li‐species is further shown. This ability to not only recover Si‐poisoned surfaces by tuning the relative surface acidity of an oxide surface, but subsequently outperform the pre‐poisoned response, promises to extend the operating life of materials and devices for which the catalytic oxygen/solid interface reaction is central.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Identification and Suppression of Point Defects in Bromide Perovskite Single Crystals Enabling Gamma‐Ray Spectroscopy

Abstract Methylammonium lead tribromide (MAPbBr 3 ) stands out as the most easily grown wide‐band‐gap metal halide perovskite. It is a promising semiconductor for room‐temperature gamma‐ray ( γ ‐ray) spectroscopic detectors, but no operational devices are realized. This can be largely attributed to a lack of understanding of point defects and their influence on detector performance. Here, through a combination of crystal growth design and defect characterization, including positron annihilation and impedance spectroscopy, the presence of specific point defects are identified and correlated to detector performance. Methylammonium (MA) vacancies, MA interstitials, and Pb vacancies are identified as the dominant charge‐trapping defects in MAPbBr 3 crystals, while Br vacancies caused doping. The addition of excess MABr reduces the MA and Br defects and so enables the detection of energy‐resolved γ ‐ray spectra using a MAPbBr 3 single‐crystal device. Interestingly, the addition of formamidinium (FA) cations, which converted to methylformamidinium (MFA) cations by reaction with MA + during crystal growth further reduced MA defects. This enabled an energy resolution of 3.9% for the 662 keV 137 Cs line using a low bias of 100 V. The work provides direction toward enabling further improvements in wide‐bandgap perovskite‐based device performance by reducing detrimental defects.

Ni, Zhenyi↗
DOE OSTI2023

Ultrasensitive Room Temperature Infrared Photodetection Using a Narrow Bandgap Conjugated Polymer

Abstract Photodetectors operating across the short‐, mid‐, and long‐wave infrared (SWIR–LWIR, λ = 1–14 µm) underpin modern science, technology, and society in profound ways. Narrow bandgap semiconductors that form the basis for these devices require complex manufacturing, high costs, cooling, and lack compatibility with silicon electronics, attributes that remain prohibitive for their widespread usage and the development of emerging technologies. Here, a photoconductive detector, fabricated using a solution‐processed narrow bandgap conjugated polymer is demonstrated that enables charge carrier generation in the infrared and ultrasensitive SWIR–LWIR photodetection at room temperature. Devices demonstrate an ultralow electronic noise that enables outstanding performance from a simple, monolithic device enabling a high detectivity ( D *, the figure of merit for detector sensitivity) >2.44 × 10 9 Jones (cm Hz 1/2 W −1 ) using the ultralow flux of a blackbody that mirrors the background emission of objects. These attributes, ease of fabrication, low dark current characteristics, and highly sensitive operation overcome major limitations inherent within modern narrow–bandgap semiconductors, demonstrate practical utility, and suggest that uncooled detectivities superior to many inorganic devices can be achieved at high operating temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Transition Metal Dichalcogenides: Making Atomic‐Level Magnetism Tunable with Light at Room Temperature

Abstract The capacity to manipulate magnetization in 2D dilute magnetic semiconductors (2D‐DMSs) using light, specifically in magnetically doped transition metal dichalcogenide (TMD) monolayers ( M ‐doped TX 2 , where M = V, Fe, and Cr; T = W, Mo; X = S, Se, and Te), may lead to innovative applications in spintronics, spin‐caloritronics, valleytronics, and quantum computation. This Perspective paper explores the mediation of magnetization by light under ambient conditions in 2D‐TMD DMSs and heterostructures. By combining magneto‐LC resonance (MLCR) experiments with density functional theory (DFT) calculations, we show that the magnetization can be enhanced using light in V‐doped TMD monolayers (e.g., V‐WS 2 , V‐WSe 2 ). This phenomenon is attributed to excess holes in the conduction and valence bands, and carriers trapped in magnetic doping states, mediating the magnetization of the semiconducting layer. In 2D‐TMD heterostructures (VSe 2 /WS 2 , VSe 2 /MoS 2 ), the significance of proximity, charge‐transfer, and confinement effects in amplifying light‐mediated magnetism is demonstrated. We attributed this to photon absorption at the TMD layer that generates electron–hole pairs mediating the magnetization of the heterostructure. These findings will encourage further research in the field of 2D magnetism and establish a novel design of 2D‐TMDs and heterostructures with optically tunable magnetic functionalities, paving the way for next‐generation magneto‐optic nanodevices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Elucidate the Thermal Degradation Mechanism of Y6‐Based Organic Solar Cells by Establishing Structure‐Property Correlation

Abstract Organic solar cells (OSCs) achieved performance booming benefiting from the emerging of non‐fullerene acceptors, while inadequate device stability hampers their further application. At present, the prevalent belief attributes the inevitable thermal degradation of OSC device to morphological instability caused by excessive phase separation and crystallization in the active layer during device operation. However, it is inapplicable for state‐of‐art Y6‐based devices which strongly degrade before large‐scale morphology change. Herein, an alternative degradation mechanism is elucidated wherein molecular orientation change and demixing induced performance degradation in Y6‐based devices. Distinct from IT‐4F‐based counterpart, Y6‐based devices suffer severe thermal degradation dominated by open‐circuit voltage (V OC ) and fill factor (FF) losses. TheV OC loss is attributed to molecular orientation transition of polymer donors from edge‐on to face‐on, leading to a strong built‐in potential reduction and increase in non‐radiative loss due to energy level shifting. As forFFdecay, discontinuous acceptor phases result in electron mobility decrease by over orders of magnitude, originating from the increased molecular stacking and phase separation. This work reveals the thermal degradation mechanism for Y6‐based devices and correlates the photoelectric properties with morphology instability, which will offer guidance for improving the stability of high‐performance OSCs.

Chemistry↗
DOE OSTI2020

A Self‐Consistent Model for Sorption and Transport in Polyimide‐Derived Carbon Molecular Sieve Gas Separation Membranes

Abstract Demand for energy‐efficient gas separations exists across many industrial processes, and membranes can aid in meeting this demand. Carbon molecular sieve (CMS) membranes show exceptional separation performance and scalable processing attributes attractive for important, similar‐sized gas pairs. Herein, we outline a mathematical and physical framework to understand these attributes. This framework shares features with dual‐mode transport theory for glassy polymers; however, physical connections to CMS model parameters differ from glassy polymer cases. We present evidence in CMS membranes for a large volume fraction of microporous domains characterized by Langmuir sorption in local equilibrium with a minority continuous phase described by Henry's law sorption. Using this framework, expressions are provided to relate measurable parameters for sorption and transport in CMS materials. We also outline a mechanism for formation of these environments and suggest future model refinements.

Sanyal, Oishi↗