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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry

Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A State-Space Model of an Inverter-Based Microgrid for Multivariable Feedback Control Analysis and Design

In this work, a synchronous model for grid-connected and islanded microgrids is presented. The grid-connected model is based on the premise that the reference frame is synchronized with the AC bus. The quadrature component of the AC bus voltage can be cancelled, which allows to express output power as a linear equation for nominal values in the AC bus amplitude voltage. The model for the islanded microgrid is developed by integrating all the inverter dynamics using a state-space model for the load currents. This model is presented in a comprehensive way such that it could be scalable to any number of inverter-based generators using inductor–capacitor–inductor (LCL) output filters. The use of these models allows designers to assess microgrid stability and robustness using modern control methods such as eigenvalue analysis and singular value diagrams. Both models were tested and validated in an experimental setup to demonstrate their accuracy in describing microgrid dynamics. In addition, three scenarios are presented: non-controlled model, Linear-Quadratic Integrator (LQI) power control, and Power-Voltage (PQ/Vdq) droop–boost controller. Experimental results demonstrate the effectiveness of the control strategies and the accuracy of the models to describe microgrid dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Current and Future γ-Ray Searches for Dark Matter Annihilation Beyond the Unitarity Limit

For decades, searches for electroweak-scale dark matter (DM) have been performed without a definitive detection. This lack of success may hint that DM searches have focused on the wrong mass range. A proposed candidate beyond the canonical parameter space is ultraheavy DM (UHDM). In this work, we consider indirect UHDM annihilation searches for masses between 30 TeV and 30 PeV—extending well beyond the unitarity limit at ~100 TeV—and discuss the basic requirements for DM models in this regime. We explore the feasibility of detecting the annihilation signature, and the expected reach for UHDM with current and future very-high-energy (VHE; >100 GeV) γ-ray observatories. Specifically, we focus on three reference instruments: two Imaging Atmospheric Cherenkov Telescope arrays, modeled on VERITAS and CTA-North, and one extended air shower array, motivated by HAWC. With reasonable assumptions on the instrument response functions and background rate, we find a set of UHDM parameters (mass and cross section) for which a γ-ray signature can be detected by the aforementioned observatories. Here, we further compute the expected upper limits for each experiment. With realistic exposure times, the three instruments can probe DM across a wide mass range. At the lower end, it can still have a point-like cross section, while at higher masses the DM could have a geometric cross section, indicative of compositeness.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Active learning of uniformly accurate interatomic potentials for materials simulation

An active learning procedure called deep potential generator (DP-GEN) is proposed for the construction of accurate and transferable machine learning-based models of the potential energy surface (PES) for the molecular modeling of materials. This procedure consists of three main components: exploration, generation of accurate reference data, and training. Application to the sample systems of Al, Mg, and Al-Mg alloys demonstrates that DP-GEN can produce uniformly accurate PES models with a minimal number of reference data.

36 MATERIALS SCIENCE↗
DOE OSTI2014

An evaluation of experimental decadal predictions using CCSM4

This study assesses retrospective decadal prediction skill of sea surface temperature (SST) variability in initialized climate prediction experiments with the Community Climate System Model version 4 (CCSM4). Ensemble forecasts initialized with two different historical ocean and sea-ice states are evaluated and compared to an ensemble of uninitialized coupled simulations. Both experiments are subject to identical twentieth century historical radiative forcings. Each forecast consists of a 10-member ensemble integrated over a 10-year period. One set of historical ocean and sea-ice conditions used for initialization comes from a forced ocean-ice simulation driven by the Coordinated Ocean-ice Reference Experiments interannually varying atmospheric dataset. Following the Coordinated Model Intercomparison Project version 5 (CMIP5) protocol, these forecasts are initialized every 5 years from 1961 to 1996, and every year from 2000 to 2006. A second set of initial conditions comes from historical ocean state estimates obtained through the assimilation of in-situ temperature and salinity data into the CCSM4 ocean model. These forecasts are only available over a limited subset of the CMIP5 recommended start dates. Both methods result in retrospective SST prediction skill over broad regions of the Indian Ocean, western Pacific Ocean and North Atlantic Ocean that are significantly better than reference skill levels from a spatio-temporal auto-regressive statistical model of SST. However the subpolar gyre region of the North Atlantic stands out as the only region where the CCSM4 initialized predictions outperform uninitialized simulations. Some features of the ocean state estimates used for initialization and their impact on the forecasts are discussed.

Meteorology & Atmospheric Sciences↗
DOE OSTI2015

Calibration of X-Ray diffractometer by the experimental comparison method

A software for calibrating an X-ray diffractometer with area detector has been developed. It is proposed to search for detector and goniometer calibration models whose parameters are reproduced in a series of measurements on a reference crystal. Reference (standard) crystals are prepared during the investigation; they should provide the agreement of structural models in repeated analyses. The technique developed has been used to calibrate Xcalibur Sapphire and Eos, Gemini Ruby (Agilent) and Apex x8 and Apex Duo (Bruker) diffractometers. The main conclusions are as follows: the calibration maps are stable for several years and can be used to improve structural results, verified CCD detectors exhibit significant inhomogeneity of the efficiency (response) function, and a Bruker goniometer introduces smaller distortions than an Agilent goniometer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Investigating Application of LiDAR for Nuclear Power Plants

Many evaluation, assessment, and modeling tasks at nuclear power plants require spatial in-formation; this often requires physical visits to locations within the facility because the 2D or 3D schematics and current models do not contain enough detail or do not capture as-built and real-world conditions. These visits require extensive manual labor for not only the requesting party, but also support groups, such as security. Light Detection and Ranging (LiDAR) mapping is trying to solve that problem by providing very detailed 3D models for low costs. However, the use of these models can be very limited because either component reference information is missing and too costly to add or there is no way to extract specific spatial data needed for other tools. This report outlines two main efforts. First, to reduce the effort of “Tagging” data in large 3D models, a general Application Programming Interface (API) was developed to import a variety of existing plant database information into a 3D-visualization engine. Filters allow the user to have only zone-specific items listed; then, they can simply click and assign the information to a specific spot or component in the 3D model. The second part of the work is the development of an interface for importing pieces from the3D-LiDAR model into other systems needed for modeling and simulation, outlined around fire modeling. This interface allows for the retrieval of item location and boundaries, enabling the auto generation of models for varying tools.

3D Modelling↗
DOE OSTI2023

A Landau-Devonshire Approach of Elastic Strain Effects on Ferroelectric Al1-xScxN

Landau-Devonshire thermodynamic modeling enables the phenomenological description of ferroelectrics. 1 The approach has been validated across a wide range of ferroelectric materials from the first ferroelectric discovered, Rochelle Salt, to recent HfO2-based materials. 2-4 Extension to what is now referred to as the Landau-Ginsburg-Devonshire model enables rigorous investigation of polarization boundaries and reorientation, phase transformations, and domain formation/evolution. We present a thermodynamic analysis of the recently discovered nitride ferroelectric materials 5-7 using the classic Landau-Devonshire approach. The electrostrictive and dielectric stiffness coefficients of Al1-xScxN with wurtzite structure (6mm) are determined using a free energy density function assuming a hexagonal parent phase (6/mmm), with the first order phase transition based on the dielectric stiffness relationships (Fig. 1). The results of this analysis show that the strain sensitivity of the energy barrier is one order of magnitude larger than that of the spontaneous polarization in these wurtzite ferroelectrics, yet both are less sensitive to strain compared to classic perovskite ferroelectrics (Fig. 2). These analysis results reported here explain experimentally reported sensitivity of coercive field to elastic strain/stress in Al1-xScxN films, and would enable further thermodynamic analysis via phase field simulation and related methods.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗
DOE OSTI2024

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗
DOE OSTI2018

Revised Tijeras Arroyo Groundwater Current Conceptual Model and Corrective Measures Evaluation Report - February 2018.

The U.S. Department of Energy (DOE) and the management and operating (M&O) contractor for Sandia National Laboratories beginning on May 1, 2017, National Technology & Engineering Solutions of Sandia, LLC (NTESS), hereinafter collectively referred to as DOE/NTESS, prepared this Revised Tijeras Arroyo Groundwater Current Conceptual Model (CCM) and Corrective Measures Evaluation (CME) Report , referred to as the Revised CCM/CME Report, to meet requirements under the Sandia National Laboratories-New Mexico (SNL/NM) Compliance Order on Consent (Consent Order). The Consent Order became effective on April 29, 2004. The Consent Order identifies the Tijeras Arroyo Groundwater (TAG) Area of Concern (AOC) as an area of groundwater contamination requiring further characterization and corrective action. In November 2004, New Mexico Environment Department (NMED) approved the July 2004 CME Work Plan. In April 2005, DOE and the SNL M&O contractor at the time, Sandia Corporation (Sandia), hereinafter collectively referred to as DOE/Sandia, submitted a CME Report, but NMED did not finalize review of that document. In December 2016, DOE/Sandia submitted a combined and updated CCM/CME Report. NMED issued a disapproval letter in May 2017 that included comments on the December 2016 CCM/CME Report. In August 2017, NMED and DOE/NTESS staff held a meeting to discuss and clarify outstanding issues. This Revised CCM/CME Report addresses (1) the issues presented in the NMED May 2017 disapproval letter and (2) findings from the August 2017 meeting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Why Do Global Long-term Scenarios for Agriculture Differ? An overview of the AgMIP Global Economic Model Intercomparison

Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. Ten global economic models that produce long-term scenarios were asked to compare a reference scenario with alternate socio-economic, climate change and bioenergy scenarios using a common set of key drivers. Results suggest that, once general assumptions are harmonized, the variability in general trends across models declines, and that several common conclusions are possible. Nonetheless, differences in basic model parameters, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. This holds for both the common reference scenario and for the various shocks applied. We conclude that agro-economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross-fertilize analyses at different scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

A three-dimensional sectional representation of aerosol mixing state for simulating optical properties and cloud condensation nuclei

Light absorption by black carbon (BC) particles emitted from fossil fuel combustion depends on the how thickly they are coated with non-refractory species such as ammonium, sulfate, nitrate, organics, and water. The cloud condensation nuclei (CCN) activation property of a particle depends on its dry size and the hygroscopicities of all the individual species mixed together. It is therefore necessary to represent both size and mixing state of aerosols to reliably predict their climate-relevant properties in atmospheric models. Here we describe and evaluate a novel sectional framework in the Model for Simulating Aerosol Interactions and Chemistry, referred to as MOSAIC-mix, that represents the mixing state by resolving aerosol dry size (D dry ), BC dry mass fraction (w BC ), and hygroscopicity (κ). Using ten idealized urban plume scenarios in which different types of aerosols evolve over 24 hours under a range of atmospherically relevant environmental conditions, we examine errors in CCN concentrations and optical properties with respect to a more explicit aerosol mixing state representation. We find that only a small number of w BC and κ bins are needed to achieve significant reductions in the errors, and propose a configuration consisting of 24 D dry bins, 2 w BC bins, and 2 κ bins that gives 24-hour average errors of about 5% or less in CCN concentrations and optical properties, 3-4 times lower than those from size-only-resolved simulations. Here, these results show that MOSAIC-mix is suitable for use in regional and global models to examine the effects of evolving aerosol mixing states on aerosol-radiation-cloud feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

JAMES BUTTLE REVIEW: Interflow, subsurface stormflow and throughflow: A synthesis of field work and modelling

Interflow, throughflow and subsurface stormflow are interchangeable terms that refer to the lateral subsurface flow above a restricting layer of lower hydraulic conductivity that occurs during and following storm events. Interflow (used here) is a more dominant process in steeper catchments with high infiltration capacity soils overlying a more impermeable soil or geologic layer. Interflow as a runoff process was first recognised in the early 1900s, yet hydrologists still struggle to predict its occurrence, persistence, importance, interaction with other streamflow generation processes, and potential to connect to valleys and streams during and following storms. We review the history of interflow research and address some of the challenges in understanding its role in runoff production. We argue that characterising the controls on interflow initiation and occurrence relies on detailed field observations of subsurface properties, which exist only in limited experimental settings. This data shortcoming contributes to our inability to predict interflow or determine its contribution to streamflow more broadly. There remain many opportunities to advance our understanding of interflow that include both modelling and experimental or observational approaches in hydrology.

hillslope hydrology↗
DOE OSTI2025

Large-signal Stability Analysis of Grid-forming Inverters with Equivalent-circuit Models

Here, this paper proposes an energy function-based direct method for large-signal stability assessment of grid-forming (GFM) inverters leveraging an equivalent-circuit representation of all involved control- and physical-layer dynamics. Three different primary controls, a standard inner-current outer-voltage cascaded-control architecture, output LCL filter, and reference-current saturation limiting are featured in the modeling and analysis framework. A composite energy function for the GFM inverter is obtained by summing up individual energy contributions gleaned from the circuit representation. The approach can readily be generalized to different primary controls, output-filter arrangements, and current limiters since it is based on a circuit-theoretic foundation. Numerical simulations validate the efficacy of the approach in estimating the critical clearing time following a large-signal disturbance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

The Wave Energy Converter Control Competition: Overview

Over the past two years, a wave energy converter control systems competition (WECCCOMP) has been in progress, with the objective of comparing different wave energy converter (WEC) control paradigms on a standard benchmark problem. The target system is a point absorber, corresponding to a single float with an absolute reference, of the WaveStar WEC prototype. The system was modelled in WEC-Sim, with the hydrodynamic parameters validated against tank test data. Competitors were asked to design and implement a WEC control system for this model, with performance evaluated across six sea states. The evaluation criteria included a weighted combination of average converted power, peak/average power, and the degree to which the system physical constraints were exploited or temporarily exceeded.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Integrating crop growth models with remote sensing for predicting biomass yield of sorghum

Abstract Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programmes to develop varieties aimed at performance in the target environments. Crop models can improve this testing regime by providing a predictive framework to (i) augment field phenotyping data and derive hard-to-measure phenotypes and (ii) estimate performance across geographical regions using historical weather data. The goal of this study was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits in 18 commercial grain and biomass sorghum hybrids. Genotype parameters for each hybrid were estimated using remote-sensing measurements combined with manual phenotyping in West Lafayette, IN, in 2018. The models were validated in hybrid performance trials in two additional seasons at that site and against yield trials conducted in Bushland, TX, between 2001 and 2018. These trials demonstrated that (i) maximum plant height, final dry biomass and radiation use efficiency (RUE) of photoperiod-sensitive and -insensitive forage sorghum hybrids tended to be higher than observed in grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass production in longer growing environments and (iii) the parameterized and validated models perform well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize larger plant breeding populations.

Yang, Kai-Wei↗
DOE OSTI2016

A comprehensive scenario of the thermodynamic anomalies of water using the TIP4P/2005 model

The striking behavior of water has deserved it to be referred to as an “anomalous” liquid. The water anomalies are greatly amplified in metastable (supercooled and/or stretched) regions. This makes difficult a complete experimental description since, beyond certain limits, the metastable phase necessarily transforms into the stable one. Theoretical interpretation of the water anomalies could then be based on simulation results of well validated water models. But the analysis of the simulations has not yet reached a consensus. In particular, one of the most popular theoretical scenarios—involving the existence of a liquid-liquid critical point (LLCP)—is disputed by several authors. In this work, we propose to use a number of exact thermodynamic relations which may shed light on this issue. Interestingly, these relations may be tested in a region of the phase diagram which is outside the LLCP thus avoiding the problems associated to the coexistence region. The central property connected to other water anomalies is the locus of temperatures at which the density along isobars attain a maximum (TMD line) or a minimum (TmD). We have performed computer simulations to evaluate the TMD and TmD for a successful water model, namely, TIP4P/2005. We have also evaluated the vapor-liquid (VL) spinodal in the region of large negative pressures. The shape of these curves and their connection to the extrema of some response functions, in particular the isothermal compressibility and heat capacity at constant pressure, provides very useful information which may help to elucidate the validity of the theoretical proposals. In this way, we are able to present for the first time a comprehensive scenario of the thermodynamic water anomalies for TIP4P/2005 and their relation to the vapor-liquid spinodal. The overall picture shows a remarkable similarity with the corresponding one for the ST2 water model, for which the existence of a LLCP has been demonstrated in recent years. It also provides a hint as to where the long-sought for extrema in response functions might become accessible to experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗