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DOE OSTI2026

Using Density-Corrected DFT to Understand Density-Driven and Functional-Dependent Errors in Ab Initio Simulations of the Hydrated Electron

The hydrated electron, an excess electron in liquid water, plays a crucial role in a plethora of chemical processes, motivating extensive research efforts to characterize its structure, dynamics, and reactivity in solution. Recent theoretical approaches to understanding this intriguing object have involved ab initio simulations based on density functional theory (DFT). Although DFT allows for the study of hydrated electron reactivity and quantum mechanical behavior, it is well-known that anionic systems can suffer from significant density-driven errors (DDEs). Density-corrected DFT (DC-DFT) provides a framework to mitigate such errors; the method reduces DDEs by replacing the self-consistent (SC) density associated with a given density functional with the Hartree–Fock (HF) density. Since HF densities tend to be more localized than DFT SC densities, the DC-DFT scheme significantly improves errors in calculations where the SC density is spuriously delocalized. Here, we investigate how the use of density correction affects the calculated properties of the DFT-simulated (PBEh) hydrated electron, a particularly challenging diffuse anionic system to simulate. First, we analyze charge delocalization in a system consisting of a model octahedral hydrated electron water cluster (the so-called Kevan structure) along with a spatially separated sulfur atom. We show that the use of density correction indeed reduces DDEs in comparison to a standard DFT global hybrid functional. We then propagate molecular dynamics trajectories of the hydrated electron using DC-DFT, where we find that DC further localizes electron density in the cavity region, a signature of reduced charge delocalization. Unfortunately, the decreased radius of gyration of the spin density and corresponding tightening of the local solvation structure from density correction causes predicted observables to deviate further from experimental measurements than when density correction is not employed. Here, we argue that DC’s worse agreement with experiment results from the removal of a fortuitous cancellation of errors that is intrinsic to the PBEh functional. This indicates that the difficulties with DFT to simulate hydrated electrons are primarily due to the inherent approximations in DFT rather than to density-driven errors.

Density functional theory↗

DOE OSTI2021

Component-wise reduced order model lattice-type structure design

Lattice-type structures can provide a combination of stiffness with light weight that is desirable in a variety of applications. Design optimization of these structures must rely on approximations of the governing physics to render solution of a mathematical model feasible. In this paper, we propose a topology optimization (TO) formulation that approximates the governing physics using component-wise reduced order modeling as introduced in Huynh et al. (2013); Eftang and Patera (2013), which can reduce solution time by multiple orders of magnitude over a full-order finite element model while providing a relative error in the solution of 1%. In addition, the offline training data set from such component-wise models is reusable, allowing its application to many design problems for only the cost of a single offline training phase, and the component-wise method is nearly embarrassingly parallel. We also show how the parameterization chosen in our optimization allows a simplification of the component-wise reduced order model (CWROM) not noted in previous literature, for further speedup of the optimization process. Furthermore, the sensitivity of the compliance with respect to the particular parameterization is derived solely at the component level. In numerical examples, we demonstrate a 1000x speedup over a full-order FEM model with relative error of 1% and show minimum compliance designs for two different cantilever beam examples, one smaller and one larger. Finally, error bounds for the displacement field, compliance, and compliance sensitivity of the CWROM are derived.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Relating the structure of geminal amido esters to their molecular hyperpolarizability

Advanced organic non-linear optical (NLO) materials have attracted increasing attention due to their multitude of applications in modern telecommunication devices. Arguably the most important advantage of organic NLO materials, relative to traditionally used inorganic NLO materials, is their short optical response time. Geminal amido esters with their donor-x-acceptor (D-π-A) architecture exhibit high levels of electron delocalization and substantial intramolecular charge transfer, which should endow these materials with short optical response times and large molecular (hyper)polarizabilities. In order to test this hypothesis, the linear and second-order non-linear optical properties of five geminal amido esters, ( E )-ethyl 3-(X-phenylamino)-2-(Y-phenylcarbamoyl)acrylate (1: X = 4-H,Y = 4-H; 2: X= 4-CH 3 , Y = 4-CH 3 ; 3: X = 4-NO 2 , Y = 2,5-OCH 3 ; 4: X = 2-Cl, Y = 2-Cl; 5: X = 4-Cl, Y = 4-Cl) were synthesized and characterized, whereby NLO structure-function relationships were established including intramolecular charge transfer characteristics, crystal field effects, and molecular first hyperpolarizabilities β. Given the typically large errors (10-30%) associated with the determination of (β) coefficients, three independent methods were used: i) density functional theory, ii) hyper-Rayleigh scattering, and iii) high-resolution X-ray diffraction data analysis based on multipolar modeling of electron densities at each atom. These three methods delivered consistent values of β, and based on these results, 3 should hold the most promise for NLO applications. In conclusion, the correlation between the molecular structure of these geminal amido esters and their linear and non-linear optical properties thus provide molecular design guidelines for organic NLO materials; this leads to the ultimate goal of generating bespoke organic molecules to suit a given NLO device application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

VARIATIONAL PRINCIPLE FOR PLANETARY INTERIORS

In the past few years, the number of confirmed planets has grown above 2000. It is clear that they represent a diversity of structures not seen in our own solar system. In addition to very detailed interior modeling, it is valuable to have a simple analytical framework for describing planetary structures. The variational principle is a fundamental principle in physics, entailing that a physical system follows the trajectory, which minimizes its action. It is alternative to the differential equation formulation of a physical system. Applying the variational principle to the planetary interior can beautifully summarize the set of differential equations into one, which provides us some insight into the problem. From this principle, a universal mass–radius relation, an estimate of the error propagation from the equation of state to the mass–radius relation, and a form of the virial theorem applicable to planetary interiors are derived.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Interpretable and flexible non-intrusive reduced-order models using reproducing kernel Hilbert spaces

This paper develops an interpretable, non-intrusive reduced-order modeling technique using regularized kernel interpolation. Existing non-intrusive approaches approximate the dynamics of a reduced-order model (ROM) by solving a data-driven least-squares regression problem for low-dimensional matrix operators. Our approach instead leverages regularized kernel interpolation, which yields an optimal approximation of the ROM dynamics from a user-defined reproducing kernel Hilbert space. We show that our kernel-based approach can produce interpretable ROMs whose structure mirrors full-order model structure by embedding judiciously chosen feature maps into the kernel. The approach is flexible and allows a combination of informed structure through feature maps and closure terms via more general nonlinear terms in the kernel. We also derive a computable a posteriori error bound that combines standard error estimates for intrusive projection-based ROMs and kernel interpolants. In conclusion, the approach is demonstrated in several numerical experiments that include comparisons to operator inference using both proper orthogonal decomposition and quadratic manifold dimension reduction.

Data-driven model reduction↗

DOE OSTI2016

A TRACER METHOD FOR COMPUTING TYPE IA SUPERNOVA YIELDS: BURNING MODEL CALIBRATION, RECONSTRUCTION OF THICKENED FLAMES, AND VERIFICATION FOR PLANAR DETONATIONS

We refine our previously introduced parameterized model for explosive carbon–oxygen fusion during thermonuclear Type Ia supernovae (SNe Ia) by adding corrections to post-processing of recorded Lagrangian fluid-element histories to obtain more accurate isotopic yields. Deflagration and detonation products are verified for propagation in a medium of uniform density. A new method is introduced for reconstructing the temperature–density history within the artificially thick model deflagration front. We obtain better than 5% consistency between the electron capture computed by the burning model and yields from post-processing. For detonations, we compare to a benchmark calculation of the structure of driven steady-state planar detonations performed with a large nuclear reaction network and error-controlled integration. We verify that, for steady-state planar detonations down to a density of 5 × 10{sup 6} g cm{sup −3}, our post-processing matches the major abundances in the benchmark solution typically to better than 10% for times greater than 0.01 s after the passage of the shock front. As a test case to demonstrate the method, presented here with post-processing for the first time, we perform a two-dimensional simulation of a SN Ia in the scenario of a Chandrasekhar-mass deflagration–detonation transition (DDT). We find that reconstruction of deflagration tracks leads to slightly more complete silicon burning than without reconstruction. The resulting abundance structure of the ejecta is consistent with inferences from spectroscopic studies of observed SNe Ia. We confirm the absence of a central region of stable Fe-group material for the multi-dimensional DDT scenario. Detailed isotopic yields are tabulated and change only modestly when using deflagration reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

X-RAY SPECTRAL AND OPTICAL PROPERTIES OF A ULX IN NGC 4258 (M106)

We study the X-ray and optical properties of the ultraluminous X-ray source (ULX) X-6 in the nearby galaxy NGC 4258 (M106) based on the archival XMM-Newton , Chandra , Swift , and Hubble Space Telescope (HST) observations. The source has a peak luminosity of L {sub X} ∼ 2 × 10{sup 39} erg s{sup −1} in the XMM-Newton observation of 2004 June. Consideration of the hardness ratios and the spectral model parameters shows that the source seems to exhibit possible spectral variations throughout the X-ray observations. In the images from the HST /Advanced Camera for Surveys, three optical sources have been identified as counterpart candidates within the 1 σ error radius of 0.″3. The brightest one has an absolute magnitude of M {sub V} ≈ −7.0 and shows extended structure. The remaining two sources have absolute magnitudes of M {sub V} ≈ −5.8 and −5.3. The possible spectral types of the candidates from brightest to dimmest were determined as B6–A5, B0–A7, and B2–A3. The counterparts of the X-ray source possibly belong to a young star cluster. Neither the standard disk model nor the slim disk model provides firm evidence to determine the spectral characteristics of ULX X-6. We argue that the mass of the compact object lies in the range 10–15 M {sub ☉}, indicating that the compact source is most likely a stellar-mass black hole.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Force field for calcium sulfate minerals to predict structural, hydration, and interfacial properties

Calcium sulfates such as anhydrite, hemihydrate, and gypsum find widespread use in building materials, implants, and tissue healing. We introduce a simple and compatible atomistic force field for all calcium sulfate phases that reproduces a wide range of experimental data including lattice parameters, surface, hydration, mechanical, and thermal properties in 1% to 5% accuracy relative to experiments. The performance is several times better than prior force fields and DFT methods, which lead to errors in structures and energies up to 100%. We explain (hkl) cleavage energies, the dynamics of (hkl) water interfaces, and new insights into molecular origins of crystal-facet specific hydration and solubility. Impressive agreement of computed and experimentally measured hydration energies is shown. The models add to the Interface force field (IFF) and are compatible with multiple force fields (CHARMM, AMBER, GROMOS, CVFF, PCFF, OPLS-AA) for property predictions of sulfate-containing materials from atoms to the large nanometer scale.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Adaptive h -refinement for reduced-order models: ADAPTIVE h -refinement for reduced-order models

Our work presents a method to adaptively refine reduced-order models a posteriori without requiring additional full-order-model solves. The technique is analogous to mesh-adaptive h-refinement: it enriches the reduced-basis space online by ‘splitting’ a given basis vector into several vectors with disjoint support. The splitting scheme is defined by a tree structure constructed offline via recursive k-means clustering of the state variables using snapshot data. This method identifies the vectors to split online using a dual-weighted-residual approach that aims to reduce error in an output quantity of interest. The resulting method generates a hierarchy of subspaces online without requiring large-scale operations or full-order-model solves. Furthermore, it enables the reduced-order model to satisfy any prescribed error tolerance regardless of its original fidelity, as a completely refined reduced-order model is mathematically equivalent to the original full-order model. Experiments on a parameterized inviscid Burgers equation highlight the ability of the method to capture phenomena (e.g., moving shocks) not contained in the span of the original reduced basis.

42 ENGINEERING↗

DOE OSTI2020

Validation and Sensitivity Analysis of a 1-D Lake Model Across Global Lakes

Lakes have important influence on weather and climate from local to global scales. However, their prediction using numerical models is notoriously difficult because lakes are highly heterogeneous across the globe, but observations are sparse. In this study, we assessed the performance of a 1-D lake model in simulating the thermal structures of 58 lakes with diverse morphometric and geographic characteristics by following the phase 2a local lake protocol of the Inter-sectoral Impact Model Intercomparison Project (ISIMIP2a). After calibration, the root-mean-square errors (RMSE) were below 2 °C for 70% and 75% of the lakes for epilimnion and full-profile temperature simulations, with an average of 1.71 °C and 1.43 °C, respectively. The model performance mainly depended on lake shape rather than location, supporting the possibility of grouping model parameters by lake shape for global applications. Furthermore, through machine-learning based parameter sensitivity tests, we identified turbulent heat fluxes, wind-driven mixing and water transparency as the major processes controlling lake thermal and mixing regimes. Snow density was also important for modeling the ice phenology of high-latitude lakes. The relative influence of the key processes and the corresponding parameters mainly depended on lake latitude and depth. Turbulent heat fluxes showed a decreasing importance in affecting epilimnion temperature with increasing latitude. Wind-driven mixing was less influential to lake stratification for deeper lakes while the impact of light extinction, on the contrary, showed a positive correlation with depth. Our findings may guide improvements in 1-D lake model parameterizations to achieve higher fidelity in simulating global lake thermal dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Evaluation of the Planetary Boundary Layer Height From ERA5 Reanalysis With MOSAiC Observations Over the Arctic Ocean

The planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year-round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLH MOSAiC ), and further evaluate the PBLH from the ERA5 reanalysis (PBLH ERA5 ). Comparisons between PBLH MOSAiC and PBLH ERA5 from different perspectives reveal that: (a) The overestimation of PBLH ERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLH ERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLH ERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLH ERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Modeling direct interband tunneling. I. Bulk semiconductors

Interband tunneling is frequently studied using the semiclassical Kane model, despite uncertainty about its validity. Revisiting the physical basis of this formula, we find that it neglects coupling to other bands and underestimates transverse tunneling. As a result, significant errors can arise at low and high fields for small and large gap materials, respectively. We derive a simple multiband tunneling model to correct these defects analytically without arbitrary parameters. Through extensive comparison with band structure and quantum transport calculations for bulk InGaAs, InAs, and InSb, we probe the accuracy of the Kane and multiband formulas and establish the superiority of the latter. We also show that the nonlocal average electric field should be used when applying either of these models to nonuniform potentials. Our findings are important for efficient analysis and simulation of bulk semiconductor devices involving tunneling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Recent Measurement of Flavor Asymmetry of Antiquarks in the Proton by Drell–Yan Experiment SeaQuest at Fermilab

A measurement of the flavor asymmetry of the antiquarks ($\bar{d}$ and $\bar{u}$) in the proton is described in this thesis. The proton consists of three valence quarks, sea quarks, and gluons. Antiquarks in the proton are sea quarks. They are generated from the gluon splitting: g → q + $\bar{q}$. According to QCD (Quantum Chromodynamics), the gluon splitting is independent of quark flavor. It suggests that the amounts of $\bar{d}$ and $\bar{u}$ should be the same in the proton. However, the NMC experiment at CERN found that the amount of $\bar{d}$ is larger than that of $\bar{u}$ in the proton using the deep inelastic scattering in 1991. This result is obtained for $\bar{d}$ and $\bar{u}$ integrated over Bjorken x. Bjorken x is the fraction of the momentum of the parton to that of the proton. The NA51 experiment (x ~ 0.2) at CERN and E866/NuSea experiment (0.015 < x < 0.35) at Fermilab measured the flavor asymmetry of the antiquarks ($\bar{d}$/$\bar{u}$) in the proton as a function of x using Drell–Yan process. The experiments reported that the flavor symmetry is broken over all measured x values. Understanding the flavor asymmetry of the antiquarks in the proton is a challenge of the QCD. The theo- retical investigation from the first principle of QCD such as lattice QCD calculation is important. In addition, the QCD effective models and hadron models such as the meson cloud model can also be tested with the flavor asymmetry of antiquarks. From the experimental side, it is important to measure with higher accuracy and in a wider x range. The SeaQuest (E906) experiment measures $\bar{d}$/$\bar{u}$ at large x (0.15 < x < 0.45) accurately to understand its behavior. The SeaQuest experiment is a Drell–Yan experiment at Fermi National Accelerator Laboratory (Fermilab). In the Drell–Yan process of proton-proton reaction, an antiquark in a proton and a quark in another proton annihilate and create a virtual photon, which then decays into a muon pair (q$\bar{q}$ → γ* → µ + µ - ). The SeaQuest experiment uses a 120 GeV proton beam extracted from Fermilab’s Main Injector. The proton beam interacts with hydrogen and deuterium targets. The SeaQuest spectrometer detects the muon pairs from the Drell–Yan process. The $\bar{d}$/$\bar{u}$ ratio at 0.1 < x < 0.58 is extracted from the number of detected Drell–Yan muon pairs. After the detector construction, commissioning run and detector upgrade, the SeaQuest experiment started the physics data acquisition from 2013. We finished so far three periods of physics data acquisition. The fourth period is in progress. The detector construction, detector performance evaluation, data taking and data analysis for the flavor asymmetry of the antiquarks $\bar{d}$/$\bar{u}$ in the proton are my contribution to SeaQuest. The cross section ratio of Drell–Yan process in p- p and p-d reactions is obtained from dimuon yields. In the experiment with high beam intensity, it is important to control the tracking efficiency of charged particles through the magnetic spectrometer. The tracking efficiency depends on the chamber occupancy, and the appropriate method for the correction is important. The chamber occupancy is the number of hits in drift chambers. A new method of the correction for the tracking efficiency is developed based on the occupancy, and applied to the data. This method reflects the real response of the drift chambers. Therefore, the systematic error is well controlled by this method. The flavor asymmetry of antiquarks is obtained at 0.1 < x < 0.58. At 0.1 < x < 0.45, the result is $\bar{d}$/$\bar{u}$ > 1. The result at 0.1 < x < 0.24 agrees with the E866 result. The result at x > 0.24, however, disagrees with the E866 result. The result at 0.45 < x < 0 the statistical errors. u¯ results extracted from experiments are used to investigate the validity of the theoretical models. The present experimental result provides the data points in wide x region. It is useful for understanding the proton structure in the light of QCD and effective hadron models. The present result has a practical application as well. Antiquark distributions are important as inputs to simulations of hadron reactions such as W± production in various experiments. The new knowledge on antiquark distributions helps to improve the precision of the simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Combustion energy frontier research center (CEFRC) final report (August 1, 2009 – July 31, 2016)

The Combustion Energy Frontier Research Center (CEFRC) was established to tackle the single overarching grand challenge of energy sustainability, energy security and global warming: to develop a “validated, predictive, multi-scale, combustion modeling capability to optimize the design and operation of evolving fuels in advanced engines for transportation applications,” as identified in the DOE report on “Basic Energy Needs for Clean and Efficient Combustion of 21st Century Transportation Fuels”. The challenge is particularly daunting since energy conversion efficiencies and exhaust emissions are governed by coupled chemical and transport processes at multiple length scales ranging from electron excitation to molecular rearrangements to nanoscale particulate formation to turbulent fuel/air mixing. To tackle this challenge, the CEFRC assembled a world-class team of 15 principal investigators, with the objectives to: 1) develop and test theoretical models to predict elementary reaction rates, molecule thermalization rates, chemical bond dissociation energies, and nonequilibrium transport properties using quantum chemistry calculations that account for strong electron correlation and multiple electronic potential energy surfaces; 2) develop automated kinetic mechanism generation, reduction, and error control methods for predicting alternative fuel including biofuel oxidation, fuel droplet decomposition, and NOx and particulate formation; 3) validate and improve the predictions of these models by measuring ignition delay times, species profiles, flame structures, burning limits, turbulence-kinetic coupling, and NOx and soot emissions at high-pressures and near-limit conditions, by using advanced experimental diagnostic techniques including multiple laser techniques, molecular beam sampling and synchrotron photoionization, and by conducting the measurements in high-pressure shock tubes, jet-stirred and flow reactors, flame bombs, counterflow flames, and advanced-design rapid compression ignition instruments; and 4) develop a suite of validated petascale high-fidelity simulation and modeling capabilities to understand and predict chemistry-turbulence-radiation coupling for new fuels in new regimes, including the high pressure, low-temperature combustion in advanced engine and turbine designs, and 5) establish a knowledge highway between researchers and engineers in academia, national laboratories, and industry to facilitate the dissemination and exchange of knowledge on national and international levels, and enrich the talent pool and capabilities of the next generation of combustion scientists and engineers. The technical activities of the CEFRC were conducted through three Disciplinary Working Groups – Chemistry Theory, Experiment and Mechanism, and Reacting Flows, which coordinated the Center’s research on the development of combustion chemistry of Foundation Fuels (C0–C4 hydrocarbons), Alcohols, and Biodiesel through three corresponding Mechanism Thrust Groups. Such a two-dimensional coordinated and tightly interwoven research structure has been proven to be highly effective in assuring the interplay between the developments of the fundamentals of combustion science and the utilization of the various categories of fuels. The Center has accomplished the above goals over the five year period (August 1, 2009 – July 31, 2014) with appropriated funding, followed by two additional no-cost-extension (NCE) years. The research results are documented in 230 journal publications, with six legacy review papers on the study of combustion chemistry using shock tubes, flow reactors, rapid compression machines, and flames, on uncertainty quantification, and on theoretical reaction dynamics and chemical modeling of combustion. A robust outreach program complemented these PI-led research activities, consisting of: 1) a roving post-doc program comprised of a corps of Center-appointed, co- or multi-sponsored post-doctoral fellows with rotating assignments to conduct seed projects initiated by at least two PIs, in residence with these sponsoring PIs, to rapidly pursue new and high-risk, high-payoff interdisciplinary ideas; 2) an annual summer school on combustion heavily attended (~200) by senior graduate students and practicing researchers covering advanced topics on chemical kinetics, fluid mechanics, turbulent combustion, engine combustion, new technologies, etc.; 3) a robust open web-site providing Center and community information as well as the lecture videos and notes of the summer school; and 4) widely distributed biannual newsletters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Predicting biomass of hyperdiverse and structurally complex central Amazonian forests - a virtual approach using extensive field data

Notice on corrigendum: This paper has a corresponding corrigendum published. Please read the corrigendum first. Old-growth forests are subject to substantial changes in structure and species composition due to the intensification of human activities, gradual climate change and extreme weather events. Trees store ca. 90 % of the total aboveground biomass (AGB) in tropical forests and precise tree biomass estimation models are crucial for management and conservation. In the central Amazon, predicting AGB at large spatial scales is a challenging task due to the heterogeneity of successional stages, high tree species diversity and inherent variations in tree allometry and architecture. We parameterized generic AGB estimation models applicable across species and a wide range of structural and compositional variation related to species sorting into height layers as well as frequent natural disturbances. We used 727 trees (diameter at breast height ≥ 5 cm) from 101 genera and at least 135 species harvested in a contiguous forest near Manaus, Brazil. Sampling from this data set we assembled six scenarios designed to span existing gradients in floristic composition and size distribution in order to select models that best predict AGB at the landscape level across successional gradients. We found that good individual tree model fits do not necessarily translate into reliable predictions of AGB at the landscape level. When predicting AGB (dry mass) over scenarios using our different models and an available pantropical model, we observed systematic biases ranging from -31 % (pantropical) to +39 %, with root-mean-square error (RMSE) values of up to 130 Mg ha -1 (pantropical). Our first and second best models had both low mean biases (0.8 and 3.9 %, respectively) and RMSE (9.4 and 18.6 Mg ha -1 ) when applied over scenarios. Predicting biomass correctly at the landscape level in hyperdiverse and structurally complex tropical forests, especially allowing good performance at the margins of data availability for model construction/calibration, requires the inclusion of predictors that express inherent variations in species architecture. The model of interest should comprise the floristic composition and size-distribution variability of the target forest, implying that even generic global or pantropical biomass estimation models can lead to strong biases. Reliable biomass assessments for the Amazon basin (i.e., secondary forests) still depend on the collection of allometric data at the local/regional scale and forest inventories including species-specific attributes, which are often unavailable or estimated imprecisely in most regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

An unstructured-mesh finite-volume MPDATA for compressible atmospheric dynamics

An advancement of the unstructured-mesh finite-volume MPDATA (Multidimensional Positive Definite Advection Transport Algorithm) is presented that formulates the error-compensative pseudo-velocity of the scheme to rely only on face-normal advective fluxes to the dual cells, in contrast to the full vector employed in previous implementations. This is essentially achieved by expressing the temporal truncation error underlying the pseudo-velocity in a form consistent with the flux-divergence of the governing conservation law. The development is especially important for integrating fluid dynamics equations on non-rectilinear meshes whenever face-normal advective mass fluxes are employed for transport compatible with mass continuity—the latter being essential for flux-form schemes. In particular, the proposed formulation enables large-time-step semi-implicit finite-volume integration of the compressible Euler equations using MPDATA on arbitrary hybrid computational meshes. Furthermore, it facilitates multiple error-compensative iterations of the finite-volume MPDATA and improved overall accuracy. The advancement combines straightforwardly with earlier developments, such as the nonoscillatory option, the infinite-gauge variant, and moving curvilinear meshes. A comprehensive description of the scheme is provided for a hybrid horizontally-unstructured vertically-structured computational mesh for efficient global atmospheric flow modelling. The proposed finite-volume MPDATA is verified using selected 3D global atmospheric benchmark simulations, representative of hydrostatic and non-hydrostatic flow regimes. Besides the added capabilities, the scheme retains fully the efficacy of established finite-volume MPDATA formulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Systematic Parameterization of Lignin for the CHARMM Force Field

Lignin is an abundant aromatic biopolymer within plant cell walls formed through radical coupling chemistry, whose composition and topology can vary greatly depending on the biomass source. Computational modeling provides a complementary approach to traditional experimental techniques to probe lignin interactions, lignin structure, and lignin material properties. However, current modeling approaches are limited based on the subset of lignin chemistries covered by existing lignin force fields. To fill the gap, we developed a comprehensive lignin force field that accounts for more lignin-lignin and lignin-carbohydrate interlinkages than existing lignin force fields, and also greatly expands the lignin monomer chemistries that can be modeled beyond simple alcohols and into the rich mixture of natural lignin varieties. The development of this force field utilizes recent developments in parameterization methodology, and synthesizes them into a workflow that combines target data from multiple molecules simultaneously into a single consistent and comprehensive parameter set. The parameter set represents a significant improvement to alternatives for atomic modeling of diverse lignin topologies, more accurately reproducing experimental observables while also significantly reducing the error relative to quantum calculations. The improved energetics, as well as the rigid adherence to CHARMM parameterization philosophy, enables simulation of lignin within its biological context with greater accuracy than was previously possible. The lignin force field presented here is therefore a crucial first step towards modeling lignin structure across a broad range of environments, including within plant cell walls where lignin is complexed with carbohydrates and deconstructed by bacterial or fungal enzymes, or as it exists within industrial solvent mixtures. Future simulations enabled by this updated lignin force field will thus lead to better chemical and structural understanding of lignin, providing new insight into its role in biomass recalcitrance or probing the potential for lignin to be used within industrial processes.

09 BIOMASS FUELS↗