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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 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2023

FWP FEAA149: “Next Generation Environmental Barrier Coatings”

Environmental barrier coatings (EBCs) are required coatings for utilization of SiC/SiC ceramic matrix composite (CMC) components in gas turbines, where the EBC represents the life-limiting factor for such components. EBC/CMC systems have shown success in aero-engine applications with increased turbine inlet temperatures and improved efficiencies, which are achieved through higher temperature stability, lower density, and decreased reliance on cooling air compared to traditional superalloys. While industrial gas turbines (IGTs) do not currently utilize SiC/SiC CMCs, the current shift towards low-carbon or carbon-free fuel sources for power generation could result in a need for EBC/CMC components with higher temperature capabilities. In this work, three tasks were outlined to improve understanding of EBC lifetimes to encourage use in IGTs with carbon-free fuel such as hydrogen: 1. Define the bond coating oxidation kinetics and EBC failure criteria, 2. Measure thermal expansion coefficients of each layered material, and 3. Perform advanced characterization and modeling to assess EBC lifetimes. Cyclic steam oxidation tests were conducted on various EBC/Si/SiC chemistries and EBC/SiC architectures to define substrate oxidation kinetics and EBC failure modes. An open-source code was developed to quantify the undulating thermally grown oxide thickness with thousands of measurements from specimen cross-section images. Bond coating oxidation kinetics were determined and used to develop a kinetic and thermodynamic model for predicting EBC lifetimes. High-temperature Raman spectroscopy was utilized for determining the SiO 2 thermally grown oxide phase transformation as the life-limiting feature for EBCs. Model efforts supported the claim that the SiO 2 phase transformation causes elevated stress during thermal cycling with associated cracking that decreases the adhesion strength of the EBC, eventually resulting in coating spallation. The finite element model subroutine will be made publicly available upon internal review. Further development of an EBC lifetime model for IGTs involves definition of a critical SiO 2 thickness for EBC spallation and must also consider both environmental (gas velocity, pressure, etc.) and specimen (EBC dopants, layer architectures, etc.) effects into predicted bond coating oxidation kinetics for long-lifetime components.

36 MATERIALS SCIENCE↗

DOE OSTI2021

WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)

The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.

Miara, Ariel↗

DOE OSTI2021

Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3)

Miara, Ariel↗

DOE OSTI2022

Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains

Establish publicly available open-source, high-resolution datasets of greenhouse gas (GHG) emissions, meteorology, soil, and vegetation to support testing and validation of emerging biofuel production monitoring technologies. The project team deployed latest technologies to collect “Gold Standard” data for field- level fluxes of CO 2 , N 2 O, CH 4 and H 2 O in grain sorghum production systems in Texas, Oklahoma, and Kansas. The Oklahoma State University led SMARTFARM was initiated on Oct 1, 2020, due to COVID-19 pandemic delay. We installed closed-path dual laser Eddy Covariance (EC) flux measurement system along with a well-established open-path EC system for simultaneously measuring field-level fluxes of CO 2 , N 2 O, CH 4 , and H2O. The eddy flux data are combined with sub-acre soil moisture and temperature measurements, plant and soil analysis data (nutrient, composition, carbon, growth, and phenology), spatial surveys of soil EC, and pH. Grain sorghum crop was managed including planting and harvesting by producers. All teams recruited postdocs and students for the project and submitted purchase orders for field equipment. The team has developed a draft impact sheet and finalized the advisory board for the project.

09 BIOMASS FUELS↗

DOE OSTI2025

Thermodynamic modeling of countercurrent chemical looping reverse water gas shift process for redox material screening

The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Market optimization and technoeconomic analysis of hydrogen-electricity coproduction systems

Decarbonization efforts across North America, Europe, and beyond rely on variable renewable energy sources such as wind and solar, as well as alternative fuels, such as hydrogen, to support the sustainable energy transition. These advancements have prompted a need for more flexibility in the electric grid to complement non-dispatchable energy sources and increased demand from electrification. Integrated energy systems are well suited to provide this flexibility, but conventional technoeconomic modeling paradigms neglect the time-varying dynamic nature of the grid and thus undervalue resource flexibility. In this work, we develop a computational optimization framework for dynamic market-based technoeconomic comparison of integrated energy systems that coproduce low-carbon electricity and hydrogen (e.g., solid oxide fuel cells, solid oxide electrolysis) against technologies that only produce electricity (e.g., natural gas combined cycle with carbon capture) or only produce hydrogen. Our framework starts with rigorous physics-based process models, built in the open-source Institute for the Design of Advanced Energy Systems (IDAES) modeling and optimization platform, for six energy process concepts. Using these rigorous models and a workflow to optimally design each technology, the framework is shown to be capable of evaluating new and emerging technologies in varying energy markets under a plethora of future scenarios (i.e., renewables penetration, carbon tax, etc.). Ultimately, our framework finds that solid oxide fuel cell-based coproduction systems achieve positive profits for 85% of the analyzed market scenarios. From these market optimization results, we use multivariate linear regression (R 2 values up to 0.99) to determine which electricity price statistics are most significant to predict the optimized annual profit of each system. The proposed framework provides a powerful tool for directly comparing flexible, multi-product energy process concepts to help discern optimal technology and integration options.

08 HYDROGEN↗

DOE OSTI2026

Archi: Agentic Operations at the CMS Experiment

We present Archi, an open-source, end-to-end framework for scientific collaborations that combines the systematic ingestion and organization of heterogeneous data sources with the deployment of configurable, private, and extensible agents that retrieve and reason over them. An instance of Archi has been deployed for the Computing Operations team of the CMS experiment at CERN's LHC since February 2026 as a support agent for technical operators, offering retrieval and analysis capabilities by combining documentation, historical data, and live monitoring systems. We evaluate the system on operator feedback and a question set collected from production usage, graded by human and automated panels. The system proves effective at operational tasks, resolving real-world queries posed by CMS operators. We also observe that locally-hosted, open-weight models perform competitively, enabling fully private management of sensitive data.

Lugato, Pietro [MIT; CERN]↗

DOE OSTI2023

Hard x-ray – optical four-wave mixing using a split-and-delay line

New, hard x-ray free electron lasers (FEL) produce intense femtosecond-to-attosecond pulses at angstrom wavelengths, giving access to the fundamental spatial and temporal scales of matter. These revolutionary light sources open the door to applying the suite of nonlinear, optical spectroscopy methods at hard x-ray photon energies. Nonlinear spectroscopy with hard x-rays can allow for measuring the coherence properties of short wavelength excitations with atomic specificity and for understanding how high energy excitations couple to other degrees of freedom in atomic, molecular or condensed-phase systems. As a step in this direction, here we present hard x-ray, optical four-wave mixing (4WM) measurements done at 9.8 keV at the split-and-delay line at the x-ray correlation spectroscopy (XCS) hutch of the Linac Coherent Light Source (LCLS). In this work, we create an x-ray transient grating (TG) from a pair of crossing x-ray beams and diffract optical laser pulses at 400 nm from the TG. The key technical advance here is being able to independently vary the delays of the x-ray pulses. Measurements were made in 3 different solid samples: bismuth germinate (BGO), zinc oxide (ZnO) and yttrium aluminum garnet (YAG). The resulting phase-matched, 4WM signal is measured in two different ways: by varying the x-ray, x-ray pulse delay which can reveal both material and light source coherence properties and also by varying the optical laser delay with respect to the x-ray TG to study how the x-ray excitation couples to the optical properties. Although no coherent 4WM signal was seen in these measurements, the absence of this signal gives important information on experimental requirements for detecting this in future work. Also, our laser-delay scans, although not a new measurement, were applied to different materials than in past work and reveal new examples x-ray induced lattice dynamics in solids. This work represents a key step towards extending nonlinear optics and time-resolved spectroscopy into the hard x-ray regime.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Ten questions concerning reinforcement learning for building energy management

As buildings account for approximately 40% of global energy consumption and associated greenhouse gas emissions, their role in decarbonizing the power grid is crucial. The increased integration of variable energy sources, such as renewables, introduces uncertainties and unprecedented flexibilities, necessitating buildings to adapt their energy demand to enhance grid resiliency. Consequently, buildings must transition from passive energy consumers to active grid assets, providing demand flexibility and energy elasticity while maintaining occupant comfort and health. This fundamental shift demands advanced optimal control methods to manage escalating energy demand and avert power outages. Reinforcement learning (RL) emerges as a promising method to address these challenges. Here, in this paper, we explore ten questions related to the application of RL in buildings, specifically targeting flexible energy management. We consider the growing availability of data, advancements in machine learning algorithms, open-source tools, and the practical deployment aspects associated with software and hardware requirements. Our objective is to deliver a comprehensive introduction to RL, present an overview of existing research and accomplishments, underscore the challenges and opportunities, and propose potential future research directions to expedite the adoption of RL for building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Real-time Distribution Simulation and Application Development for Power Systems Education

To help bridge the gap between traditional power system engineering instruction and emerging industry needs, a new set of classroom and research tools are needed. Real-time simulation tools emulating power system control room software present an opportunity to introduce students to the array of operational considerations, technical challenges, and decision-making associated with power system operations. The GridAPPS-D platform is proposed to support coursework and academic research as it provides an open-source platform for simulation, application development, and software integration. The GridAPPS-D platform, simulation capabilities, development environment, and interactive training are discussed in the context of lessons-learned from implementation for undergraduate and graduate students in the US and India. A series of potential GridAPPS-D supported academic capabilities are introduced.

Active distribution networks, open educational res↗

DOE OSTI2024

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗

DOE OSTI2022

Ch3MS-RF: a random forest model for chemical characterization and improved quantification of unidentified atmospheric organics detected by chromatography–mass spectrometry techniques

Abstract. The chemical composition of ambient organic aerosols plays a critical role in driving their climate and health-relevant properties and holds important clues to the sources and formation mechanisms of secondary aerosol material. In most ambient atmospheric environments, this composition remains incompletely characterized, with the number of identifiable species consistently outnumbered by those that have no mass spectral matches in the literature or the National Institute of Standards and Technology/National Institutes of Health/Environmental Protection Agency (NIST/NIH/EPA) mass spectral databases, making them nearly impossible to definitively identify. This creates significant challenges in utilizing the full analytical capabilities of techniques which separate and generate spectra for complex environmental samples. In this work, we develop the use of machine learning techniques to quantify and characterize novel, or unidentifiable, organic material. This work introduces Ch3MS-RF (Chemical Characterization by Chromatography–Mass Spectrometry Random Forest Modeling), an open-source, R-based software tool, for efficient machine-learning-enabled characterization of compounds separated in chromatography–mass spectrometry applications but not identifiable by comparison to mass spectral databases. A random forest model is trained and tested on a known 130 component representative external standard to predict the response factors of novel environmental organics based on position in volatility–polarity space and mass spectrum, enabling the reproducible, efficient, and optimized quantification of novel environmental species. Quantification accuracy on a reserved 20 % test set randomly split from the external standard compound list indicates that random forest modeling significantly outperforms the commonly used methods in both precision and accuracy, with a median response factor percent error of −2 %, for modeled response factors, compared to > 15 %, for typically used proxy assignment-based methods. Chemical properties modeling, evaluated on the same reserved 20 % test set and an extrapolation set of species identified in ambient organic aerosol samples collected in the Amazon rainforest, also demonstrate robust performance. Extrapolation set property prediction mean absolute errors for carbon number, oxygen to carbon ratio (O : C), average carbon oxidation state (OSc‾), and vapor pressure are 1.8, 0.15, 0.25, and 1.0 (log(atm)), respectively. Extrapolation set out-of-sample R2 for all properties modeled are above 0.75, with the exception of vapor pressure. While predictive performance for vapor pressure is less robust compared to the other chemical properties modeled, random-forest-based modeling was significantly more accurate than other commonly used methods of vapor pressure prediction, decreasing the mean vapor pressure prediction error to 0.24 (log(atm)) from 0.55 (log(atm)) (chromatography-based vapor pressure prediction) and 1.2 (log(atm)) (chemical formula-based vapor pressure prediction). The random forest model significantly advances an untargeted analysis of the full scope of chemical speciation yielded by two-dimensional gas chromatography (GCxGC-MS) techniques and can be applied to gas chromatography coupled with electron ionization mass spectrometry (GC-MS) as well. It enables the accurate estimation of key chemical properties commonly utilized in the atmospheric chemistry community, which may be used to more efficiently identify important tracers for further individual analysis and to characterize compound populations uniquely formed under specific ambient conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Produced water sharing: Improved economics and reduced community impact – A Pennsylvania case study

Here, hydraulic fracturing for oil and gas extraction from unconventional reservoirs is water intensive. Between water sourced for fracturing purposes and water present in rock formations, operators often produce a greater volume of water than oil or gas. Historically, this surplus of produced water has mainly been disposed of via deep injection wells. Rising disposal costs, seasonally limited water availability, and concerns over induced seismicity have incentivized produced water recycling practices, where an operator uses produced water for hydraulic fracturing operations. The logistical challenges associated with produced water recycling have also encouraged operators to adopt ad-hoc water exchange practices, in which competing operators will exchange produced water for mutual cost savings. In this paper, we investigate the potential benefit from systematic produced water exchange among operators in Northeastern Pennsylvania. We leverage PARETO, a free and open-source modeling framework for produced water management optimization, to quantify the benefits of water exchange practices. In an example drawn from FracFocus data, we find that the adoption of systematic water sharing could improve produced water recycling rates from 49.2% to 99%, decreasing operating and trucking costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

A Roadmap for a Lightning Modeling Grand Challenge

This document is a roadmap for building an interconnected model of the physical processes that produce a lightning discharge, and its observable optical and radio signals. We call this a Lightning Modeling Grand Challenge, recognizing that significant effort and coordination of human and financial resources is required to realize the capability. The roadmap serves to outline the coordination of resources necessary to enable stitching together existing knowledge and model components to make a lightning prediction, and to test these predictions with observations. Such a capability does not currently exist. The roadmap is motivated not only by a spirit of scientific inquiry, but by practical challenges faced by US Federal and societal stakeholders. Advancements in lightning observations have outpaced our tests of integrated understanding, leaving many stakeholders unsure how to design their missions to properly detect and discriminate lightning, and unsure how to apply the sometimes-disagreeing lightning signals from diverse instruments. The time is right to connect existing theories and models to support stakeholders in understanding the signals they observe, for needs as diverse as climate monitoring, national security, weather forecasting, public safety, and protection of natural and built environments. The roadmap’s two main technical sections describe the components of a linked physical model, followed by a description of models of lightning signals and sensors that are driven by outputs from the physical model. The goal is to predict the time-varying physical properties of lightning that are self-consistent with the thunderstorm’s structure and dynamics. These lightning signals then propagate through the storm, with realistic dispersion and attenuation, to receivers on the ground or in space. At a high level, the model begins with weather (cloud) model output, including explicit prediction of the electrification of cloud particles. The cloud’s electrical structure drives a model of lightning physics, from initiation, through channel development, and discharges along those channels. Key lightning parameters, such as the temperature and currents in the channel, and their space and time distribution, are then used to produce optical and electromagnetic signal sources that propagate to modeled receivers. This architecture therefore generates a dataset suitable for comparison to existing and envisioned observing systems. The need for additional measurements and field campaigns to support model development is described. In each model sub-component, inputs, outputs, uncertainties, evaluation methods, and next steps are summarized, interleaved with references to the scientific literature. Identifying boundaries between the model sub-components aids in segmenting an integrated, complex model into practical work packages and system sub-components, allowing a diverse team to contribute and maintain the system. We estimate that at least five years of effort and a $\$$10M initial investment is necessary to make a significant step forward. Mechanisms to facilitate community coordination, including annual workshops and open-source code repositories, are described.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Design and optimization of flexible decoupled high-temperature gas-cooled reactor plants with thermal energy storage

Advanced nuclear power plants are well-positioned for future zero-carbon grids, however, the need for flexible power generation will be required over the traditional emphasis on baseload generation for meeting historical demands. To achieve such flexibility, this work examines viable configurations for coupling nuclear energy production with thermal energy storage. Previous designs on nuclear-thermal energy storage configurations for advanced reactor designs, which utilized reactor steam as the heat source for charging the thermal energy storage, are restricted by the heat diversion ratio and efficiency losses, thus their impacts can be limited. In this context, this study proposes configurations for fully decoupling the nuclear reactor from the power cycle and positioning the storage as an intermediate loop, thereby achieving an unconstrained heat diversion ratio and improved efficiency. Compared with a standard high-temperature gas-cooled reactor’s power cycle, steady-state thermodynamic modeling and dispatch optimizations quantify the benefits of a steam reheat cycle within the fully decoupled thermal energy system to separate the plant cycle from the high-pressure primary side. These benefits are further detailed, compatible with required high-temperature and high-pressure conditions, through (1) open-source dynamic transient models that examine the impact of off-design operation on the systems, (2) the investigation of components design and costing and finally (3) sizing and dispatch optimization. The fully-decoupled design achieves a cycle efficiency of 43.1%, an enhancement over the vendor’s standard efficiency of 42.2% (Xe-100 design). Here, the proposed design offers strengthened physical barriers from the nuclear island as well as superior operational flexibility and power boosting. Dispatch optimization and market analysis reveal that thermal energy storage size is highly dependent on the peak patterns of electricity prices and the minimum generation level constraint imposed on the balance of plant. Evaluation of off-design operation demonstrates that the full decoupling design with the suggested fail-safe control mechanisms ensures a minimal impact on reactor parameters, even during rapid power ramping.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗

DOE OSTI2022

MULTIMARKET CONTROL AND OPERATION OF AN ADVANCED NUCLEAR REACTOR WITHIN AN INTEGRATED ENERGY PARK

Integrated energy systems (IES) are increasing in popularity and relevance given the heightened penetration of variable renewable energy sources. This variability is causing traditional baseload generators to reconsider their business cases as exclusively electrical generation stations and to instead consider ancillary products (e.g., hydrogen) to remain competitive in the current energy market. This work investigates the coupling, control, and overall viability of IES consisting of an advanced nuclear reactor coupled with a high-temperature steam electrolysis (HTSE) plant and hydrogen storage. The goal of such IES is to produce hydrogen without impacting reactor operations during periods of off-peak electricity demand and then sell electricity to the grid during periods of high demand. To accomplish this, a novel heat exchanger, control scheme, and coupling strategy were needed to ensure that the advanced nuclear power plant could make these transitions. Idaho National Laboratory’s open-source Framework for Optimization of Resources and Economics (FORCE) framework was used to develop novel coupling and control schemes that demonstrate the viability of multi-market operation of advanced nuclear reactors to produce both electricity and hydrogen. The results demonstrated the coupled IES could operate without impacting reactor systems while monetizing the electricity market and meeting all contractual hydrogen consumer demands.

08 HYDROGEN↗

DOE OSTI2022

LigninGraphs: lignin structure determination with multiscale graph modeling

Lignin is an aromatic biopolymer found in ubiquitous sources of woody biomass. Designing and optimizing lignin valorization processes requires a fundamental understanding of lignin structures. Experimental characterization techniques, such as 2D-heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectra, could elucidate the global properties of the polymer molecules. Computer models could extend the resolution of experiments by representing structures at the molecular and atomistic scales. We introduce a graph-based multiscale modeling framework for lignin structure generation and visualization. The framework employs accelerated rejection-free polymerization and hierarchical Metropolis Monte Carlo optimization algorithms. We obtain structure libraries for various lignin feedstocks based on literature and new experimental NMR data for poplar wood, pinewood, and herbaceous lignin. The framework could guide researchers towards feasible lignin structures, efficient space exploration, and future kinetics modeling. Its software implementation in Python, LigninGraphs, is open-source and available on GitHub.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗