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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Flaw Tolerance Assessment for DOE Standard SNF Dry Storage Canisters - 26550

The U.S. DOE has designed four spent nuclear fuel (SNF) dry storage canisters for storing DOE standardized SNFs. The DOE standard canisters are cylindrical shells with a diameter of 24 inches (610 m) or 18 inches (457 m), a wall thickness of 0.5 inches (12.7 m) or 0.375 inches (9.53 m), and a length of 15 feet (4.57 m) or 10 feet (3.05 m). These DOE canister geometries are completely different from commercial canisters. The latter may experience chloride-induced stress cracking corrosion (CI-SCC) because they are stored near coastal regions. The former may not experience CI-SCC but face different challenges because they are stored in the SNF storage facilities. Because of large residual stresses, mechanical flaws may occur in the DOE canisters during long-distance transportation or lifting handling. To date, only limited structural integrity analyses were carried out through drop tests on the DOE canisters, but a more general flaw tolerance assessment has not been performed. Therefore, the failure assessment diagram (FAD)-based fracture mechanics method, as codified by the latest API 579-1/ASME FFS-1-2021 Edition, is adopted in this work to assess surface flaw tolerance for DOE canisters under operation loading and welding residual stresses (WRS), where the new code-recommended WRS distributions are used. To more adequately consider the transverse distribution of WRS, an equivalent WRS distribution is proposed to account for the WRS reduction with distance from the weld centerline. Moreover, the closed-form solutions of stress intensity factor K, which serves as the crack driving force during subcritical crack growth, are developed from the tabular data of the K factors provided in API 579-1/ASME FFS-1 and used to determine more accurate flaw sizes at flaw instability. Subsequently, the Level 2 assessment procedures with 12 assessment steps, as codified and detailed in API 579-1 and ASME FFS-1, are followed to assess the flaw tolerance for the surface flaws in the DOE standard canisters with consideration of normal or accident operation loads combined with WRS. The assessment results show that the four designs of DOE standard canisters can tolerate all surface flaws that meet the code permitted maximum sizes of a flaw length of 8 inches (i.e., 200 mm) and a flaw depth of 80% wall thickness. This demonstrates that all designs of DOE standard canisters are robust and reliable.

DOE standard canister↗
DOE OSTI2024

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Further, our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

25 ENERGY STORAGE↗
DOE OSTI2022

Compositionally Tuning Electron Transfer from Photoexcited Core/Shell Quantum Dots via Cation Exchange

It is critical to find methods to control the thermodynamic driving force for photoexcited charge transfer from quantum dots (QDs) and explore how this affects charge transfer rates, since the efficiency of QD-based photovoltaic and photocatalysis technologies depends on both this rate and the associated energetic losses. In this work, we introduce a single-pot shell growth and Cu-catalyzed cation exchange method to synthesize Cd x Zn 1-x Se/Cd y Zn 1-y S QDs with tunable driving forces for electron transfer. Functionalizing them with two molecular electron acceptors—naphthalenediimide (NDI) and anthraquinone (AQ)—allowed us to probe nearly 1 eV of driving forces. For AQ, at lower driving forces, we find that higher Zn content results in a 130-fold increase of electron transfer rate constants. However, at higher driving forces electron transfer dynamics are unaltered. Here, the data are understood using an Auger-assisted electron transfer model and analyzed with computational work to determine approximate binding geometries of these electron acceptors. Our work provides a method to tune QD reducing power and produces useful metrics for optimizing QD charge transfer systems that maximize rates of electron transfer while minimizing energetic losses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Assessing the National Off-Cycle Benefits of 2-Layer HVAC Technology Using Dynamometer Testing and a National Simulation Framework

Some CO2-reducing technologies have real-world benefits not captured by regulatory testing methods. This paper documents a two-layer heating, ventilation, and air-conditioning (HVAC) system that facilitates faster engine warmup through strategic increased air recirculation. The performance of this technology was assessed on a 2020 Hyundai Sonata. Empirical performance of the technology was obtained through dynamometer tests at Argonne National Laboratory. Performance of the vehicle across multiple cycles and cell ambient temperatures with the two-layer technology active and inactive indicated fuel consumption reduction in nearly all cases. A thermally sensitive powertrain model, the National Renewable Energy Laboratory's FASTSim Hot, was calibrated and validated against vehicle testing data. The developed model included the engine, cabin, and HVAC system controls. Validation of component thermal models and engine efficiency ensured accurate thermal dynamics, fuel consumption, and two-layer benefit. The real-world benefit of the two-layer technology was calculated by simulating the validated powertrain model across a representative test matrix comparing performance with and without the two-layer system. Simulation across the test matrix revealed a real-world representative benefit of 0.0835%. Analysis of test matrix results at the regional level revealed the most benefit in cold climates and rural regions. Mean results across cycle length sensitivity simulations revealed a larger real-world benefit of 0.0872%. These benefit values can be considered a more accurate assessment of real-world technology performance. Future work is planned to explore the requisite number of drive cycles to ensure the full technology benefit is captured.

2-layer↗
DOE OSTI2016

Progress in Monitoring Strategies for Risk Reduction in Geologic CO2 Storage

Abstract: This geophysical monitoring review is intended to lay the ground work for an approach to integrating monitoring strategies with risk assessment and risk reduction and to summarize work conducted by U.S. Department of Energy's National Risk Assessment Partnership (NRAP) participants that addresses key questions related to monitoring strategies. Commercial, demonstration and pilot geologic CO2 storage (GCS) projects have provided a wealth of practical experience in monitoring technologies. In this manuscript we review a few key projects, specific geophysical methods, well-based methods, geophysical workflows and some suggested best practices. These practices are often driven and governed by regulatory requirements (e.g. U.S. Environmental Protection Agency [US-EPA] Class VI underground injection regulation) and the need for effective reservoir management of pressures and volumes as well as the site-specific risks to containment, plume migration, and underground sources of drinking water. Reducing uncertainty in monitoring is likely to lead to reducing uncertainty in risk. One of our conclusions is the need for field experiment testing that is risk-driven. It is notable that GCS pilot projects have been designed for safe storage, and to date they have been successful. Technical challenges at all geologic CO2 storage sites include assuring injectivity and capacity predictions are reliable, the fate and subsurface topology of the CO2 plume is acceptable, regulatory permitting and compliance are accomplished in a timely manner, needed business assurances are supported by quantitative technical data, and the storage operation is acceptable to stakeholders. There is risk associated with all of these challenges necessitating a monitoring program utilizing both direct and indirect monitoring methods. Because of the direct association of risk and monitoring in GCS, geophysical monitoring is viewed as a key component in approaching risk assessment. To address monitoring in the context of risk assessment the U.S. Department of Energy's National Risk Assessment Partnership (NRAP) has undertaken a review of work related to monitoring storage sites. In this review we provide a framework for monitoring and then present some specific monitoring tools that may be useful for regulatory compliance, as well as technologies that are applicable to leakage detection.

Harbert, William↗
DOE OSTI2024

Weak-form latent space dynamics identification

Recent work in data-driven modeling has demonstrated that a weak formulation of model equations enhances the noise robustness of a wide range of computational methods. In this paper, we demonstrate the power of the weak form to enhance the LaSDI (Latent Space Dynamics Identification) algorithm, a recently developed data-driven reduced order modeling technique. We introduce a weak form-based version WLaSDI (Weak-form Latent Space Dynamics Identification). WLaSDI first compresses data, then projects onto the test functions and learns the local latent space models. Notably, WLaSDI demonstrates significantly enhanced robustness to noise. With WLaSDI, the local latent space is obtained using weak-form equation learning techniques. Compared to the standard sparse identification of nonlinear dynamics (SINDy) used in LaSDI, the variance reduction of the weak form guarantees a robust and precise latent space recovery, hence allowing for a fast, robust, and accurate simulation. We demonstrate the efficacy of WLaSDI vs. LaSDI on several common benchmark examples including viscid and inviscid Burgers', radial advection, and heat conduction. For instance, in the case of 1D inviscid Burgers' simulations with the addition of up to 100% Gaussian white noise, the relative error remains consistently below 6% for WLaSDI, while it can exceed 10,000% for LaSDI. Similarly, for radial advection simulations, the relative errors stay below 15% for WLaSDI, in stark contrast to the potential errors of up to 10,000% with LaSDI. Moreover, speedups of several orders of magnitude can be obtained with WLaSDI. For example applying WLaSDI to 1D Burgers' yields a 140X speedup compared to the corresponding full order model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

How Bayesian methods can improve R -matrix analyses of data: The example of the d t reaction

The 3 H(d, n) 4 He reaction is of significant interest in nuclear astrophysics and nuclear applications. It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors. We use one- and two-level R-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV. We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point un- certainties. We use Markov Chain Monte Carlo sampling to evaluate this R-matrix-plus-statistical model and find two-level R-matrix results that are stable with respect to variations in the channel radii. The S factor at 40 keV evaluates to 25.36(19) MeV b (68% credibility interval). We discuss our Bayesian analysis in detail and provide guidance for future applications of Bayesian methods to R-matrix analyses. We also discuss possible paths to further reduction of the S-factor uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Transfer learning for metamaterial design and simulation

Abstract We demonstrate transfer learning as a tool to improve the efficacy of training deep learning models based on residual neural networks (ResNets). Specifically, we examine its use for study of multi-scale electrically large metasurface arrays under open boundary conditions in electromagnetic metamaterials. Our aim is to assess the efficiency of transfer learning across a range of problem domains that vary in their resemblance to the original base problem for which the ResNet model was initially trained. We use a quasi-analytical discrete dipole approximation (DDA) method to simulate electrically large metasurface arrays to obtain ground truth data for training and testing of our deep neural network. Our approach can save significant time for examining novel metasurface designs by harnessing the power of transfer learning, as it effectively mitigates the pervasive data bottleneck issue commonly encountered in deep learning. We demonstrate that for the best case when the transfer task is sufficiently similar to the target task, a new task can be effectively trained using only a few data points yet still achieve a test mean absolute relative error of 3 % with a pre-trained neural network, realizing data reduction by a factor of 1000.

Peng, Rixi↗
DOE OSTI2012

An efficient modeling method for thermal stratification simulation in a BWR suppression pool

The suppression pool in a BWR plant not only is the major heat sink within the containment system, but also provides major emergency cooling water for the reactor core. In several accident scenarios, such as LOCA and extended station blackout, thermal stratification tends to form in the pool after the initial rapid venting stage. Accurately predicting the pool stratification phenomenon is important because it affects the peak containment pressure; and the pool temperature distribution also affects the NPSHa (Available Net Positive Suction Head) and therefore the performance of the pump which draws cooling water back to the core. Current safety analysis codes use 0-D lumped parameter methods to calculate the energy and mass balance in the pool and therefore have large uncertainty in prediction of scenarios in which stratification and mixing are important. While 3-D CFD methods can be used to analyze realistic 3D configurations, these methods normally require very fine grid resolution to resolve thin substructures such as jets and wall boundaries, therefore long simulation time. For mixing in stably stratified large enclosures, the BMIX++ code has been developed to implement a highly efficient analysis method for stratification where the ambient fluid volume is represented by 1-D transient partial differential equations and substructures such as free or wall jets are modeled with 1-D integral models. This allows very large reductions in computational effort compared to 3-D CFD modeling. The POOLEX experiments at Finland, which was designed to study phenomena relevant to Nordic design BWR suppression pool including thermal stratification and mixing, are used for validation. GOTHIC lumped parameter models are used to obtain boundary conditions for BMIX++ code and CFD simulations. Comparison between the BMIX++, GOTHIC, and CFD calculations against the POOLEX experimental data is discussed in detail.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

In Situ Synthesis of Uranium Carbide and its High Temperature Cubic Phase

New in situ data for the U-C system are presented, with the goal of improving knowledge of the phase diagram to enable production of new ceramic fuels. The none quenchable, cubic, δ-phase, which in turn is fundamental to computational methods, was identified. Rich datasets of the formation synthesis of uranium carbide yield kinetics data which allow the benchmarking of modeling, thermodynamic parameters etc. The order-disorder transition (carbon sublattice melting) was observed due to equal sensitivity of neutrons to both elements. This dynamic has not been accurately described in some recent simulation-based publications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Validation of a virtual source model for Monte Carlo dose calculations of a flattening filter free linac

Purpose: A linac delivering intensity-modulated radiotherapy (IMRT) can benefit from a flattening filter free (FFF) design which offers higher dose rates and reduced accelerator head scatter than for conventional (flattened) delivery. This reduction in scatter simplifies beam modeling, and combining a Monte Carlo dose engine with a FFF accelerator could potentially increase dose calculation accuracy. The objective of this work was to model a FFF machine using an adapted version of a previously published virtual source model (VSM) for Monte Carlo calculations and to verify its accuracy. Methods: An Elekta Synergy linear accelerator operating at 6 MV has been modified to enable irradiation both with and without the flattening filter (FF). The VSM has been incorporated into a commercially available treatment planning system (Monaco Trade-Mark-Sign v 3.1) as VSM 1.6. Dosimetric data were measured to commission the treatment planning system (TPS) and the VSM adapted to account for the lack of angular differential absorption and general beam hardening. The model was then tested using standard water phantom measurements and also by creating IMRT plans for a range of clinical cases. Results: The results show that the VSM implementation handles the FFF beams very well, with an uncertainty between measurement and calculation of <1% which is comparable to conventional flattened beams. All IMRT beams passed standard quality assurance tests with >95% of all points passing gamma analysis ({gamma} < 1) using a 3%/3 mm tolerance. Conclusions: The virtual source model for flattened beams was successfully adapted to a flattening filter free beam production. Water phantom and patient specific QA measurements show excellent results, and comparisons of IMRT plans generated in conventional and FFF mode are underway to assess dosimetric uncertainties and possible improvements in dose calculation and delivery.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Consistent Estimation of Gibbs Energy Using Component Contributions

Standard Gibbs energies of reactions are increasingly being used in metabolic modeling for applying thermodynamic constraints on reaction rates, metabolite concentrations and kinetic parameters. The increasing scope and diversity of metabolic models has led scientists to look for genome-scale solutions that can estimate the standard Gibbs energy of all the reactions in metabolism. Group contribution methods greatly increase coverage, albeit at the price of decreased precision. We present here a way to combine the estimations of group contribution with the more accurate reactant contributions by decomposing each reaction into two parts and applying one of the methods on each of them. This method gives priority to the reactant contributions over group contributions while guaranteeing that all estimations will be consistent, i.e. will not violate the first law of thermodynamics. We show that there is a significant increase in the accuracy of our estimations compared to standard group contribution. Specifically, our cross-validation results show an 80% reduction in the median absolute residual for reactions that can be derived by reactant contributions only. We provide the full framework and source code for deriving estimates of standard reaction Gibbs energy, as well as confidence intervals, and believe this will facilitate the wide use of thermodynamic data for a better understanding of metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Stabilization of Residual Contamination with Alternative Materials - 19404

Since 2015, Savannah River National Laboratory (SRNL) in conjunction with Florida International University (FIU) have been investigating the applicability of intumescent coatings as radiological contamination fixatives for stabilization of residual materials after decontamination efforts have concluded. Intumescent coatings are designed to prevent heat transfer to a protected substrate and are typically used in both the aerospace industry to protect components from thermal shock and in building design to protect building joints that may fail in the event of a fire. For this work, these materials are examined for their ability to reduce worker risk by fixating residual contamination and lower the impact of a release in a scenario that breaches containment of a contaminated building and subsequently induces a large-scale fire by crediting their fire-retardant attributes. Initial studies of intumescent coatings and commercial fixatives included performance in direct flame, varied environmental conditions (20-110 F or -6.67 C, 10-95% relative humidity), adhesion studies to stainless steel after curing in varied environmental conditions, and radiological exposure. Of all the materials tested, many were found to be inadequate in one or more of these areas. These materials failed in one or more of three characteristic ways: 1) through delamination at reduced temperatures (≤40 F or 4.44 C) or from even moderate handling, 2) melting off the substrate at elevated temperatures (≥90 F or 32.22 C), 3) proving to be flammable and promote smoke propagation. Failure in these ways results in the potential for a subsequent release of the fixated contamination in the event of water presence/absence or direct flame. Using these results as a platform for the best in class identified material that did not experience failure in any of these tests, SRNL and FIU targeted the plutonium-238 contaminated hot cells within Savannah River Site (SRS) Building 235-F as a characteristic test bed to benchmark an intumescent coating used as a contaminant fixative. Through discussion with the SRS 235-F Risk Reduction personnel, appropriate hazards and performance metrics were discussed and a cold demonstration was performed in a hot cell mockup located at SRS. The application methods were proven functional in the cold mock up, and these intumescent coatings were subsequently utilized in the Savannah River Site Building 235-F's Plutonium Fuel Form (PuFF) Facility to aid in stabilization of plutonium-238 in both a contaminated hot cell and Entry Hood in September 2018. Presented in this work is the overview of the application process, associated working considerations for introduction of equipment and materials into the facility, lessons learned, and lifetime monitoring data to date. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

SU-C-BRB-01: Automated Dose Deformation for Re-Irradiation

Purpose: An objective of retreatment planning is to minimize dose to previously irradiated tissues. Conventional retreatment planning is based largely on best-guess superposition of the previous treatment’s isodose lines. In this study, we report a rigorous, automated retreatment planning process to minimize dose to previously irradiated organs at risk (OAR). Methods: Data for representative patients previously treated using helical tomotherapy and later retreated in the vicinity of the original disease site were retrospectively analyzed in an automated fashion using a prototype treatment planning system equipped with a retreatment planning module (Accuray, Inc.). The initial plan’s CT, structures, and planned dose were input along with the retreatment CT and structure set. Using a deformable registration algorithm implemented in the module, the initially planned dose and structures were warped onto the retreatment CT. An integrated third-party sourced software (MIM, Inc.) was used to evaluate registration quality and to contour overlapping regions between isodose lines and OARs, providing additional constraints during retreatment planning. The resulting plan and the conventionally generated retreatment plan were compared. Results: Jacobian maps showed good quality registration between the initial plan and retreatment CTs. For a right orbit case, the dose deformation facilitated delineating the regions of the eyes and optic chiasm originally receiving 13 to 42 Gy. Using these regions as dose constraints, the new retreatment plan resulted in V50 reduction of 28% for the right eye and 8% for the optic chiasm, relative to the conventional plan. Meanwhile, differences in the PTV dose coverage were clinically insignificant. Conclusion: Automated retreatment planning with dose deformation and definition of previously-irradiated regions allowed for additional planning constraints to be defined to minimize re-irradiation of OARs. For serial organs that do not recover from radiation damage, this method provides a more precise and quantitative means to limit cumulative dose. This research is partially supported by Accuray, Inc.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A 1D–0D–3D coupled model for simulating blood flow and transport processes in breast tissue

In this work, we present mixed dimensional models for simulating blood flow and transport processes in breast tissue and the vascular tree supplying it. These processes are considered, to start from the aortic inlet to the capillaries and tissue of the breast. Large variations in biophysical properties and flow conditions exist in this system necessitating the use of different flow models for different geometries and flow regimes. In total, we consider four different model types. First, a system of 1D nonlinear hyperbolic partial differential equations (PDEs) is considered to simulate blood flow in larger arteries with highly elastic vessel walls. Second, we assign 1D linearized hyperbolic PDEs to model the smaller arteries with stiffer vessel walls. The third model type consists of ODE systems (0D models). It is used to model the arterioles and peripheral circulation. Finally, homogenized 3D porous media models are considered to simulate flow and transport in capillaries and tissue within the breast volume. Sink terms are used to account for the influence of the venous and lymphatic systems. Combining the four model types, we obtain two different 1D–0D–3D coupled models for simulating blood flow and transport processes: The first model results in a fully coupled 1D–0D–3D model covering the complete path from the aorta to the breast combining a generic arterial network with a patient specific breast network and geometry. The second model is a reduced one based on the separation of the generic and patient specific parts. The information from a calibrated fully coupled model is used as inflow condition for the patient specific sub-model allowing a significant computational cost reduction. Several numerical experiments are conducted to calibrate the generic model parameters and to demonstrate realistic flow simulations compared to existing data on blood flow in the human breast and vascular system. Moreover, we use two different breast vasculature and tissue data sets to illustrate the robustness of our reduced sub-model approach.

multiscale blood flow models↗
DOE OSTI2022

Data for Solvent-Free Enzymatic Esterification of Free Fatty Acids with Glycerol for Biodiesel Application: Optimized Using the Taguchi Experimental Method

Presence of free fatty acids along with glycerides poses a technical difficulty for biodiesel production. This work used a Taguchi L9 design to optimize the solvent-free enzymatic process to result in the esterification of oleic acid with glycerol. Under optimal conditions the esterification reaction temperature of 60°C, enzyme dose of 5 wt%, glycerol: oleic acid molar ratio of 5:1, and reaction time of 3 h, a 75.235 ± 2.19% conversion of oleic acid to esters was achieved. With the addition of molecular sieves, the conversion increased to 86.73% ± 1.09%. However, using the parameters predicted by Taguchi design (60°C, 5 wt%, 5:1, and 4.5 h), 88.5% ± 1.11% of oleic acid could be converted to esters derivative. Diglycerides were the major product, and the reaction equilibrium was attained after 4 h. The immobilized enzyme could be used up to seven times with only a 10% reduction in the conversion. Thus, the process can efficiently reduce the free fatty acid content of oil to make it suitable for biodiesel production.

Conversion↗
DOE OSTI2014

Proton-Coupled Electron Transfer in Molecular Electrocatalysis: Theoretical Methods and Design Principles

Molecular electrocatalysts play an essential role in a wide range of energy conversion processes. The objective of electrocatalyst design is to maximize the turnover frequency and minimize the overpotential for the overall catalytic cycle. Typically the catalytic cycle is dominated by key proton-coupled electron transfer (PCET) processes comprised of sequential or concerted electron transfer and proton transfer steps. A variety of theoretical methods have been developed to investigate the mechanisms, thermodynamics, and kinetics of PCET processes in electrocatalytic cycles. Electronic structure methods can be used to calculate the reduction potentials and pKa’s and to generate thermodynamic schemes, free energy reaction pathways, and Pourbaix diagrams, which indicate the most stable species at each pH and potential. These types of calculations have assisted in identifying the thermodynamically favorable mechanisms under specified experimental conditions, such as acid strength and overpotential. Such calculations have also revealed linear correlations among the thermodynamic properties, which can be used to predict the impact of modifying the ligand, substituents, or metal center. The role of non-innocent ligands, namely ligand protonation or reduction, has also been examined theoretically. In addition, the rate constants for electron and proton transfer reactions, as well as concerted PCET reactions, have been calculated to investigate the kinetics of molecular electrocatalysts. The concerted PCET mechanism is thought to lower the overpotential required for catalysis by avoiding high-energy intermediates. Rate constant calculations have revealed that the concerted mechanism involving intramolecular proton transfer will be favored by designing more flexible ligands that facilitate the proton donor-acceptor motion while also maintaining a sufficiently short equilibrium proton donor-acceptor distance. Overall, theoretical methods have assisted in the interpretation of experimental data and the design of more effective molecular electrocatalysts. The research on the Ni(P2N2)2 catalysts was supported as part of the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences.

Solis, Brian H.↗
DOE OSTI2020

Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences

Data science has primarily focused on big data, but for many physics, chemistry, and engineering applications, data are often small, correlated and, thus, low dimensional, and sourced from both computations and experiments with various levels of noise. Typical statistics and machine learning methods do not work for these cases. Expert knowledge is essential, but a systematic framework for incorporating it into physics-based models under uncertainty is lacking. Here, we develop a mathematical and computational framework for probabilistic artificial intelligence (AI)–based predictive modeling combining data, expert knowledge, multiscale models, and information theory through uncertainty quantification and probabilistic graphical models (PGMs). We apply PGMs to chemistry specifically and develop predictive guarantees for PGMs generally. Our proposed framework, combining AI and uncertainty quantification, provides explainable results leading to correctable and, eventually, trustworthy models. The proposed framework is demonstrated on a microkinetic model of the oxygen reduction reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗