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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

β decay of Ba 141

The β-decay strength function of nuclides produced in fission is important as it dictates the distribution of decay energy between electrons, neutrinos, and γ rays and so is critical for calculating decay heat in reactors and for estimating the reactor antineutrino spectrum. Several experimental techniques are available to determine this strength function, including electron spectroscopy, γ-ray calorimetry (TAGS spectroscopy), and detailed, high-resolution spectroscopy with modern large high-purity germanium arrays. This work investigates the decay of the well-known and strongly produced fission fragment 141 Ba. A beam of 141 Cs was implanted at the target position of the Gammasphere and the subsequent decay of the daughter 141 Ba was studied. Extensive decay spectroscopy was possible up to the decay Q value of 3.197(7) MeV, including a significant extension of the level scheme and detailed angular correlation measurements for all levels with greater than 0.25% β feeding. The distribution of the β-decay strength was then inferred and compared to previous calorimetric studies. In conclusion, the agreement was excellent and provides a benchmark for comparing strength function methods and data for a more detailed understanding of the structure of 141 La.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A phase-field model of quasi-brittle fracture for pressurized cracks: Application to UO 2 high-burnup microstructure fragmentation

Here, in this paper, we present a phase-field model of quasi-brittle fracture with pressurized cracks, with dedicated applications for polycrystalline materials. The model is formulated as a minimization problem within the variational framework. The external work done by pressure on the crack surfaces is included in the objective function. Several careful modeling choices lead to a regularization-length-independent critical strength. The model is constructed to give a softening response with an underlying linear traction-separation law. The pressure-dependent softening response and the regularization of the prescribed pressure are demonstrated with a (quasi) one-dimensional numerical analysis. In a two-dimensional numerical analysis under plane strain assumptions, the critical stress corresponding to crack propagation (as predicted by our quasi-brittle fracture model) is compared with linear elastic fracture mechanics (LEFM) analytical solutions. Our model is further utilized to simulate fission-gas-induced fragmentation of the UO 2 high-burnup structure (HBS). Simulation results show that pressurized bubbles can cause crack nucleation and propagation, and that the bubble size and the surrounding external pressure affect the critical pressure corresponding to crack nucleation. Simulations of a partial HBS at different recrystallization stages show that different grain structures (due to recrystallization) also influence crack paths and fragmentation morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiplicity and event-scale dependent flow and jet fragmentation in pp collisions at $\sqrt{s}$ = 13 TeV and in p–Pb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV

Long- and short-range correlations for pairs of charged particles are studied via two-particle angular correlations in pp collisions at $\sqrt{s}$ = 13 TeV and p–Pb collisions at $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV. The correlation functions are measured as a function of relative azimuthal angle Δφ and pseudorapidity separation Δη for pairs of primary charged particles within the pseudorapidity interval |η| < 0.9 and the transverse-momentum interval 1 < p T < 4 GeV/c. Flow coefficients are extracted for the long-range correlations (1.6 < |Δη| < 1.8) in various high-multiplicity event classes using the low-multiplicity template ft method. The method is used to subtract the enhanced yield of away-side jet fragments in high-multiplicity events. These results show decreasing flow signals toward lower multiplicity events. Furthermore, the flow coefficients for events with hard probes, such as jets or leading particles, do not exhibit any significant changes compared to those obtained from high-multiplicity events without any specific event selection criteria. The results are compared with hydrodynamic-model calculations, and it is found that a better understanding of the initial conditions is necessary to describe the results, particularly for low-multiplicity events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Conductive Liquid Metal Vitrimer Composites for Reconfigurable and Recyclable Flexible Electronics

Liquid metal (LM) elastomer composites exhibit excellent functionality for stretchable electronics and wearables, but limited recycling and reuse pathways constrain their sustainable use. Here, to address these challenges amid growing concerns over electronic waste, a conductive LM–vitrimer composite is presented that enables recyclable and reconfigurable electronics. This soft and stretchable composite features uniformly distributed LM inclusions that enhance thermal conductivity by 6.53× and enable the formation of conductive traces with electrical self-healing, while the vitrimer provides structural restoration. The dynamic covalent bonds of the vitrimer matrix are leveraged for both reprocessing the composite and chemically recovering 94% of the LM. This liquid-state filler slightly reduces the vitrimer's stiffness to 2.63 MPa (≈20% lower), while maintaining its high stretchability (>135% strain) and thermal stability. It is further examined how ultrasonicated LM inclusions interact with the vitrimer matrix and demonstrate the composite's self-healing and recyclability through two distinct approaches: 1) thermomechanical reprocessing, which restores fragmented composites under heat and compression for circuit reconfiguration; and 2) chemical recycling, which recovers the embedded LM for reuse in fabricating new composites and redesigned circuitry. With the integration of recyclability and diverse functional capabilities, LM–vitrimer composites emerge as a promising material platform for sustainable, flexible electronics.

Han, Youngshang [Univ. of Washington, Seattle, WA ↗
DOE OSTI2023

Reaction nanoscopy of ion emission from sub-wavelength propanediol droplets

Abstract Droplets provide unique opportunities for the investigation of laser-induced surface chemistry. Chemical reactions on the surface of charged droplets are ubiquitous in nature and can provide critical insight into more efficient processes for industrial chemical production. Here, we demonstrate the application of the reaction nanoscopy technique to strong-field ionized nanodroplets of propanediol (PDO). The technique’s sensitivity to the near-field around the droplet allows for the in-situ characterization of the average droplet size and charge. The use of ultrashort laser pulses enables control of the amount of surface charge by the laser intensity. Moreover, we demonstrate the surface chemical sensitivity of reaction nanoscopy by comparing droplets of the isomers 1,2-PDO and 1,3-PDO in their ion emission and fragmentation channels. Referencing the ion yields to gas-phase data, we find an enhanced production of methyl cations from droplets of the 1,2-PDO isomer. Density functional theory simulations support that this enhancement is due to the alignment of 1,2-PDO molecules on the surface. The results pave the way towards spatio-temporal observations of charge dynamics and surface reactions on droplets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Second Report of the Nuclear Data Subcommittee of the Nuclear Science Advisory Committee

The central importance of the nuclear data curated by the US Nuclear Data Program (USNDP) for clean energy generation, national security, nonproliferation, medical applications, and space exploration as well as basic science was described in a prior report issued by the DOE/NSF Nuclear Science Advisory Committee subcommittee on Nuclear Data (NSAC-ND) in September 2022. In this report, we present a set of fourteen (14) recommendations that will enhance and advance DOE-NP's stewardship of nuclear data. The first three recommendations focus on the existing core USNDP capabilities, namely: 1) Support the nuclear structure evaluation workforce to improve the currency, consistency, and accessibility of the Evaluated Nuclear Structure Data File (ENSDF); 2) Enhance nuclear reaction evaluation within the USNDP in support of the Evaluated Nuclear Data File (ENDF) through expansion of the workforce and integration of high-performance computing, automation, and machine learning and; 3) Continue atomic mass evaluation in support AME and NUBASE databases. This is followed by eight (8) recommendations representing new cross-cutting initiatives involving both measurement and evaluation to address outstanding nuclear data needs. These new initiatives require a highly trained, diverse workforce that includes personnel with expertise from both inside and outside the nuclear physics community from which evaluators have traditionally been recruited. As such, many of these initiatives are accomplished via a Topical Nuclear Data Collaborations (TNDC). A TNDC is made up of domestic and international stakeholders, subject matter and nuclear data experts, and nuclear data evaluators and features a workforce development plan to ensure that nuclear data evaluators maintain currency in the relevant applications and are seen as equity partners in the endeavor. These include: 1) Establish a coordinated effort to improve evaluation and modeling in nuclear astrophysics for stellar dynamics, multi-messenger astronomy and nucleosynthesis; 2) Initiate a TNDC to develop and maintain nuclear structure evaluation beyond discrete states, including nuclear level densities, photon strength functions and photonuclear data for improved reaction modeling, and exploring nuclear structure at finite temperature; 3) Create a TNDC to perform correlated fission data evaluation, including cross sections, fragment yields, v(A), v(E n ) for nuclear energy, national security, nonproliferation and basic science; 4) From a panel of subject matter experts to establish and annually update a roster of key decay data to nurture its accelerated dissemination including both measurement and evaluation for targeted high-value nuclides for national security, nonproliferation and medical applications; 5) Comprehensive, consistent neutron-induced structure and reaction data for nuclear energy, national security, nonproliferation and planetary nuclear spectroscopy; 6) Charged-particle stopping powers for detector design, space effects and ion beam therapy; 7) High-energy reactions for space exploration and medical nuclide production, and; 8) The creation of an infrastructure for open data and data preservation for use by the entire nuclear physics community. All told, these initiatives require approximately $6.5M increase in NP support of the USNDP in fiscal year 2023 dollars and would require at least 3-5 years to carry out due to the length of time needed to recruit and train new nuclear data researchers. This relatively modest investment would help ensure that the fruits of the nuclear data research carried out by DOE-NP and its collaborators would be brought to bear to address some of the most important needs of our nation and the world. To ensure effective execution of this plan, we present an overview of recruitment, training, and retention goals for the USNDP, the centerpiece of which is a mutually agreed upon code of conduct. Finally, we identify the facility and instrumentation needed to perform the recommended experimental activities. This includes a short review of target fabrication capabilities, reactors, neutron beam, light- and heavy-stable ion, gamma-ray, high-energy and radioactive ion beam facilities. Lastly, a more complete appendix of experimental facilities previously compiled is included with new input provided for 6 facilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Molecular mechanism of active Cas7-11 in processing CRISPR RNA and interfering target RNA

Cas7-11 is a Type III-E CRISPR Cas effector that confers programmable RNA cleavage and has potential applications in RNA interference. Cas7-11 encodes a single polypeptide containing four Cas7- and one Cas11-like segments that obscures the distinction between the multi-subunit Class 1 and the single-subunit Class-2 CRISPR Cas systems. We report a cryo-EM (cryo-electron microscopy) structure of the active Cas7-11 from Desulfonema ishimotonii (DiCas7-11) that reveals the molecular basis for RNA processing and interference activities. DiCas7-11 arranges its Cas7- and Cas11-like domains in an extended form that resembles the backbone made up by four Cas7 and one Cas11 subunits in the multi-subunit enzymes. Unlike the multi-subunit enzymes, however, the backbone of DiCas7-11 contains evolutionarily different Cas7 and Cas11 domains, giving rise to their unique functionality. The first Cas7-like domain nearly engulfs the last 15 direct repeat nucleotides in processing and recognition of the CRISPR RNA, and its free-standing fragment retains most of the activity. Both the second and the third Cas7-like domains mediate target RNA cleavage in a metal-dependent manner. The structure and mutational data indicate that the long variable insertion to the fourth Cas7 domain has little impact on RNA processing or targeting, suggesting the possibility for engineering a compact and programmable RNA interference tool.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Tempering stochastic density functional theory

Here, we introduce a tempering approach with stochastic density functional theory (sDFT), labeled t-sDFT, which reduces the statistical errors in the estimates of observable expectation values. This is achieved by rewriting the electronic density as a sum of a "warm" component complemented by "colder" correction(s). Since the warm component is larger in magnitude but faster to evaluate, we use many more stochastic orbitals for its evaluation than for the smaller-sized colder correction(s). This results in a significant reduction in the statistical fluctuations and systematic deviation compared to sDFT for the same computational effort. We demonstrate the method's performance on large hydrogen-passivated silicon nanocrystals, finding a reduction in the systematic deviation in the energy by more than an order of magnitude, while the systematic deviation in the forces is also quenched. Similarly, the statistical fluctuations are reduced by factors of ≈4-5 for the total energy and ≈1.5-2 for the forces on the atoms. Since the embedding in t-sDFT is fully stochastic, it is possible to combine t-sDFT with other variants of sDFT such as energy-window sDFT and embedded-fragmented sDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Fine resolution remote sensing spectra improves estimates of gross primary production of croplands

Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17A2H V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Here, replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Early Drug Discovery and Development of Novel Cancer Therapeutics Targeting DNA Polymerase Eta (POLH)

Polymerase eta (or Pol η or POLH) is a specialized DNA polymerase that is able to bypass certain blocking lesions, such as those generated by ultraviolet radiation (UVR) or cisplatin, and is deployed to replication foci for translesion synthesis as part of the DNA damage response (DDR). Inherited defects in the gene encoding POLH (a.k.a., XPV) are associated with the rare, sun-sensitive, cancer-prone disorder, xeroderma pigmentosum, owing to the enzyme’s ability to accurately bypass UVR-induced thymine dimers. In standard-of-care cancer therapies involving platinum-based clinical agents, e.g., cisplatin or oxaliplatin, POLH can bypass platinum-DNA adducts, negating benefits of the treatment and enabling drug resistance. POLH inhibition can sensitize cells to platinum-based chemotherapies, and the polymerase has also been implicated in resistance to nucleoside analogs, such as gemcitabine. POLH overexpression has been linked to the development of chemoresistance in several cancers, including lung, ovarian, and bladder. Co-inhibition of POLH and the ATR serine/threonine kinase, another DDR protein, causes synthetic lethality in a range of cancers, reinforcing that POLH is an emerging target for the development of novel oncology therapeutics. Using a fragment-based drug discovery approach in combination with an optimized crystallization screen, we have solved the first X-ray crystal structures of small novel drug-like compounds, i.e., fragments, bound to POLH, as starting points for the design of POLH inhibitors. The intrinsic molecular resolution afforded by the method can be quickly exploited in fragment growth and elaboration as well as analog scoping and scaffold hopping using medicinal and computational chemistry to advance hits to lead. An initial small round of medicinal chemistry has resulted in inhibitors with a range of functional activity in an in vitro biochemical assay, leading to the rapid identification of an inhibitor to advance to subsequent rounds of chemistry to generate a lead compound. Importantly, our chemical matter is different from the traditional nucleoside analog-based approaches for targeting DNA polymerases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Revealing the Reaction Path of UVC Bond Rupture in Cyclic Disulfides with Ultrafast X-ray Scattering

Disulfide bonds are ubiquitous molecular motifs that influence the tertiary structure and biological functions of many proteins. Yet it is well known that the disulfide bond is photolabile when exposed to UVC radiation. The deep-UV induced S-S bond fragmentation kinetics on very fast time scales are especially pivotal to fully understand the photostability and photodamage repair mechanisms in proteins. In 1,2-dithiane, the smallest saturated cyclic molecule that mimics biologically active species with S-S bonds, we investigate the photochemistry upon 200 nm excitation by femtosecond time-resolved X-ray scattering in the gas phase using an X-ray free electron laser. In the femtosecond time domain, we discover a very fast reaction that generates molecular fragments with one and two sulfur atoms. On picosecond and nanosecond timescales, a complex network of reactions unfolds that, ultimately, completes the sulfur dissociation from the parent molecule.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

SARS-CoV-2 variant nanobodies and constructs comprising such nanobodies

A large and highly diverse nanobody library was constructed and screened against multiple variants of SARS-COV-2 to find nanobodies with high sensitivity and specificity for the variants. Four rounds of positive selection against a panel of six diverse SARS-COV-2 variant RBDs was performed with our high-diversity. At least 59 of these nanobodies were found to work well against Alpha, Beta, Gamma, Delta, Kappa, Lambda and Mu with some overlap efficacy against other variants. These nanobodies have efficacy as stand-alone nanobodies and as a construct comprising nanobodies linked to the human IgG1 constant fragment (Fc) (nanobody-hFc constructions or nb-hFcs) to make enhanced humanized sdAbs with all the attributes of nanobodies with improved half-life and optimized effector functions. Several promising nanobodies that neutralize the original SARS-COV-2 and several of its variants have been identified, including Delta, with high efficacy. In particular, a subset of these nanobodies bind to the Omicron RBD.

Harmon, Brooke Nicole↗
DOE OSTI2020

Elucidation of Bottom-up Growth of CaCO3 Involving Prenucleation Clusters from Structure Predictions and Decomposition of Globally Optimized (CaCO3)n Nanoclusters

Low-energy minima structures for (CaCO3)n, n = 28, are predicted using bottom-up genetic algorithms in conjunction with density functional theory electronic structure calculations, in comparison with the frozen and relaxed top-down clusters generated by cuts from the calcite, vaterite, and aragonite crystal structures. Similarities in structural motifs for the bottom-up and relaxed top-down are revealed using a fragment recognition technique. Fragment energy decomposition analysis shows that the bottom-up and relaxed top-down clusters belong to two classes of amorphous clusters with distinct intracluster energy distributions, despite their structural similarity. The bottom-up clusters with >20 formula units are surface stabilized with negative surface energy densities. In contrast, the top-down clusters are interior stabilized with positive surface energy densities. We prove that the sign of the surface energy density determines whether the nucleation reaction energy as a function of nuclear size has a maximum or a minimum. The surface-stabilized bottom-up clusters are proposed to be a type of prenucleation cluster at the minimum of the nucleation reaction energy. A mechanism for mineralization of CaCO3 involving prenucleation clusters and nonclassical growth pathway is proposed on the basis of our theoretical findings, which is consistent with previous titration experiments.

calcium carbonate, prenucleation cluster, biominer↗
DOE OSTI2020

Cross-Neutralization of a SARS-CoV-2 Antibody to a Functionally Conserved Site Is Mediated by Avidity

Most antibodies isolated from individuals with coronavirus disease 2019 (COVID-19) are specific to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, COVA1-16 is a relatively rare antibody that also cross-neutralizes SARS-CoV. Here, we determined a crystal structure of the COVA1-16 antibody fragment (Fab) with the SARS-CoV-2 receptor-binding domain (RBD) and negative-stain electron microscopy reconstructions with the spike glycoprotein trimer to elucidate the structural basis of its cross-reactivity. COVA1-16 binds a highly conserved epitope on the SARS-CoV-2 RBD, mainly through a long complementarity-determining region (CDR) H3, and competes with the angiotensin-converting enzyme 2 (ACE2) receptor because of steric hindrance rather than epitope overlap. COVA1-16 binds to a flexible up conformation of the RBD on the spike and relies on antibody avidity for neutralization. These findings, along with the structural and functional rationale for epitope conservation, provide insights for development of more universal SARS-like coronavirus vaccines and therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Proteolytic processing induces a conformational switch required for antibacterial toxin delivery

Many Gram-negative bacteria use CdiA effector proteins to inhibit the growth of neighboring competitors. CdiA transfers its toxic CdiA-CT region into the periplasm of target cells, where it is released through proteolytic cleavage. The N-terminal cytoplasm-entry domain of the CdiA-CT then mediates translocation across the inner membrane to deliver the C-terminal toxin domain into the cytosol. Here, we show that proteolysis not only liberates the CdiA-CT for delivery, but is also required to activate the entry domain for membrane translocation. Translocation function depends on precise cleavage after a conserved VENN peptide sequence, and the processed ΔVENN entry domain exhibits distinct biophysical and thermodynamic properties. By contrast, imprecisely processed CdiA-CT fragments do not undergo this transition and fail to translocate to the cytoplasm. These findings suggest that CdiA-CT processing induces a critical structural switch that converts the entry domain into a membrane-translocation competent conformation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Polarized 𝐽/𝜓 production in semi-inclusive DIS at large 𝑄 2 : Comparing quark fragmentation and photon-gluon fusion

We compare the relative importance of different mechanisms for polarized 𝐽/𝜓 production in semi-inclusive deep inelastic scattering processes at large 𝑄 2 . The transverse momentum dependent (TMD) factorization framework and nonrelativistic quantum chromodynamics are used to study the leading contributions from light quark fragmentation to polarized 𝐽/𝜓, and compared to direct production via photon-gluon fusion, which can proceed through color-singlet as well as color-octet mechanisms. We identify kinematic regimes where light quark fragmentation dominates, allowing for the extraction of the 3 𝑆$^{[8]}_{1}$ matrix element, as well as regimes where photon gluon fusion dominates, suggesting that the gluon TMD parton distribution function can be probed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Diffusion power spectra as a window into dynamic materials architecture

Chemical recycling of commodity and specialty polymers presents a multifaceted challenge for industrial societies. On one hand, macromolecular architectures must be engineered to yield durable products that, on the other hand, rapidly deconstruct to recyclable monomers under pre-determined conditions. Polymer deconstruction is a chemical process that requires deep understanding of molecular reactivity in heterogeneous media, where porous material architectures evolve in both space and time. To build this understanding, we develop herein experimental and analytical methods describing sets of diffusive eigenmodes that exist within time-varying, non-Euclidean boundary conditions, a situation commonly encountered in the reactive deconstruction of polymers where chain fragments splay, alter their local dynamics, and evolve in their confinement of reacting media. Diffusion power spectra, discerned experimentally by NMR, yield polymer and solvent frequency-domain velocity autocorrelation functions that are analyzed in the context of physical models for chemical reactions parameterized with fractal mathematics. The results connect local motion in polymers to chemical reactivity during acidolysis of circular elastomers.

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

Prediction of organic homolytic bond dissociation enthalpies at near chemical accuracy with sub-second computational cost

Bond dissociation enthalpies (BDEs) of organic molecules play a fundamental role in determining chemical reactivity and selectivity. However, BDE computations at sufficiently high levels of quantum mechanical theory require substantial computing resources. In this paper, we develop a machine learning model capable of accurately predicting BDEs for organic molecules in a fraction of a second. We perform automated density functional theory (DFT) calculations at the M06-2X/def2-TZVP level of theory for 42,577 small organic molecules, resulting in 290,664 BDEs. A graph neural network trained on a subset of these results achieves a mean absolute error of 0.58 kcal mol-1 (vs DFT) for BDEs of unseen molecules. We further demonstrate the model on two applications: first, we rapidly and accurately predict major sites of hydrogen abstraction in the metabolism of drug-like molecules, and second, we determine the dominant molecular fragmentation pathways during soot formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗