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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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DOE OSTI2025

Structurally Frustrated Remeika Phases: Tolerance Factor and Non-Kramers’ Ion Effects

Quantum materials that are found on the verge of structural, magnetic, and electronic instabilities are deep reservoirs for exotic phenomena. Our criteria to study the reported Ln 5 Ru 6 Sn 18 (Ln = Gd, Tb) are guided by the tolerance factor for Remeika phases─a class of intermetallic compounds with the general formula A 3 M 4 X 13 (where A = rare-earth element, M = transition metal, and X = tetrel), which can be viewed as structural analogues of pseudoperovskites (4 × ABX 3 ), with one of the tetrel atoms occupying the A-site. We have grown single crystals, up to 0.5 cm on the largest facet, of Gd 5 Ru 6 Sn 18 (a = 13.8052(12) Å) and Tb 5 Ru 6 Sn 18 (a = 13.7825(9) Å), which we expect to be on the verge of a formation instability. Bulk magnetic, heat capacity, and electrical transport measurements reveal unusual behavior that originates from the trivalent Gd and Tb ions, with deviations from typical metallic behavior and magnetic ordering that is short-range or disrupted in some other way. Furthermore, to better understand these phenomena, single-crystal neutron diffraction is investigated, which reveals short-range correlations among the partially occupied Tb and Sn sublattices, with 3D-ΔPDF analysis supporting direction-dependent local order. Taken together, these measurements show the utility of using tolerance factors in identifying materials that are likely to exhibit complex phenomena and uncover environments where a formation instability may strongly impact emergent bulk magnetic and electronic phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The CH(X 2 Π) + H 2 O reaction: two transition state kinetics

he reaction of ground state methylidyne (CH) with water vapor (H 2 O) is theoretically re-investigated using high-level coupled cluster computations in combination with semi-classical transition state theory (SCTST) and two-dimensional master equation simulations. Insertion of CH into a H–O bond of H 2 O over a submerged barrier via a well-skipping mechanism yielding solely H and CH 2 O is characterized. The reaction kinetics is effectively determined by the formation of a pre-reaction van der Waals complex (PRC, HC—OH 2 ) and its subsequent isomerization to activated CH 2 OH in competition with PRC re-dissociation. The tunneling effects are found to be minor, while variational effects in the PRC → CH 2 OH step are negligible. The calculated rate coefficient k ( T ) is nearly pressure-independent, but strongly depends on temperature with pronounced down-up behavior: a high value of 2 x 10 -10 cm 3 s -1 at 50 K, followed by a fairly steep decrease down to 8 × 10 -12 cm 3 s -1 at 900 K, but increasing again to 5 × 10 -11 cm 3 s -1 at 3500 K. Over the T-range of this work, k ( T ) can be expressed as: k ( T , P = 0) = 2.31 × 10 -11 ( T /300 K) -1.615 exp(-38.45/ T ) cm 3 s -1 for T = 50-400 K k ( T , P = 0) = 1.15 × 10 -12 ( T /300 K) 0.8637 exp(892.6/ T ) cm 3 s -1 for T = 400-1000 K k ( T , P = 0) = 4.57 × 10 -15 ( T /300 K) 3.375 exp(3477.4/ T ) cm 3 s -1 for T = 1000–3500 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Efficient Self-Sensitized Photochemical CO 2 Reduction Using [Re(bpy 2+ )(CO) 3 (I)] 2+ and [Re(bpy 2+ )(CO) 3 (CH 3 CN)] 3+ Photocatalysts with Pendent Ammonium Cations

Rhenium(I) tricarbonyl complexes fac-[Re(bpy)(CO) 3 (L)]n + are the classical examples of self-sensitized photocatalysts capable of the dual roles of light absorption and catalysis. Here, in this work, a series of dicationic halido or tricationic solvento complexes fac-[Re(bpy 2+ )(CO) 3 X] n+ (PF 6 ) n (where X = Cl - or I - (n = 2), or CH 3 CN (n = 3) and bpy 2+ is bipyridine modified by two -CH 2 -(NMe3) + tetra-alkylammonium cations) have been investigated as self-sensitized and sensitized CO 2 reduction photocatalysts. Four structural isomers differing in the cation position have been tested in N,Nʹ-dimethylacetamide solvent (DMA) using 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzimidazole (BIH) as the electron donor, and the position of the cationic pendants has a significant impact on the catalyst turnover number and quantum efficiency (ϕ). Up to 455 self-sensitized turnovers of CO and a high photon efficiency (ϕ CO ) of 22% have been achieved. Time-resolved infrared spectroscopy and theoretical calculations were used to characterize the catalytic cycle including the ligand exchange between one-electron reduced (OER) halido and solvento species as well as the binding of CO 2 to the putative two-electron reduced (TER) species. The CO 2 -reactive TER catalyst was formed by disproportionation or intramolecular electron transfer between two forms of the OER catalyst as indicated by the formation of the fully oxidized catalyst concurrent with CO 2 binding. When [Ru(bpy) 3 ] 2+ was used as a sensitizer, catalyst durability improved, and the selectivity toward formate increased as high as 3.3:1 over CO (total TON = 1370) due to acidification of the reaction, which promotes formation of the hydride intermediate, as BIH was consumed and deprotonated.

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

Dinuclear Complexes of Uranyl, Neptunyl, and Plutonyl: Structures and Oxidation States Revealed by Experiment and Theory

Dinuclear perchlorate complexes of uranium, neptunium, and plutonium were characterized by reactivity and DFT, with results revealing structures containing pentavalent, hexavalent, and heptavalent actinyls, and actinyl-actinyl interactions (AAIs). Electrospray ionization produced native complexes [(AnO 2 ) 2 (ClO 4 ) 3 ] - for An:An = U:U, Np:Np, Pu:Pu, and Np:Pu, which are intuitively formulated as actinyl(V) perchlorates. However, DFT identified lower-energy structures [(AnO 2 )(AnO 3 )(ClO 4 ) 2 (ClO 3 )] - comprising a perchlorate fragmented to ClO 3 , actinyl(VI) cation An VI O 2 2+ , and neutral AnO 3 . For U:U and Np:Np, and Np in Np:Pu, the coordinated AnO 3 is calculated as actinyl(VI) with an equatorial oxo, [O yl =An VI =O yl ][=O eq ], whereas for Pu:Pu, it is plutonyl(V) oxyl, [O yl =Pu V =O yl ][-O eq • ]. The implied lower stability of Pu VI versus Np VI indicates weaker Pu=O eq versus Np=O eq bonding. Adsorption of O 2 by the U:U complex suggests oxidation of U V to U VI , corroborating the assignment of perchlorate [(An V O 2 ) 2 (ClO 4 ) 3 ] - . DFT predicts the O 2 adducts are [(An VI O 2 )(O 2 )(An VI O 2 )(ClO 4 ) 3 ] - with actinyls oxidized from +V to +VI by bridging peroxide, O 2 2- . In accordance with reactivity, O 2- addition is computed as substantially exothermic for U:U and least favorable for Pu:Pu. Collision-induced dissociation of native complexes eliminated ClO 2 to yield [(AnO 2 )(O) 2 (AnO 2 )(ClO 4 ) 2 ] - , in which fragmented O atoms bridge as oxyl O -• and oxo O 2- to yield uranyl(VI) and plutonyl(VI), or as oxos O 2- to yield neptunyl(VII), [O yl =Np VII =O yl ] 3+ .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Trithiol ligand provides tumor-targeting 191 Pt-complexes with high molar activity and promising in vivo properties

The Auger electron-emitting radionuclide 191 Pt is a promising candidate for radiopharmaceutical therapy. Herein, we explored novel labeling methods for 191 Pt using thiol-containing ligands to improve the in vivo stability and targeting ability of 191 Pt-labeled complexes. We synthesized dithiol-containing N 2 S 2 and NS 2 ligands, and a trithiol ligand, and then compared their radiochemical reactivity with 191 Pt. [ 191 Pt]Pt-trithiol was synthesized and its biodistribution was evaluated in mice and compared with free 191 Pt. Finally, a 191 Pt-trithiol complex targeting prostate-specific membrane antigen (PSMA): [ 191 Pt]Pt-trithiol-PSMA was developed and evaluated in mice bearing tumor xenografts and compared with a 191 Pt-complex labeled via monothiol-containing Cys ([ 191 Pt]Pt-Cys-PSMA). A comparison of N 2 S 2 , NS 2 , and trithiol showed that the trithiol ligand is the best for producing 191 Pt-labeled compounds in high yield and as a single peak in preparative HPLC. Notably, the trithiol ligand made 191 Pt-labeled compounds and precursors separatable, achieving 191 Pt-labeled products with a high molar activity: 200–400 mCi/μmol (7.4–14.8 GBq/μmol) at EOS. Additionally, [ 191 Pt]Pt-trithiol and [ 191 Pt]Pt-trithiol-PSMA were stable in vivo with rapid clearance compared with free 191 Pt and [ 191 Pt]Pt-Cys-PSMA. [ 191 Pt]Pt-trithiol-PSMA resulted in a low uptake in most normal organs and a high uptake in the kidneys and prostate cancer with PSMA expression. Furthermore, this study demonstrated that a labeling method with trithiol for Pt radionuclides achieves 191 Pt-labeled products with high molar activity. 191 Pt-trithiol-PSMA showed promising in vivo stability and tumor-targeting specificity, which should facilitate the pharmaceutical development of Pt radionuclides for radiopharmaceutical therapy, especially Auger electron cancer therapy.

Auger emitters↗
DOE OSTI2023

DRIPS: A framework for dimension reduction and interpolation in parameter space

Reduced-order models are often used to describe the behavior of complex systems, whose simulation with a full model is too expensive, or to extract salient features from the full model’s output. We introduce a new model-reduction framework DRIPS (dimension reduction and interpolation in parameter space) that combines the offline local model reduction with the online parameter interpolation of reduced-order bases (ROBs). The offline step of this framework relies on dynamic mode decomposition (DMD) to build a low-rank linear surrogate model, equipped with a local ROB, for quantities of interest derived from the training data generated by repeatedly solving the (nonlinear) high-fidelity model for multiple parameter points. The online step consists of the construction of a parametric reduced-order model for each target/test point in the parameter space, with the interpolation of ROBs done on a Grassman manifold and the interpolation of reduced-order operators done on a matrix manifold. The DMD component enables DRIPS to model (typically low-dimensional) quantities of interest directly, without having to access the (typically high-dimensional and possibly nonlinear) operators in a high-fidelity model that governs the dynamics of the underlying high-dimensional state variables, as required in projection-based reduced-order modeling. A series of numerical experiments suggests that DRIPS yields a model reduction, which is computationally more efficient than the commonly used projection-based proper orthogonal decomposition; it does so without requiring a prior knowledge of the governing equation for quantities of interest. Furthermore, for the nonlinear systems considered, DRIPS is more accurate than Gaussian-process interpolation (Kriging).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Building Neutron Scattering Infrastructure in Louisiana for Advanced Materials (Final Report)

The main objective of the Louisiana Consortium for Neutron Scattering (LaCNS) is to build a major neutron scattering infrastructure capable of treating both soft and hard materials. The goal is to create a sustainable effort having the quality, breadth, and depth necessary to produce competitive proposals including collaborative and center type proposals. Our scientific aim is to understand the role of coupling in emergent complex materials and its impact on the structure/property relationship and to explore how to tune the key couplings to guide the design of materials with the desired properties. This naturally includes building a base of users of the Spallation Neutron Source (SNS) and the High Flux Isotope Reactor (HFIR) in Louisiana; to train highly talented graduate and post-doctoral students in synthesis, neutron scattering, and simulation and modeling techniques, thereby helping to produce the next generation of scientist who use neutron scattering techniques as a crucial part of their research. The goal of our hard matter program is to understand the interplay between spin, charge, orbital, and lattice degrees of freedom in carefully selected complex materials. We have made considerable progress on number of complex systems including the oxide Sr3(Ru1-xMnx)2O7 where short-range magnetic ordering with anisotropic spin texture is initiated at the metal-insulator transition that clearly indicates a strong spin-charge coupling. Another critical area is in quantum materials. For example, in the topological semimetal BaMnSb2, we found a 3D canted antiferromagnetic Weyl semimetal with a 2D electronic structure and a nontrivial Berry phase. In addition, in the hexagonal chiral Mn1/3NbS2 system, we found soliton/soliton and soliton/antisoliton domain walls where the application of small fields or small currents can be used to control nanoscopic magnetic domains where the control of domain walls is crucially important for information storage. In addition, chemical transformation investigations were performed on the VISION instrument at Spallation Neutron Source (SNS). The soft matter effort was focused on understanding the role of non-covalent interactions on the structure and dynamics of fluid-based soft matter. One key focus was on sequence-defined (SD) amphiphilic peptoid polymers that allow encoding of molecular interactions and thereby systematic investigations of how charge directs the solution self-assembly of amphiphilic polymers in water. Another important area was on the dynamics of lipids self-assembled into membranes for exploring the permeability and mechanical using both neutron spin echo (NSE) spectroscopy and quasielastic neutron scattering (QENS) to distinguished between viscoelasticity and permeability at the molecular scale. Overall, the LaCNS project was quite successful, generating 145 publications and 245 presentations. Our graduate and post-doctoral students were well trained resulting in positions in national laboratories (Oak Ridge National Laboratory (ORNL), Argonne National Laboratory and Los Alamos National Laboratory), major research universities, and industry. We also developed a uniaxial pressure cell along with ORNL for SNS. A critical goal of this project was to establish a foundation for competing nationally in federally funded research programs. To this end, we were quite successful in generating over twenty-two federally and non-federally funded grants including awards from NSF, DOE, and DOD, and two early career awards. Equally important, we were able to secure a key major piece of instrumentation via a large ARO grant for a state-of-the-art electron microscope.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nanoscale strain wave generation by a piezoelectric grating from polar vortices

Nanostructures formed by spontaneously broken symmetry have provided new ways to manipulate quantum states. Specifically, topological structures with periodic spatial ordering, such as polar vortices and skyrmions, can be ideal hosts for creating engineered responses in both spatial and frequency domains. So far, however, only a few examples of such hierarchical engineering have been reported in the literature. Here we demonstrate that the spatially modulated piezoelectric response of a polar vortex structure can create strain waves with a characteristic nanoscale wavefront. Using time-resolved pump–probe resonant X-ray scattering and diffraction measurements, coupled with dynamical phase-field simulations, we show that the piezoelectric modulation of the spontaneously formed polar vortex crystal functions as an acoustic diffraction grating. This system converts incoming laterally uniform strain waves into outgoing waves with a characteristic sub-terahertz frequency, driven by an intrinsic excitation of the polar vortex crystal. Moreover, our phase-field simulations suggest that the dynamic mechanical displacements exhibiting vortex textures are generated from both space- and time-varying piezoelectric responses. Our findings illustrate a new method for generating nanoscale strain waves with unique spatial textures by tuning the hierarchical order of polar topologies to engineer new collective modes, allowing for a wide range of control through the topological lattice.

ferroelectrics↗
DOE OSTI2025

Data-Driven Kinetic Reaction Networks for Separation Chemistry

Understanding complex, multistep chemical reactions at the molecular level is a major challenge whose solution would greatly benefit the design and optimization of numerous chemical processes. The separation of rare-earth (4f) and actinide (5f) elements is an example where improving our chemical understanding is important for designing and optimizing new chemistries, even with a limited number of observations. Here, in this work, we leverage data-driven artificial intelligence and machine-learning approaches to develop kinetic reaction networks that describe the liquid–liquid extraction mechanism of uranium using N,N-di-2-ethylhexyl-isobutyramide (DEHiBA). Specifically, we compare and contrast the properties of two classes of models: (1) purely data-driven models that are regularized using chemistry-agnostic, L1 regression and (2) chemistry-informed models that are regularized using relative reaction energies provided by quantum mechanical calculations. We observe that purely data-driven models are unbiased, simple, and accurate in their predictions of experimental measurements when provided with sufficient data but are difficult to fully constrain and interpret. In contrast, chemistry-informed models exhibit significantly improved chemical interpretability and consistency, providing a detailed description of the separation process while achieving high accuracy through ensemble averaging. Overall, the dominant species predicted to be extracted into the organic phase is UO 2 (NO 3 ) 2 (DEHiBA) 2 , agreeing with experimental slope analysis, thermodynamic modeling, EXAFS, and crystal structures. This work demonstrates that leveraging the fundamental structure of the problem can lead to efficient learning schemes that provide both accurate predictions and chemical insights at a low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Numerical simulations of liquid jetting with solid inclusions

The dynamics of finite-sized particles in fluids, and their influence on the overall flow, are of great interest across several industrial, environmental, and medical fields. In the context of inkjet printing, the presence of solid inclusions can be either intentional, as in additive manufacturing, or unintentional, as in standard printing processes. These inclusions can strongly impact the jetting process, causing effects such as jet asymmetry, bubble entrapment, and the formation of satellite droplets. Understanding and controlling particle behavior is therefore essential, particularly to predict how and when particles are ejected over multiple jetting cycles. It is therefore critical to develop reliable models that allow for a deeper understanding of the complex interplay between particle and fluid during the whole printing process. To address this, we present a tailored implementation of the Color-Gradient multicomponent Lattice Boltzmann Method for fully resolved three-dimensional (3D) simulations of multicycle liquid jetting with particles. Our method supports realistic parameter settings aligned with industrial inkjet systems, and we provide both qualitative and quantitative validation against experimental data. Additionally, we introduce a simplified model based on the Stokes drag law, in which solid particles are represented as point particles and do not influence the fluid flow. Despite this limitation, the model offers a computationally efficient means to explore the vast parameter space typically encountered in industrial applications, allowing, e.g., identifying critical ejection regions and estimating the number of cycles required for particle release. These qualitative insights are valuable for guiding and complement fully two-way coupled simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗
DOE OSTI2025

Improved loss functions for machine-learned atomic potentials

Machine learning (ML) has become an invaluable tool across a wide array of domains in science as researchers find new ways to leverage its predictive power. This is especially true in chemistry, where ML is used to fit chemical properties or desirable attributes to the local structure of molecules and materials. In the pursuit of greater accuracy, it is relatively simple to increase the size or complexity of such models, although this often requires simultaneously seeking larger datasets in order to both fit and interpret the larger number of parameters. However, it is equally important to assess the quality and relative importance of the data and how these factors impact the training process. We, therefore, investigate the impact of using different loss functions for training neural network potentials (NNPs), as the loss function defines the error and parameter gradients used to train the NNP. In particular, we test the mean-squared error and Huber loss functions and, using insight from these functions, derive a new loss function based on the Asinh function, which yields significant improvement in the accuracy and generality of NNPs. We show that by discounting/minimizing errors and anomalies in the optimization process, both the Huber and Asinh loss functions improve the training of NNPs, leading to a final potential with a greater effective dimensionality.

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

Machine Learning Prediction of the Experimental Transition Temperature of Fe(II) Spin-Crossover Complexes

Spin-crossover (SCO) complexes are materials that exhibit changes in the spin state in response to external stimuli, with potential applications in molecular electronics. It is challenging to know a priori how to design ligands to achieve the delicate balance of entropic and enthalpic contributions needed to tailor a transition temperature close to room temperature. Here, we leverage the SCO complexes from the previously curated SCO-95 data set [Vennelakanti et al. J. Chem. Phys. 159, 024120 (2023)] to train three machine learning (ML) models for transition temperature (T 1/2 ) prediction using graph-based revised autocorrelations as features. We perform feature selection using random forest-ranked recursive feature addition (RF-RFA) to identify the features essential to model transferability. Of the ML models considered, the full feature set RF and recursive feature addition RF models perform best, achieving moderate correlation to experimental T 1/2 values. We then compare ML T 1/2 predictions to those from three previously identified best-performing density functional approximations (DFAs) which accurately predict SCO behavior across SCO-95, finding that the ML models predict T 1/2 more accurately than the best-performing DFAs. In addition, we study ML model predictions for a set of 18 SCO complexes for which only estimated T 1/2 values are available. Upon excluding outliers from this set, the RF-RFA RF model shows a strong correlation to estimated T 1/2 values with a Pearson’s r of 0.82. In contrast, DFA-predicted T 1/2 values have large errors and show no correlation to estimated T 1/2 values over the same set of complexes. Overall, our study demonstrates slightly superior performance of ML models in comparison with some of the best-performing DFAs, and we expect ML models to improve further as larger data sets of SCO complexes are curated and become available for model training.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Kinetics vs Thermodynamics: Engineering Photoredox Reactivity from an Upper Excited State of Fe II

Ultrafast deactivation of metal-to-ligand charge-transfer (MLCT) states into low-lying metal-centered states has long limited the utility of first-row transition-metal complexes in a broad range of applications, including photoredox catalysis. Here we bypass such limitations using a Fe II -pyridinium carbene complex to enable electron transfer reactivity directly from a higher-lying MLCT state. Time-resolved spectroscopic data revealed that the higher-energy MLCT manifold relaxes to lower-lying metal-centered states with a time constant of ca. 3 ps. The nature of the metal-centered (MC) excited state as a 3 MC (i.e., S = 1) was inferred from variable-temperature transient absorption studies. These experiments also revealed that the ground-state recovery process occurs at or very near the “Marcus barrierless regime”, thereby allowing for an estimate of its excited-state redox potential. The detailed picture of the energetics of this compound that emerged enabled fine-tuning of competing thermodynamic and kinetic pathways to effect electron transfer from the higher-energy MLCT excited state prior to relaxation to the ligand-field manifold. We believe these results open an unexplored landscape for the use of earth-abundant first-row transition-metal-based chromophores for applications in light-to-chemical energy conversion.

charge transfer↗
DOE OSTI2025

Wavelength-Selective Reactivity of Iron(III) Halide Salts in Photocatalytic C–H Functionalization

The utility of halogen radicals in hydrocarbon functionalization extends from early examples of photochemical halogenation to recent reports using photoredox catalysis with iridium complexes and simple transition metal salts such as FeCl 3 . The majority of these methods (uncatalyzed and iron-catalyzed) require UV light (λ ≤ 390 nm), and systematic efforts to enable the use of visible light remain valuable. We report the use of a simple Fe(III) salt that enables a C–H to C–C and C–N functionalization under visible light. The reactivity and selectivity profile using different light sources demonstrates wavelength-selective behavior, which was further investigated with deuterium kinetic isotope effect experiments and DFT calculations. These results show that control over the reactive intermediates in this iron-catalyzed reaction can be achieved through proper choice of the wavelength of irradiation.

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

Feasibility of Realizing a Universal Identifier Based on Fiber Bragg Grating Technology

Over the past year we have collected data on different fiber Bragg gratings (FBG) with the end goal of understanding their suitability for use in a new type of unique identifier (UID) that could be used in both tags and seals for high-value, high-risk assets. The ideal UID will have a complex signature that allows items to be uniquely identified by that signature. Tamper indication must be an integral part of the tag/seal process with measurable changes to the device signature indicative of any attempt to tamper with the monitored item. Further, the signature must be so difficult to reproduce that even state-actors with significant resources at their disposal will be discouraged from attempting it. Finally, readout verification of the product must be simple and secure, while providing red-light/green-light results in real time. To evaluate how well an FBG-based UID could meet these goals, we collected data on a large number of FBG samples from different vendors. Measurements included the response of the devices to uniform tension, tension when wrapped on a mandrel, and the response to changes in temperature and humidity, as well as the effect of simple potting in expanding and nonexpanding potting materials. We tested FBG samples written into single-mode fibers that were coated with the two commonly used materials, polyimide and acrylate and gratings that were both uniform and those with an apodized response (i.e., the intensity of the grating was varied to minimize sidelobes). The result of the work to date did not find any significant issues with the design concept for a UID based on this technology. Specific findings include a baseline design comprising five FBGs with distinct spectral returns analyzed using a difference-correlation approach. To realize this device, careful attention must be given to the impact of environmental factors on the UID response, limiting the properties of the potting compounds and FBG coating materials that can be used.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Ligand-Structure-Dependent Coherent Vibrational Wavepacket Dynamics in Pyrazolate-Bridged Pt(II) Dimers

Bimetallic transition metal complexes have gained increasing attention because of their versatile functions in solar energy conversion and photonics applications arising from inter-metal electronic coupling. In bimetallic platinum (Pt) complexes, electronic communication between the Pt-centered and ligand-centered moieties have been shown to be critical for defining their excited-state dynamic trajectories undergoing either localized ligand centered (LC)/metal-to-ligand-charge-transfer (MLCT) transitions or delocalized metal-metal-to-ligand-charge-transfer (MMLCT) transitions. The branching of the excited-state intersystem crossing (ISC) trajectories are modulated through structural factors that alter the relative energies of the different states. In this study, we investigated the correlation of the structural factors influencing the excited state trajectories. Using femtosecond broadband transient absorption (fs-BBTA) spectroscopy, ultrafast dynamics in the excited state of two select Pt(II) dimers have been mapped out using their coherent vibrational wavepacket signatures in corresponding transient absorption spectra. To examine how the ligand moieties of the Pt(II) dimers influence excited-state dynamics and the coherent vibrational wavepacket behavior, here we carried out comparative studies on two pyrazolate-bridged Pt(II) dimers of the general formula [Pt( t Bu 2 Pz)(N^C)] 2 ( t Bu 2 Pz = 3,5-di-tert-butylpyrazole); N^C = 7,8-benzoquinoline (bzq, 1) or 1-phenylisoquinoline (piq, 2)). We found that photoexcitation into the low energy absorption bands of 1 and 2 respectively induce the formation of 1 MMLCT states from which ultrafast ISC proceeds, resulting in stimulated emission quenching and decoherence of the vibrational wavepacket motions. The results obtained in this study suggest that both energetics and the structural rigidity of the aromatic cyclometalating ligands in 1 and 2 can significantly influence dynamics along the excited state trajectory characterized by dephasing of the coherent oscillations. The collective results provide direct evidence of how ligand structure alters electronic dynamics along excited state trajectories associated with ISC processes, providing insight into using ligand design to steer photochemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗