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DOE OSTI2020

Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Substituent Effects on Exchange Coupling and Magnetic Relaxation in 2,2'-Bipyrimidine Radical-Bridged Dilanthanide Complexes

Systematic analysis of related compounds is crucial to the design of single-molecule magnets with improved properties, yet such studies on multinuclear lanthanide complexes with strong magnetic coupling remain rare. In this work, we present the synthesis and magnetic characterization of the series of radical-bridged dilanthanide complex salts [(Cp* 2 Ln) 2 (μ-5,5'-R 2 bpym)](BPh 4 ) (Ln = Gd, Dy; R = NMe 2 (1), OEt (2), Me (3), F (4); bpym = 2,2'-bipyrimidine). Modification of the substituent on the bridging 5,5'-R 2 bpym radical anion allows the magnetic exchange coupling constant, J Gd-rad , for the gadolinium compounds in this series to be tuned over a range from -2.7 cm -1 (1) to -11.1 cm -1 (4), with electron-withdrawing or -donating substituents increasing or decreasing the strength of exchange coupling, respectively. Modulation of the exchange coupling interaction has a significant impact on the magnetic relaxation dynamics of the single-molecule magnets 1-Dy through 4-Dy, where stronger J Gd-rad for the corresponding Gd 3+ compounds is associated with larger thermal barriers to magnetic relaxation ( U eff ), open magnetic hysteresis at higher temperatures, and slower magnetic relaxation rates for through-barrier processes. Further, we derive an empirical linear correlation between the experimental U eff values for 1-Dy through 4-Dy and the magnitude of J Gd-rad for the corresponding gadolinium derivatives that provides insight into the electronic structure of these complexes. This simple model applies to other organic radical-bridged dysprosium complexes in the literature, and it establishes clear design criteria for increasing magnetic operating temperatures in radical-bridged molecules.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗

DOE OSTI2025

Replication Data for: Deconstructing Chirality: Probing Local and Non-local Effects in Azobenzene Derivatives with X-ray Circular Dichroism

Resolving molecular chirality at the atomic scale remains a critical challenge in chemistry. Conventional Optical Circular Dichroism spectroscopy often overlooks subtle and localized structural features. Here, we computationally investigate site-specific X-ray Circular Dichroism (XCD) across a series of trans-azobenzene derivatives to deconstruct and interpret chiroptical signals at the atomic level. Our modeling reveals that XCD is capable of distinguishing dichroic contributions arising from both a local chiral center and global molecular twist, revealing their intricate interplay and potential for constructive or destructive interference. We show that sterically-induced global distortions can dominate the XCD signal in some cases, even suppressing the response from the chiral center itself. This insight suggests a new molecular design principle for tuning chiroptical activity, which we extend by proposing strategies to achieve unidirectional photoisomerization through steric gearing. Altogether, this work establishes a quantitative framework for engineering chiroptical responses, laying the foundation for the design of functional chiral systems utilizing principles of unidirectional molecular motor-like conformational dynamics.

Chemistry↗

DOE OSTI2020

Full circle mechanical dynamic characterization including experimental modal analysis and finite element analysis

During operation, it was observed that a specific mechanical system experienced undesirable vibration and it became necessary to understand and mitigate this phenomenon. This document investigates the tools, methodology, and results of the dynamic characterization of the system. The characterization makes use of the experimental modal analysis (EMA) methods of single input multiple output (SIMO) and single input single output (SISO). The validity of the theory of reciprocity is confirmed to minimize measurement error, cost, and time of repeat testing. Finite element analysis (FEA) is used in choosing transducer and modal impact locations to adequately characterize the system. Single degree of freedom (SDOF) and multiple degree of freedom (MDOF) curve fitting is used to fully characterize the system’s mode shapes and natural frequencies. The EMA characterization results are used to modify and validate the FEA model so that FEA can be used to model potential structural modifications to the system to mitigate the undesirable vibration. Structural modifications are chosen, implemented, and their effectiveness is quantified using EMA. Finally, a qualitative evaluation of the methodology of FEA validation by EMA and tuning of the model to match the experimental results is discussed.

42 ENGINEERING↗

DOE OSTI2025

Deconstructing Chirality: Probing Local and Nonlocal Effects in Azobenzene Derivatives with X-ray Circular Dichroism

Resolving molecular chirality on the atomic scale remains a critical challenge in chemistry. Conventional Optical Circular Dichroism spectroscopy often overlooks subtle and localized structural features. Here, we computationally investigate site-specific X-ray circular dichroism (XCD) across a series of trans-azobenzene derivatives to deconstruct and interpret chiroptical signals at the atomic level. Our modeling reveals that XCD is capable of distinguishing dichroic contributions arising from both a local chiral center and a global molecular twist, revealing their intricate interplay and potential for constructive or destructive interference. We show that sterically induced global distortions can dominate the XCD signal in some cases, even suppressing the response from the chiral center itself. This insight suggests a new molecular design principle for tuning the chiroptical activity, which we extend by proposing strategies to achieve unidirectional photoisomerization through steric gearing. Altogether, this work establishes a quantitative framework for engineering chiroptical responses, laying the foundation for the design of functional chiral systems utilizing principles of unidirectional molecular motor-like conformational dynamics.

X-ray spectroscopy↗

DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

DOE OSTI2021

Validation of simulated wave energy converter responses to focused waves

Focused waves are increasingly used as a design method to predict extreme loads for offshore structures, such as wave energy converters (WECs). However, the ability of computational methods to accurately simulate the prescribed focused waves and resulting wave structure interactions is not well validated. This study uses two computational fluid dynamic methods, WEC-Sim and STAR-CCM+, to evaluate the responses of two taut-moored WEC-like buoys to three different focused waves. WEC-Sim is a computationally efficient, mid-fidelity model, based on linearised potential flow theory. In contrast, STAR-CCM+ is a high-fidelity, three-dimensional, unsteady, Reynolds-averaged Navier–Stokes-based model. The two buoy geometries considered are a hemispherical-bottom cylinder and a truncated cylinder with a cylindrical moon pool. Three prescribed focused waves are generated in both codes, and the simulated displacements and mooring loads are obtained for each of the hydrodynamic bodies. The resulting STAR-CCM+ generated focused waves have approximately the same accuracy, in comparison with the analytic solution, as experimentally generated focused waves. The WEC-Sim simulated responses, when using viscous coefficients tuned to the measured displacements, are, on average, within 11.5% of experimentally measured values, whereas the STAR-CCM+ simulated responses are, on average, within 14.2% of the experimental values.

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Static and dynamic magnetic properties of honeycomb lattice antiferromagnets Na 2 M 2 TeO 6 , M = Co and Ni

The magnetic structures and spin dynamics of Na 2 CO 2 TeO 6 and Na 2 Ni 2 TeO 6 are investigated by means of elastic and inelastic neutron scattering measurements and the results are discussed in the context of a generalized Kitaev-Heisenberg model on a honeycomb lattice with strong spin-orbit coupling. The large number of parameters involved in the Hamiltonian model is evaluated by using an iterative optimization algorithm capable of extracting model solutions and simultaneously estimating their uncertainty. The analyses indicate that both Co 2+ (d 7 ) and Ni 2+ (d 8 ) antiferromagnets realize bond-dependent anisotropic nearest-neighbor interactions and support the theoretical predictions for the realization of Kitaev physics in 3 d electron systems with effective spins S = 1/2 and 1. By studying the Na-doped system Na 2.4 Ni 2 TeO 6 , we show that the control of Na content can provide an effective route for fine-tuning the magnetic lattice dimensionality, as well as to controlling the bond-dependent anisotropic interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

A pathway to synthesizing single-crystal Fe and FeCr films

Nuclear reactor environments provide a unique scientific and engineering challenge wherein materials must tolerate prolonged exposure to concurrent irradiation, elevated temperatures, and corrosive media. However, uncontrolled variability in material composition and structure often prohibits truly single-variable experiments that can reveal basic aspects of environmental damage. Here, Magnetron sputtering is used to provide a more controlled model system for these fundamental studies, yielding reproducible single-crystal Fe and FeCr thin films containing 8 and 18 at.% Cr. Electron microscopy is used to determine the systematic correlations between growth conditions and the resulting film microstructure and surface morphology. It is found that the substrate temperature and applied radio frequency (RF) bias can be tuned to obtain consistent homogeneous and single crystal films with a minimal amount of Ar impurities from the RF bias process. Epitaxial, single-crystal Fe films are obtained on MgO substrates at 500 °C with 10 Watt (W) RF bias deposition. However, when Cr is alloyed with Fe, higher substrate temperatures (600 °C) and applied RF biases (15 W) are required to achieve a similar epitaxial single-crystal FeCr film. Accelerated molecular dynamics simulations reveal that Cr impedes surface transport, explaining the need for higher temperature and bias during the growth of the Cr-bearing films.

36 MATERIALS SCIENCE↗

DOE OSTI2026

FOCAL Campaign II/III: Applying Active Hull Controls Using Tuned-mass Dampers/Hull Flexibility and Internal Loads

Campaign II and III of the Floating Offshore-wind Controls Advanced Laboratory Experimental Program (FOCAL) aimed to generate a dataset enabling the validation of the performance and loads of a scaled hull, with and without structural hull control. The floating platform was subjected to a variety of wave environments and controlled using tuned-mass dampers (TMDs) tuned to two of the systems natural frequencies (Platform Pitch and Tower-bending). The floating platform is fully instrumented to record a variety of parameters in real time such as platform dynamics, accelerations, and loads at different points in the structure. The test data considered was generated at the University of Maine's Harold Alfond Wind and Wave (W2) testing facility. This testing was focused only on validation of wave loading, and wind conditions were not considered. As such the platform does not support a working turbine, and instead supports a structure designed to have the same mass properties as the 1:70 IEA 15MW Reference turbine. The Load Cases (LC) considered in this testing campaign are as follows: LC 1.X - Platform Static Offset (TMD off); LC 2.X - Platform Free-decays (TMD off); LC 3.X - Wave Cases (Regular Wave, Irregular Wave, Pink Noise Wave) with and without TMDs active. Detailed properties on the model system are found in the following reference: Lenfest E., Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental Program - Campaigns 2 and 3: 1:70 Model-scale Testing of the IEA-Wind 15MW Reference Turbine and the VolturnUS-S Hull. UMaine ASCC Report Number 23-56-1183.

17 WIND ENERGY↗

DOE OSTI2020

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing

The recent development of deep learning has been mostly focusing on Euclidean data, such as images, videos, audios, etc. However, most real-world information and relation are often expressed as graphs. To efficiently learn from graph data, graph convolutional networks (GCNs) emerge as a promising approach, showing advantages in several practical applications such as social network analysis, knowledge discovery, 3D modeling, motion capturing, etc. Real-world graphs are usually extremely large and imbalanced, posting significant performance demand and design challenges on the hardware dedicated for GCN inference. In this paper, we propose an architecture design called UW-GCN to accelerate graph convolutional network inference. To tackle the major performance bottleneck from workload imbalance, we propose dynamic neighborhood stealing and remote chunk shuffling techniques, relying on hardware flexibility to achieve hardware auto-tuning under negligible area or delay overhead. Specifically, UW-GCN is able to smartly profile the sparse graph pattern while continuously adjusting the workload distribution via routing reconfiguration among parallel processing elements (PEs). The ideal configuration is then reused in the remaining iterations. To the best of our knowledge, this is the first accelerator design particularly for GCN and the first work relying on hardware auto-tuning, which is normally based on software, to achieve near-optimal workload balance in processing sparse structures.

Geng, Tong↗

DOE OSTI2020

Antisense targeting of decoy exons can reduce intron retention and increase protein expression in human erythroblasts

The decoy exon model has been proposed to regulate a subset of intron retention (IR) events involving predominantly larger introns (>1 kb). Splicing reporter studies have shown that decoy splice sites are essential for activity, suggesting that decoys act by engaging intron-terminal splice sites and competing with cross-intron interactions required for intron excision. The decoy model predicts that antisense oligonucleotides may be able to block decoy splice sites in endogenous pre-mRNA, thereby reducing IR and increasing productive gene expression. Indeed, we now demonstrate that targeting a decoy 5' splice site in the O-GlcNAc transferase (OGT) gene reduced IR from ~80% to ~20% in primary human erythroblasts, accompanied by increases in spliced OGT RNA and OGT protein expression. The remaining OGT IR was refractory to antisense treatment and might be mediated by independent mechanism(s). In contrast, other retained introns were strongly dependent on decoy function, since antisense targeting of decoy 5' splice sites greatly reduced (SNRNP70) or nearly eliminated (SF3B1) IR in two widely expressed splicing factors, and also greatly reduced IR in transcripts encoding the erythroid-specific structural protein, α-spectrin (SPTA1). These results show that modulating decoy exon function can dramatically alter IR and suggest that dynamic regulation of decoy exons could be a mechanism to fine-tune gene expression post-transcriptionally in many cell types.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Tuning the Functionalities of Porous Liquids for Emergent Gas-Capture Properties

Type 3 Porous Liquids (PLs) are a class of materials with the potential to revolutionize gas capture, storage, and utilization. These PLs are formed by suspending sorbent nanoparticles (e.g., metal−organic frameworks) in sterically excluded solvents, creating permanent porosity for gas capture in a processable, low-viscosity phase. Herein, a computational study revealed sorbent surface functionalization strategies to enhance CO 2 sorption, and the molecular structural signatures underpinning the enhancements in gas uptake. PLs composed of a ZIF-8 surface functionalized with 3-amino-1,2,4-triazole (Atz) in glyceryl triacetate were targeted for emergent CO 2 capture, exceeding that of the unfunctionalized ZIF-8 PL. ZIF-8 was surface functionalized with Atz at various surface coverage fractions (f), and classical molecular dynamics simulations predicted an increase in CO 2 sorption capacity with increasing f, up to f = 0.75. Additionally, detailed structural analyses revealed that solvent orientational order, derived from the solvent triplet-angle distribution, can identify the gas-capture potential of a PL without requiring computationally expensive direct modeling of the CO 2 sorption. Combined with experimental validation, initial computational screening of PL compositions promises to accelerate the discovery of PL compositions for novel gas separation materials platforms.

gas capture↗

DOE OSTI2026

New Perspectives on Vibrational Energy Transfer in Energetic Materials: Insights from Pressure-Tuned Ultrafast Spectroscopy

Understanding the manner in which vibrational energy flows between molecular and lattice vibrations is of great interest in physical chemistry due to its central role in reactivity and energy dissipation in molecular materials. Here, in this feature article, we highlight our recent efforts employing ultrafast broadband infrared spectroscopy toward understanding the interplay between molecular and lattice vibrations in energetic materials, motivated by the open questions surrounding the role of vibrational energy transfer (VET) in reaction initiation in these materials. Our work addresses the ongoing debate on the participation of doorway modes in VET. We further present new results from high-pressure ultrafast experiments on RDX, a hydrogen-bonded material, and BNFF, a hydrogen-free material, to explore how intermolecular interaction strength governs VET pathways and time scales. Collectively, our findings reveal that vibrational dynamics in these systems occurs across three distinct time regimes, with VET being incomplete out to hundreds of picoseconds, suggesting the importance of considering nonstatistical reactions in the modeling of these materials. These time scales vary as intermolecular interaction strength is indirectly modified by application of static pressure, indicating dramatic changes to the vibrational structure of these materials under shock-relevant conditions. Our results thus shed light on how intermolecular interactions shape vibrational energy redistribution in molecular materials, and highlight the need for further theoretical and experimental investigation.

Carlson, Daniel Ryan [Sandia National Laboratories↗

DOE OSTI2023

Tailoring light-induced charge transfer and intersystem crossing in FeCO using time-dependent spin–orbit configuration interaction

Real-time (RT) electronic structure methods provide a natural framework for describing light–matter interactions in arbitrary time-dependent electromagnetic fields (EMF). Optically induced excited state transitions are of particular interest, which require tuned EMF to drive population transfer to and from the specific state(s) of interest. Intersystem crossing, or spin-flip, may be driven through shaped EMF or laser pulses. These transitions can result in long-lived “spin-trapped” excited states, which are especially useful for materials requiring charge separation or protracted excited state lifetimes. Time-dependent configuration interaction (TDCI) is unique among RT methods in that it may be implemented in a basis of eigenstates, allowing for rapid propagation of the time-dependent Schrödinger equation. The recent spin–orbit TDCI (TD-SOCI) enables a real-time description of spin-flip dynamics in an arbitrary EMF and, therefore, provides an ideal framework for rational pulse design. The present study explores the mechanism of multiple spin-flip pathways for a model transition metal complex, FeCO, using shaped pulses designed to drive controlled intersystem crossing and charge transfer. These results show that extremely tunable excited state dynamics can be achieved by considering the dipole transition matrix elements between the states of interest.

Chemistry↗

DOE OSTI2026

Bridge Connectivity Dictates Spin Interactions and Triplet Pair Dynamics in Intramolecular Singlet Fission

Electron spin plays a critical role in determining the structure, dynamics, and reactivities of molecular excited states, including multiexciton processes such as singlet fission. These systems exhibit triplet pair states whose excited state dynamics can be widely tuned through molecular engineering. For example, the electronic coupling between covalently linked chromophores can be readily modulated using chemical bridges to control proximity, quantum interference, or resonance effects. However, less is known about how spin coupling interactions are impacted by chromophore architecture, and how this influences triplet pair recombination dynamics. Here, in this study, we investigate the role of bridge connectivity and chromophore identity in modulating interchromophore exchange and dipolar coupling interactions for a series of pentacene and tetracene dimers bridged by alternant hydrocarbons (phenylene, naphthalene, anthracene). Using both time-resolved electron paramagnetic resonance and transient absorption spectroscopy, we find that the boundedness and recombination pathways of the triplet pair spins are highly sensitive to molecular architecture and chromophore-specific magnetic dipolar interactions. Notably, nominally ferromagnetic and antiferromagnetic eigenstates result in distinct spin state orderings, consistent with predictions from quantum interference-based graphical models. These findings establish new design principles for tuning spin dynamics in iSF materials, with implications for photonic and quantum information applications.

He, Guiying [City Univ. of New York (CUNY), NY (Un↗