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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Opportunities for fundamental physics research with radioactive molecules

Molecules containing short-lived, radioactive nuclei are uniquely positioned to enable a wide range of scientific discoveries in the areas of fundamental symmetries, astrophysics, nuclear structure, and chemistry. Recent advances in the ability to create, cool, and control complex molecules down to the quantum level, along with recent and upcoming advances in radioactive species production at several facilities around the world, create a compelling opportunity to coordinate and combine these efforts to bring precision measurement and control to molecules containing extreme nuclei. In this paper, we review the scientific case for studying radioactive molecules, discuss recent atomic, molecular, nuclear, astrophysical, and chemical advances which provide the foundation for their study, describe the facilities where these species are and will be produced, and provide an outlook for the future of this nascent field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Statistically-driven Experimental Design to Improve Reference-free Quantification of Small Molecules by Liquid Chromatography-Mass Spectrometry

Non-targeted analysis of small molecules and metabolites in unknown, complex samples using liquid chromatography-tandem mass spectrometry remains challenging. One of the main bottlenecks is the extensive unannotated regions of metabolomics mass spectrometry data, resulting in knowledge gaps. Small molecule annotation in mass spectrometry data has conventionally relied on reference standards and libraries for compound identification and confirmation, which can constrain compound identification to those molecules already known, thus limiting the ability to discover new knowledge and new markers. Retention time prediction can facilitate and expedite unknown compound identification in non-targeted analysis of complex metabolomics samples. Additionally, accurate retention time predictions can also inform sample mixture design for LC-MS/MS analyses. However, current machine learning-based methods for retention time prediction are typically developed for specific chromatographic platforms and are not generalizable across scales. And while technologies and methods to improve reference-free metabolite identification for more comprehensive annotation of unknowns has received much attention, development of the same for quantitation without reference standards has been much more limited, despite its importance in toxicological, environmental, food safety, forensics, and clinical applications. We believe that a reference-free quantitation strategy that exploits mass spectrometry data already collected for reference-free identification can provide much more insight on unknowns, and move the metabolomics field for more complete unknowns characterization. As such, we pursue two efforts to improve upon current state-of-the-art methods in non-targeted analysis: (1) machine learning-based retention time prediction and (2) statistical design of experiments framework for reference-free quantitation. In this work, we develop and demonstrate (1) a generalizable retention time prediction capability across chromatographic conditions and scales, and (2) a statistical design-based framework for response factor contribution elucidation and reference-free quantitation. Evaluation of our retention time prediction model, PrediToR, showed approximately 24% improvement over current models, and we observed approximately 10X improvement in concentration estimation accuracy from our statistical design-based response factor model over a primarily ionization efficiency-based model. We expect that future efforts to improve upon these new capabilities will further advance non-targeted analysis of small molecules towards truly reference-free metabolomics.

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

Laser Spectroscopy of Exotic Atoms and Molecules Containing Octupole-Deformed Nuclei

This project investigated the nuclear, atomic, and molecular structure of exotic atoms and molecules containing actinide isotopes. These short-lived radioactive systems are challenging to produce and study in the laboratory, yet they offer unique opportunities for fundamental science. These nuclei are predicted to exhibit pear-shaped (octupole) deformation, a rare collective nuclear behavior that dramatically enhances their sensitivity to fundamental physics phenomena such as time-reversal- and parity-violating effects. Such enhancements make them ideal probes for exploring open questions in our understanding of the universe such as the origin of the matter–antimatter asymmetry of the universe. To realize these measurements, the project led the development of a new laser spectroscopy experiment at MIT, and later commissioned at the Facility for Rare Isotope Beams (FRIB) at Michigan State University: the Resonance Ionization Spectroscopy Experiment (RISE). RISE combines the spectroscopic precision of collinear laser spectroscopy with the sensitivity of particle-detection techniques, enabling measurements of rare isotopes produced at rates as low as a few ions per second. The beamline was designed, built, and installed, and was successfully commissioned at FRIB during the grant period. RISE is now a permanent capability of the FRIB facility, and has produced several results on the study of rare atoms and molecules for nuclear structure and fundamental symmetries. In parallel with the FRIB program, the project contributed to the first precision laser-spectroscopy measurements of short-lived radioactive molecules. Working with international collaborators at CERN's ISOLDE facility, the team conducted pioneering experiments on radium monofluoride (RaF) and actinium monofluoride (AcF). The results from this work have been published in major journals of science, including Nature, Science, Nature Physics, Nature Communications, and Physical Review Letters. These findings have guided future experiments on the laser cooling of radioactive molecules, opening a new platform for precision tests of fundamental symmetries.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Symmetry‐Breaking Strategy Yields Dopant‐Free Small Molecule Hole Transport Materials for Inorganic Perovskite Solar Cells with 20.58% Efficiency and Outstanding Stability

Abstract Inorganic perovskites are known for their excellent photothermal stability; however, the photothermal stability of all‐inorganic n‐i‐p perovskite solar cells (PSCs) is compromised due to ion diffusion and free radical‐induced degradation caused by the use of doped spiro‐OMeTAD hole transport materials (HTMs). In this study, two isomeric donor–acceptor–donor (D–A–D) type small molecules, namely HBT and HiBT, were developed and used as dopant‐free HTMs, using 2,1,3‐benzothiadiazole or benzo[d][1,2,3]thiadiazole as acceptor moieties. The HiBT molecule, with its symmetry‐breaking features, exhibits a large dipole moment, enhanced coordination‐active sites, and a well‐aligned energy level structure, all of which contribute to passivating perovskite surface defects and improving free charge separation. As a result, inorganic CsPbI 3 PSCs with HiBT HTM achieved an impressive power conversion efficiency (PCE) of 20.58%, the highest reported for dopant‐free HTM‐based inorganic PSCs. Moreover, the enhanced hydrophobic properties of HiBT molecules, coupled with their ability to passivate perovskite surface defects, contribute to significantly improved device stability. The unencapsulated devices based on HiBT HTM retained over 83% and 80% of their initial efficiency after being stored at 85 °C for 50 days and undergoing maximum power point (MPP) tracking at 85 °C for 1100 h, respectively. These results highlight that the symmetry‐breaking strategy is an exceptionally effective approach for designing efficient, dopant‐free small molecule HTMs, significantly contributing to both the high efficiency and enhanced stability of all‐inorganic PSCs.

Chemistry↗
DOE OSTI2024

Machine learning for the redox potential prediction of molecules in organic redox flow battery

Here, organic redox flow batteries (ORFB) are recognized as an innovative technology for the large-scale storage of renewable energy. The redox potential of organic redox-active molecules plays a vital role in their performance. Advanced screening techniques like high-throughput experiment and machine learning (ML) have significantly enhanced organic material performance and transformed the field of ORFB. However, the scarcity of experimental data poses a considerable challenge for ML model development in this domain. In our study, we developed lightweight graph-based Gaussian process regression (GPR) models with GPU-accelerated marginalized graph kernel and hybrid kernel to predict the redox potentials of organic redox-active molecules for ORFBs, specifically focusing on small datasets. To evaluate model accuracy, we created a new experimental database of organic redox-active molecules by the data from hundreds of published papers and assembled previous computational datasets. We also considered some key parameters, such as pH conditions and solvent type, to assess their impact on redox potential prediction. Our GPR model predicted redox potentials with high accuracy across all datasets using minimal training data. The study provides powerful tools for molecule screening and design and delivers valuable guidance on designing training datasets for costly experiments.

25 ENERGY STORAGE↗
DOE OSTI2025

Dirhodium(II,II) Complexes as Panchromatic Single-Molecule Photocatalysts for Hydrogen Evolution

The growing global energy demand and climate change have prompted a shift from carbon-based fuels to sustainable energy sources. Hydrogen production by harnessing solar energy and using abundant proton sources represents an attractive approach to addressing this crisis. Single-molecule single-chromophore photocatalysts, capable of both absorbing the incident photon and catalyzing the chemical transformation, are able to circumvent energy losses present in multicomponent systems that require a photosensitizer and a catalyst, often employing additional redox relay molecules. Here, the series of complexes derived from cis-[Rh 2 (μ-DPhF) 2 (μ-bncn) 2 ] 2+ (1; DPhF = N,N′-diphenylformamidinate, bncn = benzo[c]cinnoline) discussed in this Account presents robust and air-stable single-molecule photocatalysts with panchromatic absorption from the ultraviolet spectral region to the near-infrared (NIR), with high turnover frequencies of ∼20 to 30 h –1 under red light irradiation. For comparison, other single-molecule hydrogen-evolving photocatalysts reported to date exhibit low photocatalytic efficiency, are not operable in the visible or NIR regions, and are unstable under an ambient atmosphere.

Absorption↗
DOE OSTI2025

A Comparison of Electronic Structure Methods for Predicting the Hydrogenation Energies of Candidate Molecules for Hydrogen Storage

The development of novel energy materials and fuels is required to expand current available energy sources. Aiming to reach this goal, there is growing interest in using molecular hydrogen as an energy carrier due to its abundance and high energy density. Liquid organic hydrogen carriers (LOHCs) are a promising route to the large-scale storage and transport of hydrogen for use in the energy economy. The search for thermodynamically viable LOHC molecules for real world use has led to a set of constraints on the dehydrogenation enthalpy and the minimum gravimetric hydrogen capacity. These constraints allow one to formulate the search for an ideal LOHC candidate molecule as an optimization problem well suited to the strengths of machine learning and artificial intelligence computational approaches. A critical barrier to a large-scale, high-throughput screening of LOHC candidate molecules is the lack of reliable training data. Computational electronic structure methods including density functional theory, coupled cluster approximations, and diffusion Monte Carlo can be used to provide training data where experimental data are either unreliable or do not exist. In this work, we use these methods to calculate the dehydrogenation energies and enthalpies of candidate LOHC molecules.

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

X‑ray Coherent Diffractive Imaging of Large Helium Nanodroplets Doped with Small Molecules

We report the first X-ray coherent diffractive imaging experiment on molecule-doped helium nanodroplets. It complements previous work, where we reported single-shot X-ray coherent diffractive imaging studies of Xe dopant clusters formed in 4He and 3He droplets. These noble gas clusters were used to visualize the impact of rotational excitation of the droplets on the spatial distribution of atomic dopants within the droplets, and to study the differences and connections between quantum and classical droplet rotational motion. Here, we expand our studies to the molecular dopants CF4, CHF3, CH3CN, and SF6, imaged with 1.5 keV photons. We find multiple Bragg spots in the diffraction patterns of molecule-doped droplets with radii of approximately 600 nm, which provide evidence that molecules form elongated clusters with preferential alignment along the angular momentum axis of the 4He droplets, in agreement with our previous results on the aggregation of Xe clusters on quantum vortices. Real-space reconstructions of molecular dopant cluster density profiles are obtained for droplets with smaller radii of approximately 300 nm. The diffuse images suggest the formation of low-density, potentially porous, molecular clusters upon aggregation at T = 0.4 K in 4He droplets. In the normal fluid 3He droplets, molecules aggregate into loose clusters on the droplets' equator, similar to previous observations for Xe atoms. Time-of-flight mass spectra reveal that the doped helium nanodroplet moieties fragment extensively into constituent atomic ions, producing only a small fraction of molecular fragment ions. The findings are discussed in the context of previously proposed schemes to use He droplets as potential tamper materials for ultrafast X-ray imaging experiments.

Feinberg, AlexandraJ↗
DOE OSTI2025

Spin-Polarized Oxygen Evolution Reaction Enabled by Chiral Molecules Coupled with Ferromagnetic Electrocatalysts

The discovery of chirality-induced spin selectivity (CISS) revolutionized our understanding of the capabilities of chiral molecules, revealing that chiral molecules can function as spin filters, aligning the spin orientation of electrons when they transmit through them. Recently, CISS has been exploited to direct energy conversion, especially the oxygen evolution reaction (OER). However, despite the remarkable progress that has been achieved, the effect of CISS in influencing the intermediate species formation and changing the rate-determining step (RDS) is still vague. To understand those key reaction mechanism steps, electrocatalysts with distinct magnetic characteristics, ferromagnetic CoFe2O4 and paramagnetic Co3O4, were synthesized. The results show that spin-polarized charge carriers retain their spin alignment when coupled with ferromagnetic CoFe2O4, akin to the behavior observed under a magnetic field. The Tafel analysis and kinetic isotope studies (kinetic isotope effect) suggest that in the absence of chiral molecules, the initial electron transfer step, the formation of O* species, governs the rate-determining step (RDS). However, introducing chiral molecules shifts the RDS to a combination of the first and second electron transfers, leading to the formation of OOH*. This conclusion was further supported by in situ infrared spectroscopy, which shows that l-methionine-modified CoFe2O4 (l-CoFe2O4) promotes the formation of OOH*, a key intermediate for O2 generation. This study highlights the critical role of CISS in affecting the OER mechanism and intermediate species formation.

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

Tunable Spin Qubit Pairs in Quantum Dot–Molecule Conjugates

Organic molecules and quantum dots (QDs) have both shown promise as materials that can host quantum bits (qubits). This is in part because of their synthetic tunability. The current work employs a combination of both materials to demonstrate a series of tunable quantum dot–organic molecule conjugates that can both host photogenerated spin-based qubit pairs (SQPs) and sensitize molecular triplet states. The photogenerated qubit pairs, composed of a spin-correlated radical pair (SCRP), are particularly intriguing since they can be initialized in well-defined, nonthermally populated, quantum states. Additionally, the radical pair enables charge recombination to a polarized molecular triplet state, also in a well-defined quantum state. The materials underlying this system are an organic molecular chromophore and electron donor, 9,10-bis(phenylethynyl)anthracene, and a quantum dot acceptor composed of ZnO. We prepare a series of quantum dot–molecule conjugates that possess variable quantum dot size and two different linker lengths connecting the two moieties. Optical spectroscopy revealed that the QD–molecule conjugates undergo photoexcited charge separation to generate long-lived charge-separated radical pairs. The resulting spin states are probed using light-induced time-resolved electron paramagnetic resonance (TR-EPR) spectroscopy, revealing the presence of singlet-generated SCRPs and molecular triplet states. Notably, the EPR spectra of the radical pairs are dependent on the geometry of this highly tunable system. The g value of the ZnO QD anion is size tunable, and the line widths are influenced by radical pair separation. Overall, this work demonstrates the power of synthetic tunability in adjusting the spin specific addressability, satisfying a key requirement of functional qubit systems.

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

Single-molecule live-cell RNA imaging with CRISPR–Csm

Abstract Understanding the diverse dynamic behaviors of individual RNA molecules in single cells requires visualizing them at high resolution in real time. However, single-molecule live-cell imaging of unmodified endogenous RNA has not yet been achieved in a generalizable manner. Here, we present single-molecule live-cell fluorescence in situ hybridization (smLiveFISH), a robust approach that combines the programmable RNA-guided, RNA-targeting CRISPR–Csm complex with multiplexed guide RNAs for direct and efficient visualization of single RNA molecules in a range of cell types, including primary cells. Using smLiveFISH, we track individual nativeNOTCH2andMAP1Btranscripts in living cells and identify two distinct localization mechanisms including the cotranslational translocation ofNOTCH2mRNA at the endoplasmic reticulum and directional transport ofMAP1BmRNA toward the cell periphery. This method has the potential to unlock principles governing the spatiotemporal organization of native transcripts in health and disease.

Biotechnology & Applied Microbiology↗
DOE OSTI2026

Advancing density functional tight-binding method for large organic molecules through equivariant neural networks

Semi-empirical quantum-mechanical (QM) methods have become valuable tools for studying complex (bio)molecular systems due to their balance between computational efficiency and accuracy. A key aspect of these methods is their parameterization, which not only governs the reliability of the results but also provides an opportunity to enhance their overall performance. In our previous work [J. Phys. Chem. Lett., 2021, 11, 16], we advanced the third-order semi-empirical density functional tight-binding (DFTB3) method for computing multiple properties of small molecules by developing the machine learning (ML) potential NN rep to bridge the gap between DFTB3 electronic components and those of the hybrid DFT-PBE0 functional. To overcome the limitations of NN rep , we introduce the EquiDTB framework, which leverages physics-inspired equivariant neural networks (NN) to parameterize scalable and transferable many-body Δ TB potentials, replacing the standard pairwise DFTB repulsive potential. This advancement extends the applicability of our ML-corrected DFTB approach to larger molecules and non-covalent systems (including only C, N, O, and H atoms), going beyond the chemical space represented in the training QM datasets. The enhanced performance of EquiDTB over the standard TB methods is demonstrated by the accurate computation of the atomic forces of S66x8 molecular dimers, as well as their interaction energies. Moreover, EquiDTB can be effectively employed to explore the potential energy surfaces of large and flexible drug-like molecules—for example, to determine the minimum energy path between isomers, analyze structural transitions during dynamical simulations, compute vibrational modes, and investigate energetic rankings. The performance for single molecules slightly decreases when the DFTB electronic energy is reduced to first-order but remains superior to standard TB methods. Our work thus demonstrates that an optimal integration of an equivariant NN with QM datasets can advance the DFTB method while maintaining high efficiency, paving the way for reliable (bio)molecular simulations.

Medrano Sandonas, Leonardo [Technische Universität↗
DOE OSTI2024

Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?

Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique “fingerprint” of a molecule. The availability of large molecular databases and the development of artificial intelligence methods for spectroscopy make the testing of this assumption timely. In this paper, we pose the determination of molecular structures from rotational spectra as an inverse problem. Within this framework, we adopt a funnel-based approach to search for molecular twins, which are two or more molecules, which have similar rotational spectra but distinctly different molecular structures. Here we demonstrate that there are twins within standard levels of computational accuracy by generating rotational constants for many molecules from several large molecular databases, indicating that the inverse problem is ill-posed. However, some twins can be distinguished by increasing the accuracy of the theoretical methods or by performing additional experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

ZnO quantum dot–molecule conjugates: Chemical interactions, charge dynamics, and spin polarization

Conjugates between molecules and quantum dots (QDs) have been explored for a range of potential applications from photocatalysis and photovoltaics to quantum information science technologies. A particularly ubiquitous material in many of these applications are ZnO QDs since they can accept and transport electrons and can also act as hosts for unique spin states. Conjugates between molecular light absorbers and ZnO QDs have been explored for decades as components in dye-sensitized solar cells. Recently, these materials have also attracted interest for their ability to produce spin-polarized states upon photoexcitation. The current paper employs a series of light absorbing perylene molecules with different ZnO QD sizes to explore key features of these QD–molecule conjugates: (1) chemical interactions, (2) charge dynamics, and (3) spin polarization. The chemical interactions between the molecules and QDs are determined with binding equilibria and reveal dramatic impact of ligand size. The charge transfer dynamics from photoexcited perylenes to ZnO QDs were found to depend exponentially on the linker length. Finally, time-resolved electron paramagnetic resonance experiments reveal that these conjugates generate spin-polarized states in the form of radical pairs and triplets. These spin states hold promise as potential qubits and also offer an avenue to efficiently sensitize molecular triplets.

Hernandez, Frida S. [Amherst College, MA (United S↗
DOE OSTI2025

Can increasing the size and flexibility of a molecule reduce decoherence and prolong charge migration?

Coherent superposition of electronic states, created by ionizing a molecule, can initiate ultrafast dynamics of the electron density. Correlation between nuclear and electron motions, however, typically dissipates the electronic coherence in only a few femtoseconds, especially in larger and more flexible molecules. We, therefore, use ab initio semiclassical dynamics to study decoherence in a sequence of analogous organic molecules of increasing size and find, surprisingly, that extending the carbon skeleton in propynal analogs slows down decoherence and prolongs charge migration. To elucidate this observation, we decompose the overall decoherence into contributions from individual vibrational modes and show that: 1) The initial decay of electronic coherence is caused by high- and intermediate-frequency vibrations via momentum separation of nuclear wavepackets evolving on different electronic surfaces. 2) At later times, the coherence disappears completely due to the increasing position separation in the low-frequency modes. 3) In agreement with another study, we observe that only normal modes that preserve the symmetry of the molecule induce decoherence. All together, we justify the enhanced charge migration by a combination of increased hole-mixing and the disappearance of decoherence contributions from specific vibrational modes—CO stretching in butynal and various H rockings in pentynal.

Science & Technology - Other Topics↗
DOE OSTI2025

Conveyor-belt magneto-optical trapping of molecules

Abstract Laser cooling is used to produce ultracold atoms and molecules for quantum science and precision measurement applications. Molecules are more challenging to cool than atoms due to their vibrational and rotational internal degrees of freedom. Molecular rotations lead to the use of type-II transitions ( F ⩾ F ′ ) for magneto-optical trapping (MOT). When typical red detuned light frequencies are applied to these transitions, sub-Doppler heating is induced, resulting in higher temperatures and larger molecular cloud sizes than realized with the type-I MOTs most often used with atoms. To improve type-II MOTs, Jarvis et al (2018 Phys. Rev. Lett. 120 083201) proposed a blue-detuned MOT to be applied after initial cooling and capture with a red-detuned MOT. This was successfully implemented (Burau et al 2023 Phys. Rev. Lett. 130 193401; Jorapur et al 2024 Phys. Rev. Lett. 132 163403; Li et al 2024 Phys. Rev. Lett. 132 233402), realizing colder and denser molecular samples. Very recently, Hallas et al (2024 arXiv:2404.03636) demonstrated a blue-detuned MOT with a ‘1+2’ configuration that resulted in even stronger compression of the molecular cloud. Here, we describe and characterize theoretically the conveyor-belt mechanism that underlies this observed enhanced compression. We perform numerical simulations of the conveyor-belt mechanism using both stochastic Schrödinger equation and optical Bloch equation approaches. We investigate the conveyor-belt MOT characteristics in relation to laser parameters, g -factors and the structure of the molecule, and find that conveyor-belt trapping should be applicable to a wide range of laser-coolable molecules.

Li, Grace K. (ORCID:0000000277223355)↗
DOE OSTI2024

Chemical reaction enhanced graph learning for molecule representation

Abstract Motivation Molecular representation learning (MRL) models molecules with low-dimensional vectors to support biological and chemical applications. Current methods primarily rely on intrinsic molecular information to learn molecular representations, but they often overlook effectively integrating domain knowledge into MRL. Results In this article, we develop a reaction-enhanced graph learning (RXGL) framework for MRL, utilizing chemical reactions as domain knowledge. RXGL introduces dual graph learning modules to model molecule representation. One module employs graph convolutions on molecular graphs to capture molecule structures. The other module constructs a reaction-aware graph from chemical reactions and designs a novel graph attention network on this graph to integrate reaction-level relations into molecular modeling. To refine molecule representations, we design a reaction-based relation learning task, which considers the relations between the reactant and product sides in reactions. In addition, we introduce a cross-view contrastive task to strengthen the cooperative associations between molecular and reaction-aware graph learning. Experiment results show that our RXGL achieves strong performance in various downstream tasks, including product prediction, reaction classification, and molecular property prediction. Availability and implementation The code is publicly available at https://github.com/coder-ACAC/RLM.

Biochemistry & Molecular Biology↗
DOE OSTI2024

Photoinitiated Reactions of Molecules and Radicals in Molecular Beams

The UV photochemistry of organic molecules is a fundamental process that governs reactions in the atmosphere, synthetic chemistry, processing of organic aerosols, and biological damage in living tissues. In many organic molecules, the ensuing evolution involves pathways that are in competition, giving rise to different products, isomerization, coupling to other electronic states, and secondary reactive collisions. Because photodissociation is usually fast (picoseconds to microseconds), these processes are far from equilibrium and are controlled by kinetic competition and dynamical forces. The work accomplished was focused primarily on the photochemistry of alpha-keto carboxylic acids, a group of acids produced from natural sources, which are implicated in aerosol formation and biological processes. In the atmosphere, they are destroyed mainly by solar radiation. Studying their photochemistry has been surprisingly difficult because of the complexity of their excited electronic states, and the effect of collisions and secondary reactions. The second project investigated the lifetime of excited electronic states of pyrazine and picoline and had both experimental and theoretical aspects. The work focused on a model molecule, pyruvic acid (PA), because it was hypothesized that it should be a good source of the unstable carbene, methylhydroxycarbene (MHC). PA has an internal hydrogen bond that controls the evolution of its decomposition. The decomposition was studied following excitation to two of its lowest excited states reached by laser irradiation at 351 and 193 nm. The photodissociation dynamics in the absence and presence of collisions was monitored and compared. Understanding the UV photochemistry requires the use of complementary experimental approaches. Two methods were enlisted, which together generated a comprehensive and detailed set of results: (i) The time-sliced velocity map imaging (SVMI) instrument at USC was exploited to determine kinetic energy release of fragments, fast dissociation timescales, and internal state distributions of fragments for which Resonance Enhanced Multiphoton Ionization (REMPI) schemes exist; and (ii) The multiplexed photoionization mass spectrometer (MPIMS) setup developed at the Sandia Combustion Research Facility was used for product discovery, achieved by exploiting tunable narrowband VUV radiation at the Advanced Light Source (ALS), and to follow in real time their subsequent unimolecular and bimolecular reactions. The experimental conditions ranged from collisionless molecular beams to study nascent products to flow reactors of variable pressures to study subsequent bimolecular reactions of the products. The goals stated above were successfully accomplished. By exciting PA to its lowest excited state, MHC was identified as the only primary product and its isomerization to vinylalcohol and acetaldehyde was directly observed in real time. Moreover, we reported the first bimolecular reaction of MHC, which was with acetaldehyde, and identified its reaction product. This paves the way for the study of other reactions of this important carbene intermediate. When excitation was carried out at 193 nm, which imparted much higher energy to PA, many more products were directly observed in real time, some deriving from three-body dissociation. Quantitative branching ratios and secondary reactions of radical products were also determined and analyzed. The studies of pyrazine and picoline focused on the second excited state of these molecules and showed (via ionization studies) that their excited states were very short lived (<100 fs) because of efficient couplings to lower electronic states via vibronic coupling. Theoretical work on modeling the absorption spectrum and decay mechanisms of the excited states are in progress in collaboration with theoreticians.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗