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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Birth of the Hydrated Electron via Charge-Transfer-to-Solvent Excitation of Aqueous Iodide

A primary means to generate hydrated electrons in laboratory experiments is excitation to the charge-transfer-to-solvent (CTTS) state of a solute such as I – (aq), but this initial step in the genesis of e – (aq) has never been simulated directly using ab initio molecular dynamics. Here, we report the first such simulations, combining ground- and excited-state simulations of I – (aq) with a detailed analysis of fluctuations in the Coulomb potential experienced by the nascent solvated electron. What emerges is a two-step picture of the evolution of e – (aq) starting from the CTTS state: I – (aq) + hν → I –* (aq) → I • (aq) + e – (aq). Notably, the equilibrated ground state of e – (aq) evolves from I –* (aq) without any nonadiabatic transitions, simply as a result of solvent reorganization. The methodology used here should be applicable to other photochemical electron transfer processes in solution, an important class of problems directly relevant to photocatalysis and energy transfer.

Carter-Fenk, Kevin↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific applications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Networks (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate bandwidths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer performance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application-level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher prediction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2020

Performance Prediction of Big Data Transfer Through Experimental Analysis and Machine Learning

Big data transfer in next-generation scientific ap- plications is now commonly carried out over connections with guaranteed bandwidth provisioned in High-performance Net- works (HPNs) through advance bandwidth reservation. To use HPN resources efficiently, provisioning agents need to carefully schedule data transfer requests and allocate appropriate band- widths. Such reserved bandwidths, if not fully utilized by the requesting user, could be simply wasted or cause extra overhead and complexity in management due to exclusive access. This calls for the capability of performance prediction to reserve bandwidth resources that match actual needs. Towards this goal, we employ machine learning algorithms to predict big data transfer perfor- mance based on extensive performance measurements, which are collected over a span of several years from a large number of data transfer tests using different protocols and toolkits between various end sites on several real-life physical or emulated HPN testbeds. We first identify a comprehensive list of attributes involved in a typical big data transfer process, including end host system configurations, network connection properties, and control parameters of data transfer methods. We then conduct an in-depth exploratory analysis of their impacts on application- level throughput, which provides insights into big data transfer performance and motivates the use of machine learning. We also investigate the applicability of machine learning algorithms and derive their general performance bounds for performance prediction of big data transfer in HPNs. Experimental results show that, with appropriate data preprocessing, the proposed machine learning-based approach achieves 95% or higher pre- diction accuracy in up to 90% of the cases with very noisy real-life performance measurements.

Yun, Daqing↗
DOE OSTI2022

Reactivity of Zn + aq in high-temperature water radiolysis

For this work, reactivity of transients involving Zn + in high-temperature water radiolysis has been studied in the temperature range of 25–300 °C. The reduced monovalent zinc species were generated from an electron transfer process between the hydrated electron and Zn 2+ ions using pulse radiolysis. The Zn + species can subsequently be oxidized by the radiolytically-produced oxidizing species: ˙OH, H 2 O 2 and ˙H. We find that the absorption of monovalent zinc is very sensitive to the pH of the medium. An absorption maximum at 306–311 nm is most pronounced at pH 7 and the signal then decreases in acidic media where the reducing electrons are competitively captured by protons. At pH values higher than 7, hydroxo-forms of Zn 2+ are created and the maximum of the absorption signal begins to shift to the red spectral region. We find that the optical spectrum of Zn + aq cannot be fully explained in terms of a charge-transfer to solvent (CTTS) process, which was previously proposed. Reaction rates of most of the recombination reactions investigated follow the empirical Arrhenius relationship at temperatures up to 200 °C and have been determined at higher temperatures for the first time. A bimolecular disproportionation reaction of Zn + aq is not observed under the conditions investigated.

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

Three‐Tier Hierarchical Structures for Extreme Pool Boiling Heat Transfer Performance

Abstract Boiling is an effective energy‐transfer process with substantial utility in energy applications. Boiling performance is described mainly by the heat‐transfer coefficient (HTC) and critical heat flux (CHF). Recent efforts for the simultaneous enhancement of HTC and CHF have been limited by an intrinsic trade‐off between them—HTC enhancement requires high nucleation‐site density, which can increase bubble coalescence resulting in limited CHF enhancement. In this work, this trade‐off is overcome by designing three‐tier hierarchical structures. The bubble coalescence is minimized to enhance the CHF by defining nucleation sites with microcavities interspersed within hemi‐wicking structures. Meanwhile, the reduced nucleation‐site density is compensated for by incorporating nanostructures that promote evaporation for HTC enhancement. The hierarchical structures demonstrate the simultaneous enhancement of HTC and CHF up to 389% and 138%, respectively, compared to a smooth surface. This extreme boiling performance can lead to significant energy savings in a variety of boiling applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fluid structural interaction simulation of the MP-1 plate performance irradiated in the advanced test reactor

Due to the high neutron fluxes they generate and increased heat transfer performance, plate type fuels are used in the U.S. high-performance research reactors. During irradiation, a significant amount of fission energy (i.e., ~200 MeV per atom) is released by the U-235 chain reaction that is carried away by the coolant. Through thermal hydraulic analysis, the coolant’s heat transfer capability is investigated to ensure that the desired fuel temperature can be maintained. At high temperatures, the plate undergoes elastic/plastic deformation, creep, and swelling as a result of both the temperature gradients and the fission gas production within the fuel. These effects are studied via fuel performance analysis. When the plate deformation is small enough that the coolant flow remains relatively unchanged, conducting these two types of analyses independently will suffice. But at high fuel burnups, the swollen plates may encroach into the coolant channels that separate the fuel plates from each other and cause these channels to narrow. Large reductions in channel gap size imperil cooling performance, causing fuel temperatures to rise. Further, if the plate deformation is asymmetric, the fuel centerline will shift toward one side of the channel, causing an uneven reduction in coolability. In addition, a boehmite (oxide) layer will, over time, grow on the plate surface, further obstructing the heat transfer process. To precisely predict fuel temperatures/deformation, a complete coupled analysis that considers coolant flow, heat transfer, oxide growth, elastic/plastic deformation, creep, and swelling is needed; however, this type of analysis method is not available in the literature. To fill the gap, this research developed a fluid structure interaction (FSI) approach to the fuel plate analysis, then successfully applied it to the Mini-Plate (MP)-1 experiment, which was irradiated in the Advanced Test Reactor (ATR) for both one and two cycles. The complete analysis coupled STAR-CCM+, a computational fluid dynamic (CFD) software for calculating flow, with Abaqus, a finite element analysis code for calculating plate deformation. Improvements in the results were found when comparing the fully coupled analysis to the independently conducted analyses but they were not significant due to the miniature size of the plates and the relatively short irradiation time. In the future, the fully coupled approach presented herein will be applied to full-size fuel plates with longer irradiation cycles once additional experiments become available.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Singly Reduced Iridium Chromophores: Synthesis, Characterization, and Photochemistry

One-electron reduced photosensitizers have been invoked as crucial intermediates in photoredox catalysis, including multiphoton excitation and electrophotocatalytic processes. However, such reduced chromophores have been less investigated, limiting mechanistic studies of their associated electron transfer processes. Here, we report a total of 11 different examples of isolable singly reduced iridium chromophores. Chemical reduction of a cyclometalated iridium complex with potassium graphite affords a 19-electron species. Structural and spectroscopic characterizations reveal a ligand-centered reduction product. The reduced chromophore absorbs a wide range of light from ultraviolet to near-infrared and exhibits photoinduced bimolecular electron transfer reactivity. Furthermore, these studies shed light on elusive reduced iridium chromophores in both ground and excited states, providing opportunities to investigate a commonly invoked intermediate in photoredox catalysis.

14 SOLAR ENERGY↗
DOE OSTI2024

Abstract for CRADA between Capture6 CORP and NETL

The National Energy Technology Laboratory (NETL) and Capture6 CORP (Participant) will collaborate to refine Capture6’s transformative air contactor design for optimal direct air capture (DAC) under an awarded project from the Department of Energy’s Direct Air Capture Pre-Commercialization Technology Prize. Current cooling tower designs require exponentially more resources as the concentration of CO 2 in the gas phase decreases, resulting in a low conversion rate of carbonates, a large physical footprint, and high evaporation of water, which consequently limits the energy and water benefits that a DAC process can create. Capture6’s innovative tower design AURA (Absorption Unit Reactor for Ambient air) seeks to improve the mass transfer characteristics of legacy cooling towers and reduces total energy demand by: (1) introducing laminar and turbulent flow to increase mass transfer, (2) generating a solvent gradient to improve CO 2 absorption, (3) leveraging venturi and packed towers to increase the surface for the mass-transfer process, (4) adding charged/cool plates to reduce overall water loss in the system, and (5) utilizing surfactant additives to increase mass transfer. The collaboration will facilitate the deployment of technologies that reduce the total energy required and carbon footprint of solvent-based carbon dioxide removal (CDR) technologies. The anticipated results support NETL’s goal of fostering rapid development and commercialization pathways for technologies that remove CO 2 from the atmosphere.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Phonon-Mediated Ultrafast Hole Transfer from Photoexcited CdSe Quantum Dots to Black Dye

We have applied non-adiabatic molecular dynamics (NAMD) and Fewest Switching surface hopping (FSSH) method to simulate the energy dissipation and charge transfer processes in the CdSe quantum dot (QD) functionalized by the Black dye. Our calculations reveal ultrafast hole transfer from the photoexcited QD to the dye, despite a significant energy splitting between QD’s and dye’s occupied states. The mechanism of such ultrafast QD-to-dye hole transfer is rationalized by strong non-adiabatic couplings between the delocalized surface orbitals of the QD and the high-frequency vibrations of isothiocyanate ligands of the Black dye. Here, this mechanism is also confirmed by a very rapid lose of coherency of the excitation due to strong electronic couplings with vibrational modes of the dye.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Dynamics of iodine geminate recombination in supercritical xenon solvent: Caging effect

Understanding the dynamics of chemical reactions in solutions is vital, as their rates and kinetics are significantly affected by the solvent environment. Supercritical solvents offer extensive applications in chemical reactions by enabling the manipulation of the solution environment. Here, in this study, we investigate the geminate recombination of iodine in a supercritical xenon solvent by using ReaxFF-based molecular dynamics simulations. Our findings reveal that the highest iodine recombination rate occurs near supercritical conditions, while lower-pressure conditions lead to reduced collision rates and unstable recombination, and higher-pressure conditions hinder iodine diffusion, resulting in a lower recombination rate. Our analysis shows that the xenon local density at the time of recombination is at least 2.5 times higher than the global density, confirming the presence of xenon clusters surrounding the Iodine atoms. This observation is further supported by coordination number analysis, which confirms an elevated xenon local density during recombination. In addition, the correlation between the total energy of xenon atoms within a cluster and recombined iodine atoms underscores the kinetic energy transfer process, validating the occurrence of geminate recombination. The excess kinetic energy from the recombining iodine atoms is transferred to the surrounding xenon atoms. Our examination of geminate recombination demonstrates that iodine atoms confined within xenon clusters—whether through manual insertion of atoms or the fast dissociation of an iodine molecule within xenon clusters—are more likely to recombine as primary geminate recombination. However, extending the iodine molecule dissociation time allows iodine atoms to diffuse out of the cluster, and the recombination to shift toward secondary geminate recombination.

Cage effect↗
DOE OSTI2026

Energy Transfer in Lanthanide Luminescent Complexes

The primary objective of this project was to investigate the mechanisms of energy transfer in lanthanide luminescent complexes, focusing on elucidating the role of ligand-to-metal charge transfer processes and the efficiency of sensitization mechanisms. Specifically, this work aimed to determine the mechanistic details of energy transfer pathways in systems incorporating lanthanide ions such as terbium and europium, with a focus on advancing the application of these complexes in molecular imaging and photonic technologies.

Raymond, Kenneth [University of California, Berkel↗
DOE OSTI2020

Emission Control from Transition Metal Dichalcogenide Monolayers by Aggregation-Induced Molecular Rotors

Organic–inorganic (O–I) heterostructures, consisting of atomically thin inorganic semiconductors and organic molecules, present synergistic and enhanced optoelectronic properties with a high tunability. Here, we develop a class of air-stable vertical O–I heterostructures comprising a monolayer of transition-metal dichalcogenides (TMDs), including WS 2 , WSe 2 , and MoSe 2 , on top of tetraphenylethylene (TPE) core-based aggregation-induced emission (AIE) molecular rotors. The created O–I heterostructures yields a photoluminescence (PL) enhancement of up to ~950%, ~500%, and ~330% in the top monolayer WS 2 , MoSe 2 , and WSe 2 as compared to PL in their pristine monolayers, respectively. The strong PL enhancement is mainly attributed to the efficient photogenerated carrier process in the AIE luminogens (courtesy of their restricted intermolecular motions in the solid state) and the charge-transfer process in the created type I O–I heterostructures. Moreover, we observe an improvement in photovoltaic properties of the TMDs in the heterostructures including the quasi-Fermi level splitting, minority carrier lifetime, and light absorption. Overall, this work presents an inspiring example of combining stable, highly luminescent AIE-based molecules, with rich photochemistry and versatile applications, with atomically thin inorganic semiconductors for multifunctional and efficient optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Production of neutron-rich heavy nuclei in deep-inelastic 208 Pb + 208 Pb collisions within the stochastic mean-field theory

In deep-inelastic collisions of heavy nuclei, reaction products with a wide range of mass and charge are produced. Such collisions been considered as a possible way to produce superheavy nuclei, as an alternative to fusion reactions. To provide reliable theoretical predictions, it is desired to develop microscopic approaches that correctly and accurately describe nucleon transfer processes in dissipative collisions of heavy nuclei. The purpose of the present work is (1) to investigate the mechanism of nucleon transfers in dissipative collisions of two heavy nuclei, and (2) to explore possible pathways to produce neutron-rich heavy nuclei, through detailed theoretical analyses of fluctuations and correlations in nucleon transfers in 208 Pb + 208 Pb reactions. Three-dimensional time-dependent Hartree-Fock (TDHF) calculations are performed for the collisions of 208 Pb + 208 Pb at 𝐸 c.m. = 832, 936, and 1040 MeV, using the Skyrme SLy4d energy density functional. To calculate fluctuations and correlations in nucleon transfers, we employ the stochastic mean-field (SMF) theory, and the results are compared with another theoretical framework currently available, the time-dependent random phase approximation (TDRPA). Primary and secondary production cross sections are calculated with the SMF theory combined with a statistical model, GEMINI ++ . Using information of nucleon flow across a neck of colliding nuclei in TDHF calculations, we solve quantal diffusion equations for fluctuations and correlations in nucleon transfers based on the SMF theory. From the SMF calculations, we obtain the time evolution of diffusion coefficients as well as fluctuations and correlations in nucleon transfers for a range of initial orbital angular momenta. We compare the results of the SMF calculations with those of TDRPA, showing that TDRPA tends to predict substantially larger fluctuations and correlations in strongly damped collisions of heavy nuclei, which exhibit complex initial angular momentum dependence, while the SMF results provide almost constant (stable) values. Using the obtained fluctuations and correlations, we calculate primary and secondary production cross sections for the 208 Pb + 208 Pb collisions. From the results, we find that both lighter and heavier reaction products as compared to 208 Pb are produced for a wide region in the 𝑁−𝑍 plane as primary products, thanks to the quantal diffusion mechanism in the dissipative collisions. However, we show that cross sections for production of heavy nuclei with 𝑍 ≳ 90 or 𝑁 ≳ 135 are washed out due to secondary particle evaporation and/or fission processes. On the other hand, we find that there remain sizable cross sections for production of neutron-rich nuclei along 𝑁 = 126 with 𝑍< 82, even after secondary disintegration processes. We demonstrate that the secondary production cross sections depend weakly on incident energies, but lower (higher) energy is slightly preferred for production of nuclei with smaller (larger) atomic numbers as compared to 𝑍 = 82. Here, based on the microscopic SMF calculations, it has been shown that deep-inelastic collisions of heavy nuclei, such as 208 Pb + 208 Pb examined in this study, can be a promising means to produce neutron-rich heavy nuclei along 𝑁=126. Discrepancies between the SMF and TDRPA approaches are left unsolved for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Linking transportation agent-based model ($\mathrm{ABM}$) outputs with micro-urban social types ($\mathrm{MUSTs}$) via typology transfer for improved community relevance

The human relationship with transportation is shaped by social, economic, demographic, and urban form variables, or socio-spatial factors. The spatial dynamics of these are key to generating and interpreting outputs of transportation models that are most relevant for a community and the diverse mobility needs of its members. Here we present a typology transfer framework, grounded in socio-spatial dynamics shaping people's mobility, to take transportation-themed regional mobility model outcomes, in this case from two agent-based models (ABMs), and extrapolate them to other cities, with less time and resource intensity than new ABM development. The typology transfer process first identifies micro-urban social types (MUSTs) using socio-spatial factors, then defines city types based on spatial patterns of MUSTs to assess across which cities transfer results are likely to best hold. Lastly, a typology transfer multiplier matrix extrapolates a given variable, in our case the Mobility Energy Productivity (MEP) metric, to another city. The full process demonstration uses ABM results from Chicago (POLARIS model) and San Francisco (BEAM model), applying them to New York City. We discuss how MEP or other outputs can be appropriately estimated and used for integrated, human-centered mobility analysis. Key findings include that this MUST framework of user-defined dependent and independent variables allows tailoring ABM results and interpretations to specific community needs and data availability. Findings clarify that positive outcomes can be targeted towards user groups, based on sociospatial characteristics, using a typology approach, such as inclusive access to mobility choices, transportation affordability, and greater efficiency in resource use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Call attention to using DRT and EIS to quantify the contributions of solid oxide cell components to the total impedance

The contributions of anode and cathode processes to solid oxide fuel cell (SOFC) impedance were studied using electrochemical impedance spectroscopy (EIS) and distribution of relaxation time (DRT). Specifically, the role of gas composition at both anode and cathode was explored in a systematic study aimed at deconvoluting, identifying and quantifying the contributions of different anode and cathode processes. Further, five distinct relaxation time distributions were observed in the DRT spectra; although the peaks were ascribed to diffusion and charge transfer processes at the electrodes, it was found that both electrodes contributed to various peaks at the same time. Moreover, it was found that two distinctive operating conditions could return equivalent DRT spectra. While DRT analysis allows to obtain useful information regarding cell performance, extra consideration is needed when assessing and quantifying anodic and cathodic resistances within the SOFC.

08 HYDROGEN↗
DOE OSTI2021

Thermal conductivity modeling of monodispersed microspheres using discrete element method

Particle beds are widely used in various systems and processes, such as particle heat exchangers, granular flow reactors, and additive manufacturing. Accurate modeling of the thermal conductivity of particle beds and understanding of their heat transfer mechanisms are important. However, previous models were based on simple cubic packing of particles, which could not accurately represent the actual heat transfer processes under certain conditions. Here, we examine the effect of the packing structure on the thermal conductivity of particle beds. We use monodispersed silica microspheres with average particle sizes ranging from 23 to 330 μm as a model material. We employ a transient hot-wire technique to measure the thermal conductivity of the particle beds with packing density of 43%–57% within a temperature range of room temperature to 500 °C and under N2 gaseous pressures of 20–760 Torr. We then use a discrete element method (DEM) to obtain the realistic packing structure of the particles, which is then fed into a finite-element model (FEM) to calculate the thermal conductivity, with the consideration of solid conduction, gas conduction, and radiation heat transfer. Our results show that the thermal conductivity model based on the more realistic random packing structure derived from the DEM shows better agreement with the experimental data compared to that based on the simple cubic-packing structure. The combined DEM and FEM methodology can serve as a useful tool to predict the effective thermal conductivity of particle beds and to quantify different heat transfer mechanisms under various conditions.

14 SOLAR ENERGY↗
DOE OSTI2020

Efficient Hot Electron Transfer from Small Au Nanoparticles

Many important chemical transformations enabled by plasmonic hot carrier photocatalysis have been reported, although their efficiencies are often too low for practical applications. Here, we examine how the efficiency of plasmon-induced hot electron transfer depends on the Au particle size in Au-tipped CdS nanorods. We show that with decreasing Au size, the plasmon width increases due to enhanced surface damping contributions. The excitation of Au nanoparticles leads to an instrument response time-limited ultrafast hot electron transfer process to CdS ($\ll$140 fs). The quantum efficiency of this process increases from ~1% to ~18% as the particle size decreases from 5.5 ± 1.1 to 1.6 ± 0.5 nm due to both enhanced hot electron generation and transfer efficiencies in small Au particles. Our finding suggests that decreasing plasmonic particle size is an effective approach for improving plasmon-induced hot carrier transfer efficiency and provides important insight for the rational improvement of plasmonic hot carrier-based devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Energy Migration Processes in Re(I) MLCT Complexes Featuring a Chromophoric Ancillary Ligand

We present herein the synthesis, structural characterization, electronic structure calculations, and ultrafast and supra-nanosecond photophysical properties of a series of five Re(I) bichromophores exhibiting metal to ligand charge transfer (MLCT) excited states based on the general formula fac -[Re(N ^ N)(CO) 3 (PNI-py)]PF 6, where PNI-py is 4-piperidinyl-1,8-naphthalimidepyridine and N ^ N is a diimine ligand ( Re1 – 5 ), along with their corresponding model chromophores where 4-ethylpyridine was substituted for PNI-py ( Mod1 – 5 ). The diimine ligands used include 1,10-phenanthroline (phen, 1 ), 2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline (bcp, 2 ), 4,4'-di- tert -butyl-2,2'-bipyridine (dtbb, 3 ), 4,4'-diethyl ester-2,2'-bipyridine (deeb, 4 ), and 2,2'-biquinoline (biq, 5 ). In these metal–organic bichromophores, structural modification of the diimine ligand resulted in substantial changes to the observed energy transfer efficiencies between the two chromophores as a result of the variation in 3 MLCT excited-state energies. The photophysical properties and energetic pathways of the model chromophores were explored in parallel to accurately track the changes that arose from introduction of the organic chromophore pendant on the ancillary ligand. All relevant photophysical and energy transfer processes were probed and characterized using time-resolved photoluminescence spectroscopy, ultrafast and nanosecond transient absorption spectroscopy, and time-dependent density functional theory calculations. Of the five bichromophores in this study, four ( Re1 – 4 ) exhibited a thermal equilibrium between the 3 PNI-py and the 3 MLCT excited state, drastically extending the lifetimes of the parent model chromophores.

14 SOLAR ENERGY↗