Search NASA⌕ Search

SEARCH · Search NASA

Results for “dynamic solar control”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Survey of Multizone Airflow Simulation Software

H-Canyon simulates the building and process ventilation to ensure positive contamination control for any modifications as well as evaluating off-normal conditions. Simulations can also be used to identify air quality of personnel occupied areas. The models can be classified into two groups, single and multi-zone models. As the name states, a single zone model assumes that the building can be described by a single, well-mixed zone. Whereas large buildings have structures that must be described as multizone. Multizone airflow models deal with the difficulty of flows in a building by distinguishing the effects of internal flow restrictions. Several models have been developed that take internal partitions into account. CONTAM (currently used) is a multizone airflow program created by NIST to determine airflows including infiltration, exfiltration, wind pressures acting outside the building, buoyancy effects caused by the indoor and outdoor air temperature difference. COMIS is a multizone air infiltration, ventilation, and contaminant transport model that was developed at Lawrence Berkeley National Laboratory. COMIS deals with applied pressure distribution, airflow components, HVAC systems, schedules, and contaminant transport. EnergyPlus is designed by DOE. It supports flexible component level configuration of HVAC models and simulates sub-hourly time steps to control fast dynamic systems. The program features include providing accurate environmental performance data including energy consumption and carbon emissions, and reporting solar gains on surfaces. Heavent is used to model industrial ventilation systems to control airborne contaminants. It's designed based on the American Conference of Governmental Industrial Hygienists (ACGIH) Ventilation manual. DesignBuilder is the most recognized and advanced user interface to EnergyPlus. It gives access to all of the most frequently required simulation capabilities covering building fabric, thermal mass, glazing, shading renewables, and HVAC analysis. The objective of this study is to identify all relevant software available including commercially licensed, freely licensed, and open source, that can be used to simulate large, complex process facility ventilation systems. All discovered software tools are evaluated for salient features and compared to the software tool currently used to simulate the H-Canyon ventilation system. The design criteria of a ventilation system has two basic requirements: Supplying fresh air for the occupants and changing the air in the room sufficiently; therefore, the smells, fumes, and contaminants will be removed. In this study, first, whether the software simulates airflow (infiltration, natural ventilation, and interzonal) or considers them to be inputs is discussed. Second, if indoor contaminant levels are considered; and finally suggestions on how airflow analysis can be more appropriately accounted for when performing airflow simulation of a building. All of the airflow software reviewed for this study can account for constant infiltration and natural ventilation rates that are not affected by changes in indoor and outdoor conditions. Modelling infiltration in EnergyPlus or DesignBuilder are applicable for small buildings and not appropriate for larger buildings like the H-Canyon. The effect of wind on external pressures, infiltration, and natural and mechanical ventilation, can also be calculated using all of these software. These programs have control options to switch between natural to mechanical ventilation modes or both (hybrid). Interzonal airflow can be applied which means one zone can be specified to receive a fixed amount of air from another zone. The following ventilation modeling software is recommended for further testing: CONTAM, COMIS, Heavent. The next step in evaluating the software will consist of creating test facility simulations using evaluation copies of the software.

42 ENGINEERING↗
DOE OSTI2026

Rotation‐Controlled Diurnal Evolution of Uranus' Asymmetric Bow Shock at Equinox

Uranus possesses the most extreme magnetic and rotational geometry in the solar system, resulting in a uniquely dynamic and asymmetric interaction between its magnetosphere and the solar wind. Here we investigate the diurnal evolution of the Uranian bow shock (BS) at equinox using global multifluid magnetohydrodynamic simulations constrained by Voyager 2 observations. The BS structure and variability are quantified using the stand‐off distance, terminator distance, flaring parameter, and BS parameter, enabling a systematic assessment of its global asymmetry over one planetary rotation. Our results show that the BS exhibits pronounced diurnal asymmetry that is primarily controlled by planetary rotation. Even under steady upstream solar wind conditions, the BS undergoes periodic expansion and contraction, reflecting rotation‐driven reconfiguration of the planetary magnetospheric topology. This diurnal modulation represents a remarkably large asymmetry in planetary BS geometry within the solar system. These results establish planetary rotation as the intrinsic primary driver of Uranus' BS dynamics at equinox and provide essential constraints for the design and formulation of future space missions to the ice giants. These findings also offer a unique framework for understanding shock physics in the abundant population of ice‐giant exoplanets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Feedback Control Approaches for Restoration of Power Grids from Blackouts

The automated restoration of power systems with variable energy resources is a timely problem to tackle. Automated restoration advice can support operators in deciding on strategic actions to restore power grids from a blackout with a mix of conventional and renewable generation resources. To this end, this paper frames the restoration process of power grids with solar resources as a nonlinear dynamic model with algebraic constraints in discrete time which is steered by feedback control loops. We discuss two feedback-control strategies based on greedy and reinforcement learning algorithms, and contrast their performance with restoration plans generated by a mixed-integer linear program. We found that the reinforcement learning algorithm infers restoration actions faster than the greedy one. However, the tuning process of the reinforcement learning parameters is slower than for the greedy one.

machine learning↗
DOE OSTI2021

Dynamic structural views in solar energy materials by femtosecond electron diffraction

Solar materials convert light into other forms of energy through excited state processes occurring on ultrafast time and atomic length scales. Understanding and controlling such nonequilibrium processes is essential for applications ranging from photovoltaics to photocatalysis. These processes are commonly studied by transient optical techniques, which resolve charge carrier dynamics. However, optical spectroscopy does not directly probe the atomic-scale motions that play a central role in the ultimate functionality of these materials. Filling this missing gap, ultrafast electron and x-ray scattering techniques enable monitoring of structural dynamics in materials with femtosecond time resolution. In this work, we focus on the use of ultrafast electron diffraction (UED) techniques to probe photoinduced energy conversion dynamics in solar energy materials. First, we discuss the use of UED as an ultrafast lattice thermometer allowing a direct probe of nonradiative relaxations such as hot carrier cooling and Auger recombination. Second, we present a time-resolved atomic pair distribution function analysis enabled by UED, which uncovers lattice deformations arising from excitation localization in materials. Finally, we provide an outlook looking toward new approaches for resolving in situ energy conversion dynamics and uncovering structure–property relationships in solar energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

From Femtoseconds to Gigaseconds: The SolDeg Platform for the Performance Degradation Analysis of Silicon Heterojunction Solar Cells

Heterojunction Si solar cells exhibit notable performance degradation. Here, we modeled this degradation by electronic defects getting generated by thermal activation across energy barriers over time. To analyze the physics of this degradation, we developed the SolDeg platform to simulate the dynamics of electronic defect generation. First, femtosecond molecular dynamics simulations were performed to create a-Si/c-Si stacks, using the machine learning-based Gaussian approximation potential. Second, we created shocked clusters by a cluster blaster method. Third, the shocked clusters were analyzed to identify which of them supported electronic defects. Fourth, the distribution of energy barriers that control the generation of these electronic defects was determined. Fifth, an accelerated Monte Carlo method was developed to simulate the thermally activated time-dependent defect generation across the barriers. Our main conclusions are as follows. (1) The degradation of a-Si/c-Si heterojunction solar cells via defect generation is controlled by a broad distribution of energy barriers. (2) We developed the SolDeg platform to track the microscopic dynamics of defect generation across this wide barrier distribution and determined the time-dependent defect density N(t) from femtoseconds to gigaseconds, over 24 orders of magnitude in time. (3) We have shown that a stretched exponential analytical form can successfully describe the defect generation N(t) over at least 10 orders of magnitude in time. (4) We found that in relative terms, Voc degrades at a rate of 0.2%/year over the first year, slowing with advancing time. (5) We developed the time correspondence curve to calibrate and validate the accelerated testing of solar cells. We found a compellingly simple scaling relationship between accelerated and normal times t normal ∝ t accel T(accel)/T(normal) . (6) We also carried out experimental studies of defect generation in a-Si:H/c-Si stacks. We found a relatively high degradation rate at early times that slowed considerably at longer time scales.

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

Controllable Solar Flux Heating for Freeze Recovery in Molten Salt Parabolic Trough Collectors

In molten-salt parabolic trough plants, the melting process is particularly important for freeze recovery of salt that is solidified in a collector loop, should such an event occur. Currently impedance heating is expected for freeze recovery of the collector loops, but this method can be expensive. Here, a lower-cost alternative is proposed to use controllable concentrated solar flux directly from the parabolic mirrors to thaw salt that is frozen in the collector. A computational fluid dynamics model was developed to explore the solidification and melting processes of molten salt in a parabolic trough receiver and to assess the viability of this concept. Results indicate that concentrated solar heating has the potential to melt frozen salt in 5.6 h, compared to that in 8.8 h for a 300 W m –1 impedance heating system. At the same time, controllable solar flux heating introduces nonuniform solar fluxes on the receiver surface, which can induce significant thermal stress on the receiver tube. A preliminary stress analysis indicates that the temperature difference across the receiver tube should be maintained below about 70 °C for heating up to 300 °C at internal pressures ≤10 bar. At these conditions, freeze recovery using solar flux heating will not significantly affect receiver lifetime. These results suggest that controllable solar flux heating could effectively supplement or replace impedance heating in the freeze recovery system. Incorporating this methodology in future parabolic trough concentrating solar power plants is an opportunity for capital and operational cost-savings.

14 SOLAR ENERGY↗
DOE OSTI2023

Modeling and control of nuclear–renewable integrated energy systems: Dynamic system model for green electricity and hydrogen production

The need for decarbonization and diversification of energy resources has led to the development of integrated energy systems (IESs), where multiple resources supply more than one energy sector. Here, one such IES with small modular nuclear reactors and renewables (wind and solar) as generating resources, catering to the demand of the electric grid while producing hydrogen for industries, is modeled in this paper. The physics-based component models are represented using the Modelica language and interconnected to form the IES. The control and coordination of the overall system are ensured by designing a suitable control architecture composed of individual subsystem-level controls and supervisory control. The dynamic performance and the load-following capability of the IES are evaluated, while satisfying the safe operational limits of the components. Different configurations and modes of IES operation are considered, where the adaptability of the control system in the presence of varying demands and renewable generations is validated. The simulation results indicate that hydrogen as a flexible load facilitates the supply of varying grid demand. Additionally, the renewables are also accommodated into the IES owing to the flexibility of the balance of plant associated with the nuclear reactors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Integrated Dynamic Facade Control with an Agent-based Architecture for Commercial Buildings

Dynamic façades have significant technical potential to minimize heating, cooling, and lighting energy use and peak electric demand in the perimeter zone of commercial buildings, but the performance of these systems is reliant on being able to balance complex trade-offs between solar control, daylight admission, comfort, and view over the life of the installation. As the context for controllable energy-efficiency technologies grows more complex with the increased use of intermittent renewable energy resources on the grid, it has become increasingly important to look ahead towards more advanced approaches to integrated systems control in order to achieve optimum life-cycle performance at a lower cost. This study examines the feasibility of a model predictive control system for low-cost autonomous dynamic façades. A system architecture designed around lightweight, simple agents is proposed. The architecture accommodates whole building and grid level demands through its modular, hierarchical approach. Automatically-generated models for computing window heat gains, daylight illuminance, and discomfort glare are described. The open source Modelica and JModelica software tools were used to determine the optimum state of control given inputs of window heat gains and lighting loads for a 24-hour optimization horizon. Penalty functions for glare and view/ daylight quality were implemented as constraints. The control system was tested on a low-power controller (1.4 GHz single core with 2 GB of RAM) to evaluate feasibility. The target platform is a low-cost ($35/unit) embedded controller with 1.2 GHz dual-core cpu and 1 GB of RAM. Configuration and commissioning of the curtainwall unit was designed to be largely plug and play with minimal inputs required by the manufacturer through a web-based user interface. An example application was used to demonstrate optimal control of a three-zone electrochromic window for a south-facing zone. The overall approach was deemed to be promising. Further engineering is required to enable scalable, turnkey solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Forward Feedback Control Scheme for a Solar Thermochemical Moving Bed Counter-Current Flow Reactor

Abstract Pelletized thermochemical energy storage media has a potential for long-duration energy storage. Production of solid-state energy storage media can be done within a cavity chemical reactor that captures concentrated solar radiation from a solar thermal field. The temperature stability of a solar reactor is directly influenced by the solar flux intercepted. This paper presents a low-order physical model to simulate the dynamic response of temperature inside a tubular plug-flow reactor prototype. Solid granular particles are fed to the reactor from the top whereas a counter-current flowing gas enters the reactor from the bottom. An in-house code was developed to model transient heat transfer of the reactor wall, gas, and moving particles. The model was preliminarily validated with packed beds for different temperature ranges and two gas flowrates. Dynamic response of the reactor temperature is simulated for different input power and gas/particle flowrates. The results show that the system response can be controlled efficiently by utilizing input power (solar flux) as a control parameter. A conventional proportional integral (PI) controller is designed to control the temperature inside the reactor and to maintain it during the solar flux intermittency. The controller parameters are tuned using the Ziegler–Nichols method to ensure optimal system response. The results show that the feedback control model is successful in tracking different reference reactor temperatures within a reasonable settling time of 30 min and eliminated overshoot. This study can be extended to include a hybrid reactor with a multi-input, multi-output variable system.

Energy & Fuels↗
DOE OSTI2026

Degradation Dynamics of Perovskite Solar Cells Under Fixed Reverse Current Injection

Previous studies of reverse-bias stability in perovskite solar cells have focused primarily on voltage controlled reverse-bias tests. Here we instead present an investigation of perovskite solar cell degradation under well-defined, constant reverse-current stress. We show that the choice of hole-transport layer dictates the dominant degradation pathway: cells using thick poly(triphenylamine) (PTAA) layers with better indium-doped tin oxide (ITO) coverage can tolerate high reverse bias but quickly undergo catastrophic breakdown under fixed reverse current near their one-sun maximum power-point. In contrast, cells modified with the phosphonic-acid interface layer MeO-2PACz, with poorer ITO coverage compared to PTAA, exhibit soft, gradual, and largely recoverable degradation, regardless of the shading conditions. For MeO-2PACz devices, degradation increases with both current magnitude and duration. Importantly, when normalized by injected charge (current times duration), lower currents applied over longer times cause more severe degradation than higher currents over shorter periods. Combining electrical measurements with spatially resolved photoluminescence imaging, we argue against shunt formation and instead support an ion- and charge-mediated interfacial electrochemical degradation mode.

Applied Physics (physics.app-ph)↗
DOE OSTI2025

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Consensus-Based Control and Optimization of Power System Inertia

The integration of distributed energy resources (DERs), such as solar, wind, and energy storage systems, into power grids through inverter-based resources reduces power system inertia, leading to faster frequency dynamics and potential grid instability. To address this challenge, this paper proposes a distributed, consensus-based approach for the real-time control and optimization of inertia sources (synchronous generators and/or DERs) during system disturbances, enhancing both system stability and economic performance. The distributed control and optimization approach assumes each inertia source exchanges information solely with its neighbor ones, making it easily scalable to large power grid networks. The impacts of the communication connectivity among the inertia sources as well as their generation capacity limits on the distributed approach are investigated. We also demonstrate the approach’s robustness in scenarios involving communication time delays and packet losses, validating its effectiveness through numerical simulations on a 4-bus test system and a two-area 8-bus test system.

Power system inertia↗
DOE OSTI2026

How Silica Surface Chemistry Modulates Interfacial Water: Insights from Machine Learning Molecular Dynamics

Controlling water structure and dynamics at silica interfaces are central to a wide range of technologies, including protective oxide layers for solar water splitting and nanoporous membranes. In this work, we develop a machine learning interatomic potential, trained via active learning, to achieve ab initio accuracy for water confined between hydroxylated silica surfaces over a range of silanol coverages and slit widths. We find that partially hydroxylated surfaces (50 and 75% OH) support stronger water−surface hydrogen bonding and more extended interfacial density profiles than fully hydroxylated (100% OH) surfaces, indicating that increasing OH coverage does not necessarily strengthen interfacial hydrogenbond networks. Translational diffusion decreases approximately linearly with slit width and OH coverage, whereas rotational dynamics respond nonlinearly. In particular, at the smallest slit width of 5 Å, 75% OH coverage produces an enhanced local tetrahedral ordered interfacial network that strongly suppresses reorientation, while 100% coverage yields a crowded, disordered interfacial layer that also hinders rotation. In contrast, the 50% OH coverage is sufficiently sparse that it does not markedly alter water structure or dynamics under confinement. These results show that coupled control of pore size and surface chemistry enables nonlinear tuning of interfacial water structure and transport, providing a design strategy for optimizing porous silica for either enhanced interfacial stability and controlled reactivity or rapid and selective transport.

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

Repurposing Inactive Oil and Gas Wells for Energy Storage: Maximizing the Potential Via Optimal Drivetrain Control: Preprint

In recent years, there has been a growing emphasis on utilizing energy storage to enhance grid resilience against disruptive events. While renewable energy supply continues to expand, gravity-based solutions like pumped hydro remain dominant in the commercial space. However, their geographical limitations constrain availability, scalability, and increase costs for co-locating solar and wind energy. An alternative approach proposes repurposing idle oil and gas wells located closer to existing grid infrastructure, offering a promising and cost-effective solution. This paper addresses the optimization and control of a regenerative drive system coupled to an interior permanent magnet synchronous machine in a 300-meter well with a 100-Newton weight. The study employs a dynamic MATLAB/Simulink model to simulate the operation of the electric drivetrain system during storage and discharge operations. The results demonstrate an initial round-trip efficiency of 85.9% for the electrical system alone and identify crucial factors for maximizing efficiency. The optimized operation and control of the electromechanical drivetrain system hold great potential for minimizing the levelized cost of storage while maximizing efficiency and revenue generation.

ENERGY STORAGE,ENGINEERING↗
DOE OSTI2026

Degradation Dynamics of Perovskite Solar Cells Under Fixed Reverse-Current Injection

Previous studies of reverse-bias stability in perovskite solar cells have focused primarily on voltage-controlled tests. Here we instead investigate perovskite solar cell degradation under well-defined, constant reverse-current stress. We show that the choice of hole-transport layer dictates the dominant degradation pathway: cells using thick poly(triphenylamine) (PTAA) layers can tolerate high reverse bias but quickly undergo catastrophic breakdown under fixed reverse current near their one-sun maximum power-point. In contrast, cells modified with phosphonic-acid interface layer MeO-2PACz, with poorer indium-doped tin oxide (ITO) coverage compared to PTAA, exhibit gradual and recoverable degradation under certain stress and recovery conditions. For MeO-2PACz devices, degradation increases with both current magnitude and duration. Importantly, when normalized by injected charge (current times duration), lower currents applied over longer times cause more degradation than higher currents over shorter periods. Here, combining electrical measurements with spatially resolved photoluminescence imaging, our observations support an ion- and charge-mediated interfacial electrochemical degradation mode.

Degradation↗
DOE OSTI2021

High-Efficiency, Low-Cost III-V Solar Cells by Dynamic Hydride Vapor Phase Epitaxy Coupled with Rapid, Polishing-Free Wafer Reuse through Orientation-Optimized (110) Spalling

We demonstrated (110) GaAs solar cells grown by D-HVPE with equivalent performance and material quality relative to (100) devices. Also, we developed a procedure for repeatable wafer-scale spalling of (110) GaAs. Spalled surfaces were free of the facets founds in (100) GaAs spalling, the large arrest lines found in (100) Ge spalling, and surface features greater than 3 µm in peak-to-valley height, which can otherwise degrade the efficiency of regrown III-V devices. A sub-µm step-terrace morphology was discovered on the post-spall wafer surface, resulting from the restricted cleavage system of GaAs, but we developed understanding of the factors that determine the resulting morphology, enabling ample opportunity for optimization of morphologies suitable for device growth and spall depth waste minimization on (110) GaAs. Lastly, we demonstrated a device grown on a previously spalled surface with only 8% relative efficiency difference to a cell grown on a new unspalled wafer. Significant optimization of the substrate regrowth conditions are required to enable higher efficiency, but these results highlight the promise of (110)-oriented devices coupled with substrate reuse by spalling as a pathway for low-cost III-V photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2023

Biomimetic Light Harvesting Complexes Based on Self-Assembled Dye-DNA Nanostructures (Final Technical Report)

A fundamental limitation in the development of artificial molecular light harvesting structures is that generally if one places pigment molecules close enough to achieve very high energy transfer efficiency and absorbance cross section, the dyes interact in such a way that self-quenching occurs. This limits both the optical cross section and the overall efficiency of light capture in such systems. Nature overcomes this problem and achieves efficient energy transfer without self-quenching by controlling the environment, vibration characteristics, orientation and dynamics of the pigments involved in light harvesting. Natural light harvesting systems have evolved highly intricate chromophore architectures of protein-bound organic molecules that absorb and funnel solar energy with high efficiency and fast transfer rates using elegant excitonic circuitries. Nature achieves this precise control over the properties of pigment complexes by using specific proteins as templates to guide the formation of very well-defined pigment aggregates, groups of pigment molecules that are in close enough contact to undergo excitonic interactions resulting in new electronic properties that were not present in the monomer. In synthetic systems, pigment aggregates are well known, and J-aggregates and H-aggregates have been long studied for their unique properties. In Nature, the chlorosomes of green bacteria form what appear to be classical J-aggregates and the light harvesting complexes of purple nonsulfur bacteria form ring structures that have many of the properties of J-aggregates such as a red-shifted absorbance spectrum and excited states that are delocalized over multiple pigment molecules. These photosynthetic systems leverage the spectral and enhanced transport properties of J-like aggregates to achieve fast exciton transport within the antenna and thus high light-harvesting efficiency. The close interaction of the pigments results in substantial electronic coupling that lifts the degeneracy of excitonic states and therefore modifies the absorption and emission spectra of the monomer. In the case of J-aggregation, lower energy excitonic states acquire significant oscillator strength, resulting in a characteristic bathochromic shift of the absorption and fluorescence and often superradiant delocalized exciton states.

77 NANOSCIENCE AND NANOTECHNOLOGY↗