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At least 577 records · Page 32

Designing ITER motional Stark effect line shift (MSE-LS) spectrometers

As a part of ITER beam aided diagnostics, the design of Motional Stark Effect (MSE) diagnostic observing the emission from the Balmer-α line is underway. The physics of Stark splitting shows that the Stark manifold is polarization dependent, and the energy splitting results in a line shift proportional to the electric field. Due to the challenges of maintaining the calibration of the plasma facing mirrors in ITER, the conventional MSE polarimetry measurement technique is replaced with a spectral approach that is deemed more favorable in the ITER environment. The MSE line shift (LS) diagnostic is designed to quantify the Lorentz electric field magnitude by measuring the Stark manifold using visible spectroscopy. In the presence of large magnetic fields and high energy heating beams of 1 MeV, the expected Stark splitting is much larger than in typical devices. The MSE-LS design has unique challenges requiring careful consideration and modeling of its viewing geometry and photon budget. The MSE-LS approach on ITER is promising but has stringent demands on the allowable errors for the statistical and systematic fitting uncertainties. In this study, a full system model and numerical simulations of data for each sightline are completed. For a range of optical transmission fractions, photon noise analysis is conducted to determine the statistical uncertainties. This provides guidance on the spectrometer throughput, dispersion at the detector, optics, and other design choices. A conceptual design of a high throughput spectrometer with a volume phase transmission grating is presented.

Instruments & Instrumentation↗

Radar Super Resolution using a Deep Convolutional Neural Network

Super-resolution involves synthetically increasing the resolution of gridded data beyond its native resolution. Typically, this is done using interpolation schemes, which estimate sub-grid scale values from neighboring data, and perform the same operation everywhere regardless of the large-scale context, or by requiring a network of radars with overlapping fields of view. Recently, significant progress has been made in single image super resolution using convolutional neural networks. Conceptually, a neural network may be able to learn relations between large scale precipitation features and the associated sub-pixel scale variability and outperform interpolation schemes. Here, we use a deep convolutional neural network to artificially enhance the resolution of NEXRAD PPI scans. The model is trained on 6-months of reflectivity observations from the Langley Hill WA (KLGX) radar, and we find that it substantially outperforms common interpolation schemes for x4 and x8 resolution increases based on several objective error and perceptual quality metrics.

radar, machine learning, super resolution, Remote ↗

Identification of Performance Shaping Factor Lag and Linger Effects for Dynamic Human Reliability Analysis: Application of Experimental Data

Many researchers have emphasized the importance of dynamic probabilistic safety assessment (PSA), which highlights the necessity of studies for dynamic human reliability analysis (HRA). Dynamic HRA concentrates on a dynamic account of human actions or how performance shaping factors (PSFs) can dynamically modify the human error probability (HEP) over time. In contrast, existing static HRA does not consider human actions as changes over time or event progressions. Accordingly, previous research on dynamic HRA conceptually suggested PSF lag and linger effects to treat dependence between operator actions in dynamic HRA versus existing approaches. As follow-up research, this study attempted to identify PSF lag and linger effects for dynamic HRA on the basis of experimental data. Firstly, mathematical models for PSF lag and linger effects were developed based on a literature survey in the field of biology. Secondly, we analyzed experimental scenarios from a control room study to identify operator actions considered in PSA. Lastly, based on the experimental data, the effect of the stress PSF with lag and linger effects was compared to that without PSF lag and linger effects. This paper concludes with an overall discussion of PSF lag and linger effects based on the relation between the stress PSF and error occurrence.

99 GENERAL AND MISCELLANEOUS↗

Produced Water-Economic, Socio, Environmental Simulation Model (PW-ESEim) Model: Proof-of-Concept for Southeastern New Mexico

A proof-of-concept tool, the Produced Water-Economic, Socio, Environmental Simulation model (PW-ESESim), was developed to support ease of analysis. The tool was designed to facilitate head-to-head comparison of alternative produced water source, treatment, and reuse water management strategies. A graphical user interface (GUI) guides the user through the selection and design of alternative produced water treatment and reuse strategies and the associated health and safety risk and economic benefits. At the highest conceptual level, alternative water strategies include the selection of a source water (locally or regionally available produced water), treatment strategy (pre-treatment, physical, chemical, biological, desalination, and post-treatment processes) and product water purpose (e.g., irrigation, industrial processing, environmental). After selection of these details, the PW-ESESim output a number of key economic, societal, environmental, public/ecological health and safety metrics to support user decision-making; specific examples include, cost of treatment, improvements in freshwater availability, human and ecologic health impacts and growth in local jobs and the economy. Through the simulation of different produced water treatment and management strategies, tradeoffs are identified and used to inform fit-for-purpose produced water treatment and reuse management decisions. While the tool was initially designed using Southeastern New Mexico (Permian Basin) as a case study, the general design of the PW-ESESim model can be extended to support other oil and gas regions of the U.S.

54 ENVIRONMENTAL SCIENCES↗

Business Models for Scaling Demand Flexibility Volume IV – Program life cycle challenges and lessons learned from U.S. programs

Load growth at the grid edge is driving increased attention to the distribution system and its ability to enable customer technology adoption in an affordable and timely manner. Key industry stakeholders, including electric utilities and regulators, can benefit from strategies to manage and balance customer needs with infrastructure investments, such as demand flexibility. This report focuses on demand flexibility—the ability to reduce, shift, shed, generate, or modulate loads in response to building and grid needs—to reduce the need for costly grid upgrades by deferring investment needs and increase system reliability by shifting electricity usage during periods of high risk. Specifically, we focus on the emerging characteristics of business models for demand flexibility as a framework to understand how demand flexibility programs generate value. In this report, we focus on the life cycle of demand flexibility programs, which provides information on value creation and describes the various deployment phases program implementers navigate from initial program conceptualization through to program expansion and replication to new customer segments and regions. This report characterizes the key phases of the demand flexibility program life cycle, identifies existing challenges across the program deployment phases, and describes lessons learned. This report is part of a series that includes reports on customer relationship management strategies, stakeholder ecosystem management, and program life cycle.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Estimating the Importance of Viral Contributions to Soil Carbon Dynamics

ABSTRACT Biogeochemical models for predicting carbon dynamics increasingly include microbial processes, reflecting the importance of microorganisms in regulating the movement of carbon between soils and the atmosphere. Soil viruses can redirect carbon among various chemical pools, indicating a need for quantification and development soil carbon models that explicitly represent viral dynamics. In this opinion, we derive a global estimate of carbon potentially released from microbial biomass by viral infections in soils and synthesize a quantitative soil carbon budget from existing literature that explicitly includes viral impacts. We then adapt known mechanisms by which viruses influence carbon cycles in marine ecosystems into a soil‐explicit framework. Finally, we explore the diversity of virus–host interactions during infection and conceptualize how infection mode may impact soil carbon fate. Our synthesis highlights key knowledge gaps hindering the incorporation of viruses into soil carbon cycling research and generates specific hypotheses to test in the pursuit of better quantifying microbial dynamics that explain ecosystem‐scale carbon fluxes. The importance of identifying critical drivers behind soil carbon dynamics, including these elusive but likely pervasive viral mechanisms of carbon redistribution, becomes more pressing with climate change.

59 BASIC BIOLOGICAL SCIENCES↗

Distributed Load Shedding Application Architecture and Bi-Level Predictive Estimator Algorithm

Increasing penetrations of distributed renewables are decreasing the effectiveness of traditional decentralized under-frequency load shedding (UFLS) schemes. As more distribution circuits begin to back-feed the transmission system, operation of traditional UFLS may exacerbate frequency instability. This paper presents the conceptual framework for a data-rich environment to coordinate UFLS across multiple distribution providers based on the laminar coordination framework in order to ensure optimal adaptive setting of UFLS relays. Communication and control are enabled through a distributed implementation of the IEC 61968-1 Common Information Model message bus structure. In addition to the proposed architecture, a novel adaptive UFLS scheme informed by a bi-level state estimator to create optimal relay setpoints is introduced. Initial simulation results are presented for the IEEE 14-bus test system on scenarios leading to mis-operation of traditional UFLS.

Anderson, Alexander A.↗

Primary System Thermal Fluids Analysis Model Development for the Compact High Temperature Gas Reactor (HC-HTGR) (Final Report)

Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is collaborating on the thermal hydraulic design and analysis of HC-HTGR reactor pressure vessel internals to ensure the reactor maintains sufficient safety margins during normal operation, shutdown, and accident conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Methane Adsorption on Heteroatom-Modified Maquettes of Porous Carbon Surfaces

Experimental and theoretical studies disagree on the energetics of methane adsorption on carbon materials. However, this information is critical for the rational design and optimization of the structure and composition of adsorbents for natural gas storage. The delicate nature of dispersion interactions, polarization of both the adsorbent and the adsorbate, interplay between H-bonding and tetrel bonding, and induced dipole/Coulomb interactions inherent to methane physisorption require computational treatment at the highest possible level of theory. In this study, we employed the smallest reasonable computational model, a maquette of porous carbon surfaces with a central site for substitution and methane binding. The most accurate predictions of methane adsorption energetics were achieved by electron-correlated molecular orbital theory CCSD(T) and hybrid density functional theory MN15 calculations employing a saturated, all-electron basis set. Here, the characteristic geometry of methane adsorption on a carbon surface (“lander approach”) arises due to bonding interactions of the adsorbent π-system with the proximal H–C bonds of methane, in addition to tetrel bonding between the antibonding orbital of the distal C–H bond and the central atom of the maquette (C, B, or N). The polarization of the electron density, structural deformations, and the comprehensive energetic analysis clearly indicate a ∼3 kJ mol –1 preference for methane binding on the N-substituted maquette. The B-substituted maquette showed a comparable or lower binding energy than the unsubstituted, pure C model, depending on the level of theory employed. The calculated thermodynamic results indicate a strategy for incorporating electron-enriched substitutions (e.g., N) into carbon materials as a way to increase methane storage capacity over electron-deficient (e.g., B) modifications. The thermochemical analysis was revised for establishing a conceptual agreement between the experimental isosteric heat of adsorption and the binding enthalpies from statistical thermodynamics principles.

03 NATURAL GAS↗

Controlling superconductivity of CeIrIn 5 microstructures by substrate selection

Superconductor/metal interfaces are usually fabricated in heterostructures that join these dissimilar materials. A conceptually different approach has recently exploited the strain sensitivity of heavy-fermion superconductors, selectively transforming regions of the crystal into the metallic state by strain gradients. The strain is generated by differential thermal contraction between the sample and the substrate. Here, we present an improved finite-element model that reliably predicts the superconducting transition temperature in CeIrIn 5 even in complex structures. Different substrates are employed to tailor the strain field into the desired shapes. Using this approach, both highly complex and strained as well as strain-free microstructures are fabricated to validate the model. This enables a high degree of control over the microscopic strain fields and forms the basis for more advanced structuring of superconductors as in Josephson junctions yet also finds natural use cases in any material class in which a modulation of the physical properties on a chip is desirable.

36 MATERIALS SCIENCE↗

Payload concepts for investigations of electrostatic dust motion on the lunar surface

Significant experimental and computational investigations have explored the feasibility of electrostatically-motivated dust motion on the lunar surface. The motion of lunar dust influences our understanding of the evolution of the surface and may also present a hazard to future exploration vehicles and astronauts. The possibility of a sustained exploration presence on the lunar surface opens the door to long-term experiments on the lunar surface, akin to the science facilities on the International Space Station. We have identified four measurements/observations that would significantly advance our understanding of dust-plasma interactions on the lunar surface. In this context, we provide conceptual designs for payloads to obtain these observations: a Langmuir probe, dust deposit witness plate, regolith charge measurement instrument, and cameras to look for evidence of horizon glow. These payloads could deploy independently and sequentially, or together as a suite. The proposed payloads would provide key observations that would inform future modeling efforts and direct future in situ experiments to understand the dust-plasma environment, both for planetary science and spacecraft design applications.

42 ENGINEERING↗

Design and Modeling of a Demonstration-scale ORC Cycle for the Liquid Air Combined Cycle

Energy storage is becoming an increasing focus for the future energy markets. One potential hybrid system for ling duration energy storage is the Liquid Air Combined Cycle (LACC). The LACC utilizes excess renewable energy to liquefy and store air during the charge cycle. During its discharge cycle, the system uses the exhaust heat from a conventional combustion turbine and an ORC bottoming cycle to vaporize and superheat the stored air that has been pressurized, which is subsequently expanded to atmosphere through a turbine. During the development of the cycle, it has been identified that the main technologies to advance the cycle are the ORC bottoming cycle machinery and the coupled operation between the liquified air subsystem and the ORC subsystem. This paper presents modeling and simulation of the LACC that involves ORC conditions that fall outside the operating regime of more common applications. Due to the low temperatures of liquified air, the ORC system operates on the order of -70°C for the pump, and the turbine has a pressure ratio around 40. The conceptual design of a demonstration system has been developed that focuses on these challenges in order to advance the overall system.

Pryor, Owen↗

Report on the Integration of Experimental and Modeling Data for Initial Equivalence Study of Microstructural Evolution in Irradiated LPBF 316SS

Advanced materials and manufacturing technologies are poised to improve the safety and design characteristics of nuclear technologies and meet US energy, environmental, and economic needs. In particular, metal additive manufacturing (AM) provides an opportunity to produce novel materials and component geometries, but their use is not without hurdles arising from the inherent microstructure variability that can result from the layer-by-layer build approach. Given the greater possible microstructure variability in AM materials—and the dearth of materials test reactors—it is impractical to rely solely on neutron irradiation studies to produce data for materials qualification for every possibility. This work within the Advanced Materials and Manufacturing Technologies (AMMT) Environmental Effects technical area contributes to the rapid qualification framework by developing a science-driven framework for the accelerated qualification of materials for nuclear environments. A key product of the Environmental Effects technical area of the AMMT program is the Licensing Approach with Ions and Neutrons (LAIN). This approach recognizes that whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. In FY 2023, the AMMT program presented a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame informed by the state of the art in materials science and a review of the current regulatory landscape. The objective of this section of the Environmental Effects technical area is to critically evaluate and refine the proposed qualification framework presented under AMMT by integrating the research results of the neutron irradiations, the ion irradiations, and modeling efforts. These ongoing efforts span across Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL) and are closely coordinated.

36 MATERIALS SCIENCE↗

Data-Driven Exploration of Climate Attractor Manifolds For Long-Term Predictability

Focal Area: This white paper responds to Focal Area 3. We seek to gain insight into decadal-scale climate predictability by applying novel manifold-finding probabilistic AI techniques to the complex data produced by Earth System models (ESMs) such as E3SM. The associated portfolio of research activities leverages DOE’s asset mix of HPC platforms, climate expertise, climate simulation codes, and AI expertise. Science Challenge: Climate and climate models are dynamical systems exhibiting properties that are interpretable through chaos theory. The theory contains an important concept that is relevant to multi-decade-scale climate prediction: a chaotic attractor. While the space containing all the possible states of the Earth’s atmosphere and ocean, the possible weather, is large, the realized states tend to stay near the smaller-dimensioned attractor. This behavior is responsible for the “order behind the irregularity” [1] of climate phenomena. Climate change can be thought of as a change in the properties of the attractor, and predicting the climate over years to decades is equivalent to predicting how those properties will change. To date, the attractor has been a useful conceptual tool, but has not been amenable to direct characterization. A new development is the advent of efficient high-dimensional manifold-finding probabilistic AI techniques, which permit a data-driven characterization of the ESM attractor and its probability distribution over weather states. Such a characterization would result in a natural dimensional reduction — a “non-linear Principal Components Analysis (PCA) adapted to climate simulation data” — leading to important advances in scenario-based long-term climate prediction, long-term prediction of water cycle extremes, ESM verification, inter-model comparison, and process model development.

54 ENVIRONMENTAL SCIENCES↗

An Analytic Formula for Entraining CAPE in Midlatitude Storm Environments

Abstract This article introduces an analytic formula for entraining convective available potential energy (ECAPE) with an entrainment rate that is determined directly from an environmental sounding, rather than prescribed by the formula user. Entrainment is connected to the background environment using an eddy diffusivity approximation for lateral mixing, updraft geometry assumptions, and mass continuity. These approximations result in a direct correspondence between the storm-relative flow and the updraft radius and an inverse scaling between the updraft radius squared and entrainment rate. The aforementioned concepts, combined with the assumption of adiabatic conservation of moist static energy, yield an explicit analytic equation for ECAPE that depends entirely on state variables in an atmospheric profile and a few constant parameters with values that are established in past literature. Using a simplified Bernoulli-like equation, the ECAPE formula is modified to account for updraft enhancement via kinetic energy extracted from the cloud’s background environment. CAPE and ECAPE can be viewed as predictors of the maximum vertical velocity w max in an updraft. Hence, these formulas are evaluated using w max from past numerical modeling studies. Both of the new formulas improve predictions of w max substantially over commonly used diagnostic parameters, including undiluted CAPE and ECAPE with a constant prescribed entrainment rate. The formula that incorporates environmental kinetic energy contribution to the updraft correctly predicts instances of exceedance of by w max , and provides a conceptual explanation for why such exceedance is rare among past simulations. These formulas are potentially useful in nowcasting and forecasting thunderstorms and as thunderstorm proxies in climate change studies. Significance Statement Substantial mixing occurs between the upward-moving air currents in thunderstorms (updrafts) and the surrounding comparatively dry environmental air, through a process called entrainment. Entrainment controls thunderstorm intensity via its diluting effect on the buoyancy of air within updrafts. A challenge to representing entrainment in forecasting and predictions of the intensity of updrafts in future climates is to determine how much entrainment will occur in a given thunderstorm environment without a computationally expensive high-resolution simulation. To address this gap, this article derives a new formula that computes entrainment from the properties of a single environmental profile. This formula is shown to predict updraft vertical velocity more accurately than past diagnostics, and can be used in forecasting and climate prediction to improve predictions of thunderstorm behavior and impacts.

54 ENVIRONMENTAL SCIENCES↗

A Strategic Condition Framework for Energy Innovation

Building upon previous work in innovation, technology, and economic fields, we propose a conceptual framework to address the interplay dynamics of public policy and the value chains of clean energy technology innovation systems, by focusing on market structural and strategic conditions in relation to the rate and direction of knowledge diffusion within activity-based value chains. Our framework extends beyond socio-technical transition models by considering such nuances as: 1) the implications of geography, 2) the locus of knowledge types, 3) the dynamics of financial and knowledge flow, and 4) emphasizing the importance of both market structure and institutional conditions. At the firm level, we consider dynamics of interactions between suppliers and customers, innovation activities, the competitive environment, and the firm’s broader strategic relationship to governance activities and structures; we allow for the fact that each of these aspects of a firm’s identity may have a strategically relevant geographic dimension (e.g., service territories, locational concentration of input resources, etc.). We provide a proof-of-concept application of the U.S. utility-scale solar photovoltaic (PV) and onshore wind sectors, including their interactions with the U.S. power market, which we in present in a web-based information platform (Energy I-SPARK, ei-spark.lbl.gov).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Performance assessment of long-legged tightly-baffled divertor geometries in the ARC reactor concept

Extremely intense power exhaust channels are projected for tokamak-based fusion power reactors; a means to handle them remains to be demonstrated. Advanced divertor configurations have been proposed as potential solutions. Recent modelling of tightly baffled, long-legged divertor geometries for the divertor test tokamak concept, ADX, has shown that these concepts may access passively stable, fully detached regimes over a broad range of parameters. The question remains as to how such divertors may perform in a reactor setting. To explore this, numerical simulations are performed with UEDGE for the long-legged divertor geometry proposed for the ARC pilot plant conceptual design - a device with projected heat flux power width (λq||) of 0.4 mm and power exhaust of 93 MW - first for a simplified Super-X divertor configuration (SXD) and then for the actual X-point target divertor (XPTD) being proposed. It is found that the SXD, combined with 0.5% fixed-fraction neon impurity concentration, can produce passively stable, detached divertor regimes for power exhausts in the range of 80-108 MW - fully accommodating ARC's power exhaust. The XPTD configuration is found to reduce the strike-point temperature by a factor of ~10 compared to the SXD for small separations (~1.4λq||) between main and divertor X-point magnetic flux surfaces. Even greater potential reductions are identified for reducing separations to ~1λq|| or less. The power handling response is found to be insensitive to the level of cross-field convective or diffusive transport assumed in the divertor leg. By raising the separatrix density by a factor of 1.5, stable fully detached divertor solutions are obtained that fully accommodate the ARC exhaust power without impurity seeding. To our knowledge, this is the first time an impurity-free divertor power handling scenario has been obtained in edge modelling for a tokamak fusion power reactor with λq|| of 0.4 mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerating Biomimetic Solar - Energy Harvesting: Mapping the Interaction Landscape of Plasmonic-Excitonic Hybrid Nanosystems (Final Report)

In general, excitonic and plasmonic nanoscale materials in close proximity show high potential for significant breakthroughs in energy related materials research. The interactions between these two kinds of materials result in coupled optical transitions (plexcitons), distinct from those of both the individual exciton and plasmon as well as from those of the sum of their constituents (synergistic effects). By linking together materials-research and physical-research approaches, this project contributes to a concerted approach on nanomaterials energy research. The project’s overall goal is to accelerate the development of well-defined plexcitonic model systems consisting of carefully engineered plasmonic and excitonic nanomaterial— essential for both gaining a fundamental understanding of plexcitonic nanomaterials and the development of novel design principles for biomimetic solar energy harvesting. During the 3-year project period and the terminal renewal with limited support for a 12-month period, we successfully synthesized and characterized (1) a robust excitonic nanomaterial and (2) a library of plasmonic nanoparticles as well as developed (3) a microfluidic platform for homogenous nanosynthesis as summarized below: (1) Robust Excitonic Nanomaterial. Supramolecular assemblies are Nature’s most successful material system for solar energy harvesting. However, photovoltaic devices based on artificial supramolecular assemblies continue to be stymied by disappointing efficiencies and poor stability. The conceptual failure may lie in current solar cell architectures, which rely on solidifying supramolecular assemblies as an ensemble into a solid matrix, neglecting the intrinsic fragility of the assemblies’ internal structure, thus disrupting or even destroying their delicate optoelectronic properties, that is, delicate Frenkel excitonic properties. Supramolecular assemblies may finally serve as usable light harvesting material systems for solar energy conversion technologies, only if they meet the following criteria: (a) Stability, that is, the fragile structure including its delicate Frenkel excitonic character needs to be stable, (b) Robustness, that is, resistant against elevated and fluctuating temperatures, and (c) Viability for device integration, that is, capable of being immobilized onto solid substrates. Here, by developing a nanocomposite via a tunable, cage-like scaffold design, we successfully provided stable supramolecular nanocomposites, that inhabit robust Frenkel excitons despite harming environmental conditions such as extreme heat stress. (2) Library of Plasmonic Nanoparticles. Naturally, current models describing plasmonic hybrid quantum states—plasmonic hybridizations—parallel those developed for molecular orbitals, equating individual plasmonic nanostructures with “atoms” and the plasmonic nanoassemblies with “molecules.” In analogy to organic synthesis, a suitably robust fabrication method would allow for “atom-like” manipulation of “molecule-like” plasmonic nanoassemblies; of high value for next-generation energy nanotechnologies. Despite this frequent comparison, current plasmonic nanoassembly fabrication methods favor top-down templating over wet-chemical synthesis, however, achieving precise control over nanostructure’s geometry and surface characteristics remain an art and a scientific challenge. The conceptual failure may lie in the current wet-chemical synthesis paradigm, as it relies on the accessibility of a multi-dimensional synthesis parameter space through limited, rather one-dimensional synthesis procedures by employing step-by-step approaches. Solution-based nanoarchitectonics for rational design of precisely built plasmonic nanoassemblies via solution-based fabrication may finally be possible only if multi-dimensional syntheses approaches are available that allow for comprehensive control over the plasmonic nanomaterials’ (a) Structural Properties and (b) Surface Properties. Here, by developing an innovative multidimensional 1,3-propanediol based polyol synthesis, we successfully provided control over the plasmonic building-block’s geometry (size and shape) together with its surface characteristics. Our results present a critical step toward the vision of a “periodic table-like” system for plasmonic materials based on straightforward wet-chemical syntheses for energy nanotechnologies. Developing deliberate modifications on this synthesis, we generated a library of plasmonic nanostructures covering the vast parameter space—opening the door for fundamental investigation of plexcitonic model systems. (3) Microfluidic Platform for Homogenous Nanosynthesis. Control over structural properties of plexcitonic nanocomposites remains a challenge due to current limitations in nanosynthesis techniques. Slight variations in nanostructure’s geometry impact their optoelectronic properties, demanding precise synthesis beyond the capabilities of solution-based (batch) synthesis processes. In contrast, the small, confined liquid volumes used in microfluidics—a reaction technique where the manipulation of fluids takes place in channels with dimensions of tens of micrometers—allows for homogenous synthesis conditions, providing excellent control of the reaction and, as a result, of the materials’ geopmetry and composition. However, thus far, the majority of plexcitonic systems has been developed via batch synthesis. Here, by successfully developing a two-channel microreactor, our microfluidic-supported synthesis approach combines the advantages of both microfluidics and batch platforms, allowing for precise spatio-temporal control over all synthesis parameters opening the possibility for homogenous nanosythnesis of well-defined plexcitonic model systems.

14 SOLAR ENERGY↗