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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High Throughput Computational Framework of Materials Properties for Extreme Environments

This project aims to establish a framework capable of efficiently predicting the properties of structural materials for service in harsh environments over a wide range of temperatures and over long periods of time. The approach is to develop and integrate high throughput first-principles calculations in combination with machine learning (ML) methods, perform high throughput CALPHAD (calculations of phase diagrams) modeling, and carry out finite element method (FEM) simulations. Relevant to high temperature service in fossil power system, nickel-based superalloys such as Inconel 740 and Haynes 282 as well as the associated (Ni-Cr-Co)-Al-C-Fe-Mn-Mo-Nb-Si-Ti system, were investigated. The present framework was built on the concept of phase-based property data, in which properties of individual phases are modeled as a function of internal and external independent variables. This project established an open-source infrastructure with the following capabilities: (1) High throughput implementation of first-principles calculations at finite temperatures and variable compositions using both accurate phonon calculations and the efficient Debye model for thermodynamic properties, elastic constants, diffusion coefficients, vacancy formation, stacking and twin faults, and dislocation mobility; i.e., using the developed code DFTTK; (2) Machine learning capabilities to predict the above properties so that the number of first-principles calculations can be significantly reduced; e.g., using the developed code SIPFENN; (3) High throughput CALPHAD modeling of the above properties as a function of temperature and composition using our unique capability based on ESPEI and PyCalphad; (4) New capabilities to predict the stress-strain behavior of individual phases; and (5) New models for tensile strength prediction in common FEM software with the crystal plasticity finite element simulations (CPFEM).

, Ni-based superalloys↗
DOE OSTI2024

Machine learning surrogates for surface complexation model of uranium sorption to oxides

Abstract The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Pinning dislocations in colloidal crystals with active particles that seek stacking faults

There is growing interest in functional, adaptive devices built from colloidal subunits of micron size or smaller. A colloidal material with dynamic mechanical properties could facilitate such microrobotic machines. Here we study via computer simulation how active interstitial particles in small quantities can be used to modify the bulk mechanical properties of a colloidal crystal. Passive interstitial particles are known to pin dislocations in metals, thereby increasing resistance to plastic deformation. We extend this tactic by employing anisotropic active interstitials that travel super-diffusively and bind strongly to stacking faults associated with partial dislocations. We find that: (1) interstitials that are effective at reducing plasticity compromise between strong binding to stacking faults and high mobility in the crystal bulk. (2) Reorientation of active interstitials in the crystal depends upon rotational transitions between high-symmetry crystal directions. (3) The addition of certain active interstitial shapes at concentrations as low as 60 per million host particles (0.006%) can create a shear threshold for dislocation migration. This work demonstrates how active materials in a dense matrix can locally sense their environment and lead to bulk property changes.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Computed versus measured ion velocity distribution functions in a Hall effect thruster

We compare time-averaged and time-varying measured and computed ion velocity distribution functions in a Hall effect thruster for typical operating conditions. The ion properties are measured by means of laser induced fluorescence spectroscopy. Simulations of the plasma properties are performed with a two-dimensional hybrid model. In the electron fluid description of the hybrid model, the anomalous transport responsible for the electron diffusion across the magnetic field barrier is deduced from the experimental profile of the time-averaged electric field. The use of a steady state anomalous mobility profile allows the hybrid model to capture some properties like the time-averaged ion mean velocity. Yet, the model fails at reproducing the time evolution of the ion velocity. This fact reveals a complex underlying physics that necessitates to account for the electron dynamics over a short time-scale. This study also shows the necessity for electron temperature measurements. Moreover, the strength of the self-magnetic field due to the rotating Hall current is found negligible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

A method of building of decision trees based on data from wearable device during a rehabilitation of patients with tibia fractures

Nowadays technologies which are used in traumatology are a combination of mechanical, electronic, calculating and programming tools. Relevance of development of mobile applications for an expeditious data processing which are received from medical devices (in particular, wearable devices), and formulation of management decisions increases. Using of a mathematical method of building of decision trees for an assessment of a patient’s health condition using data from a wearable device considers in this article.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Modeling Coverage Dependence in Surface Reaction Networks

In heterogeneous catalysis molecules adsorb on surfaces and react to form products which desorb. It has been known for a long time that the reactivity of a surface depends on coverage of intermediates, but there had been little work in quantitatively modeling this dependence or in understanding the nature of the coverage dependence. Our work aimed to develop methods for quantitatively modeling the coverage dependence of adsorption energies, and to determine the origin of the coverage dependence. We utilized density functional theory to compute the coverage dependent adsorption energies of many atomic adsorbates (H, C, N, O, and S) on the late transition metal (111) surfaces. We were able to show that the coverage dependence is due to an adsorbate-induced surface electronic structure modification mechanism of the metal atom d-orbitals. Furthermore, we showed the coverage dependence is similar for all of these adsorbates and metal surfaces, enabling the prediction of the coverage dependence of other adsorbates and metals. There are numerous ways that adsorbates can adsorb onto a surface; too many to attempt to compute every possible adsorbate configuration using density functional theory. To address this limitation we used the density functional theory results to construct a simpler model (a cluster expansion) that could be used to enumerate the configurations that could be described by a simple lattice of adsorption sites. The cluster expansion enabled us to show that the similarity in the coverage dependence exists across all coverages. Although the cluster expansion methodology can be extended in principle to multiple adsorbates, adsorption sites and alloys, in practice this is tedious and computationally expensive. As alternative this the cluster expansion approach, we developed a simple model that describes the coverage dependent mechanism that is extendable to alloy surfaces. This model allows large-scale screening studies to be performed, and was used in part of this work to identify sulfur-tolerant alloy catalysts. This grant provided full support one PhD student, Spencer Miller, who now works for Advanced Process Combinatorics, and partial support for another PhD student, Nilay Inoglu, who now works for Exxon Mobil. The work supported by this grant has been published in eight peer-reviewed publications and two book chapters which are listed in section 3. One of the publications (PRB 2010, 82, 045414) was selected as an important scientific contribution within the DOE BES Catalysis Science program for 2011. One final manuscript is nearly completed. This work was presented at four invited academic talks, including an international summer school, seven invited conference talks and 21 contributed talks and posters over the course of the grant.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2018

Gamma imaging and mapping advancements

The Savannah River National Lab (SRNL) in partnership with Los Alamos National Lab (LANL) developed an in-situ GrayQb™ radiation mapping device eliminating the need to remove the radiation sensitive phosphor storage plate (PSP) from the device for scanning between exposures. By incorporating a customized version of the LANL patented MiniMax camera-based PSP reader system into the GrayQb™ housing, the exposed PSP can now be read in-situ and digitally transmitted to a remote computer for viewing. The ability to generate radiation contour maps showing source locations and relative radiological levels present in an area has high utility for targeting clean-up efforts, maintaining worker ALARA, determining leak locations and radiological situational awareness. In-situ GrayQb™ reduces the number of required interactions with the device providing deployment cost savings, increasing personnel safety and removing human handling errors during the manual scan process. Additionally, by negating the need for an external scanner, the device becomes more mobile. Other upgrades to the device included identification of a more sensitive imaging medium and incorporation of a dual pinhole rendering the device physically capable of obtaining 3D images. Laboratory tests with Am-241 sources using a mockup of the in-situ GrayQ™, successfully demonstrated the ability to digitally capture radiation source information using the dual pinhole and camera-based PSP reader.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Report from the 2016 CrossConnects workshop: improving data mobility & management for bioinformatics

Due to significant declines in the price of genome sequencing technology, the bioinformatics sciences are experiencing a massive upswing in data generation resulting in an increasing need for data distribution and access. The sheer number of biological areas of study, many of which benefit from the scientific breakthroughs of one another, are adding to the increase of shared data usage. The need for effective data management, analysis, and access are becoming more critical. While there are commonalities facing both precision medicine and metagenomics, each area has its own unique challenges and needs. A workshop was held in April 2016 at Lawrence Berkeley National Laboratory that brought together scientists from both fields, along with experts in computing and networking. Presenters and attendees discussed current research and pressing data issues facing the bioinformatics field today and in the near future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Structure and Flow-Viscosity of Filled-Polymer-Based 3D Printing Ink: Exploration through Coarse-Grained Molecular Dynamics

The addition of nanofiller particles to a polymer matrix has long been known to enhance or modify the composite’s mechanical and rheological properties. However, quantitatively capturing such changes with molecular level simulations remains computationally challenging. Toward that goal, we performed coarse-grained molecular dynamics of a nanocomposite system at a fixed (25 vol %) filler loading under nonspecific, weak polymer–filler interactions representative of a broad class of technologically important materials. We report several interesting results, including: (1) the equilibrium chain-configuration remains Gaussian-like as in an unfilled melt; (2) smaller filler particles display a stronger tendency to cluster; (3) larger fillers act as plasticizers by reducing the entanglement density and accelerating the chain mobility; and (4) fillers enhance the tensile response modulus, with the effect being stronger for larger particles. We also simulate cluster breakup, yielding, and elongational flow under an applied time-linear tensile strain and study the flow viscosity as a function of filler-size and chain-length.

Materials science↗
DOE OSTI2022

The effect of residual palladium on the performance of organic electrochemical transistors

Organic electrochemical transistors are a promising technology for bioelectronic devices, with applications in neuromorphic computing and healthcare. The active component enabling an organic electrochemical transistor is the organic mixed ionic-electronic conductor whose optimization is critical for realizing high-performing devices. In this study, the influence of purity and molecular weight is examined for a p-type polythiophene and an n-type naphthalene diimide-based polymer in improving the performance and safety of organic electrochemical transistors. Our preparative GPC purification reduced the Pd content in the polymers and improved their organic electrochemical transistor mobility by ~60% and 80% for the p- and n-type materials, respectively. These findings demonstrate the paramount importance of removing residual Pd, which was concluded to be more critical than optimization of a polymer’s molecular weight, to improve organic electrochemical transistor performance and that there is readily available improvement in performance and stability of many of the reported organic mixed ionic-electronic conductors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Coarse-grained model of water diffusion and proton conductivity in hydrated polyelectrolyte membrane

Using dissipative particle dynamics (DPD), we simulate nanoscale segregation, water diffusion, and proton conductivity in hydrated sulfonated polystyrene (sPS). We employ a novel model [Lee et al. J. Chem. Theory Comput. 11(9), 4395-4403 (2015)] that incorporates protonation/deprotonation equilibria into DPD simulations. The polymer and water are modeled by coarse-grained beads interacting via short-range soft repulsion and smeared charge electrostatic potentials. The proton is introduced as a separate charged bead that forms dissociable Morse bonds with the base beads representing water and sulfonate anions. Morse bond formation and breakup artificially mimics the Grotthuss mechanism of proton hopping between the bases. The DPD model is parameterized by matching the proton mobility in bulk water, dissociation constant of benzenesulfonic acid, and liquid-liquid equilibrium of water-ethylbenzene solutions. The DPD simulations semi-quantitatively predict nanoscale segregation in the hydrated sPS into hydrophobic and hydrophilic subphases, water self-diffusion, and proton mobility. As the hydration level increases, the hydrophilic subphase exhibits a percolation transition from isolated water clusters to a 3D network. The analysis of hydrophilic subphase connectivity and water diffusion demonstrates the importance of the dynamic percolation effect of formation and breakup of temporary junctions between water clusters. The proposed DPD model qualitatively predicts the ratio of proton to water self-diffusion and its dependence on the hydration level that is in reasonable agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Electron transfer and atom exchange between aqueous Fe(II) and structural Fe(III) in clays. Role in U and Hg(II) transformations

During this project, we investigated Fe electron transfer and atom exchange between aqueous Fe(II) and structural Fe(III) in clay minerals. We used selective chemical extractions, enriched Fe isotope tracer experiments, computational molecular modeling, and Mössbauer spectroscopy. Our findings indicate that structural Fe(III) in clay minerals is reduced by aqueous Fe(II) and that electron transfer occurs when Fe(II) is sorbed to either basal planes and edge OH-groups of clay mineral. Findings from highly enriched isotope experiments suggest that up to 30 % of the Fe atoms in the structure of some clay minerals exhanges with aqueous Fe(II). First principles calculations using a small polaron hopping approach suggest surprisingly fast electron mobility at room temperature in a nontronite clay mineral and are consistent with temperature dependent Mössbauer data Fast electron mobility suggests that electrons may be able to conduct through the mineral fast enough to enable exchange of Fe between the aqueous phase and clay mineral structure. over the time periods we observed. Our findings suggest that Fe in clay minerals is not as stable as previously thought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Study of Microbial Environmental Processes Related to the Natural Attenuation of Uranium at the Rifle Site using Systems-level Biology

Microbes exist in communities in the environment where they are fundamental drivers of global carbon, nutrient and metal cycles. In subsurface environments, they possess significant metabolic potential to affect these global cycles including the transformation of radionuclides. This study examined the influence of microbial communities in sediment zones undergoing biogeochemical cycling of carbon, nutrients and metals including natural attenuation of uranium. This study examined the relationship of both the microbiota (taxonomy) and their metabolic capacity (function) in driving carbon, nutrient and metal cycles including uranium reduction at the Department of Energy (DOE) Rifle Integrated Field Research Challenge (RIFRC). Objectives of this project were: 1) to apply systems-level biology through application of ‘metaomics’ approaches (collective analyses of whole microbial community DNA, RNA and protein) to the study of microbial environmental processes and their relationship to C, N and metals including the influence of microbial communities on uranium contaminant mobility in subsurface settings undergoing natural attenuation, 2) improve methodologies for data generation using metaomics (collectively metagenomics, metatranscriptomics and proteomics) technologies and analysis and interpretation of that data and 3) use the data generated from these studies towards microbial community-scale metabolic modeling. The strategy for examining these subsurface microbial communities was to generate sequence reads from microbial community DNA (metagenomics or whole genome shotgun sequencing (WGS)) and RNA (metatranscriptomcs or RNAseq) and protein information using proteomics. Results were analyzed independently and through computational modeling. Overall, the community model generated information on the microbial community structure that was observed using metaomic approaches at RIFRC sites and thus provides an important framework for continued community modeling development. The model as created is capable of predicting the response of the community structure in changing environments such as anoxic/oxic conditions or limitations by carbon or nutrients. The ability to more accurately model these responses is critical to understanding carbon and energy flows in an ecosystem is critical towards improving our ability to make predictions that can be used to design more efficient remediation and management strategies, and better understand the implications of environmental perturbations on these ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Prototyping and Development of Commercial Nanocrystalline and Thin Film Silicon for Photovoltaic Manufacturing

The College of Nanoscale Science and Engineering (CNSE) at the University at Albany received funding from the Department of Energy for its proposal Prototyping and Development of Commercial Nanocrystalline and Thin Film Si for Photovoltaic Manufacturing. This project was created to identify growth rate, texture uniformity, process window, economics, composition and thickness uniformity solutions related to fabricating large area, high efficiency thin film silicon based solar cells. This document serves as a final report for the closure of this program and details the deliverables from CNSE against its original scope of work. Thin-film silicon solar cells are a promising candidate for electricity generation applications because of a combination of advantages. Nanocrystalline and poly-Si based thin films, reduces the use of expensive semiconductor material content, can be deposited onto a foreign substrate (e.g. glass or flexible stainless steel) and enables use of the cells in wide variety of applications. In addition, nano and poly-Si films have higher carrier mobility as well as reduce recombination effects, relative to traditional amorphous-silicon films. They can be mass-produced at low cost, and expected to have a strong position in the international photovoltaic industry, which is experiencing a compounded annual growth of 25%. The objectives included: Demonstration of high rate VHF (Very High Frequency) growth of nc-Si over large areas with uniform thickness. Demonstration of single chamber device growth that allows mass production processing. Demonstration of uniform segmented electrodes. Development of computer models to accelerate efforts. Demonstration of large grain thin film polycrystalline silicon films fabrication. Utilizing the AIC (Aluminum Induced Crystallization) process for large grain silicon film fabrication. Demonstration of 12% efficient nanocrystalline and polycrystalline thin film devices. The end result expected was the production of high-efficiency, low-cost thin film Si devices with reduced cost per watt, allowing dramatically increased market penetration. While further research is required to meet these ultimate goals, this project proved its feasibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Atomic Layer Deposition (ALD) to Extend Catalyst Lifetime for Biobased Adipic Acid Production

Robust heterogeneous catalysts are essential for enabling biomass conversion; however, harsh reaction environments introduce durability challenges for many conventional catalyst materials [1]. The hydrogenation of biobased muconic acid to adipic acid is one such emerging chemistry that faces PGM catalyst stability challenges [2]. Muconic acid is a heavily-investigated biobased platform chemical that can be converted into an array of large-market commodity chemicals [2]. PGM catalysts are exceptionally effective for muconic acid hydrogenation to adipic acid, with Pd the most active to date. [2] However, Pd leaches in an acidic environment and this chemistry has a high propensity for fouling. Atomic layer deposition (ALD) is one such material design strategy that has emerged to stabilize supported metal catalysts [3]. ALD coatings are theorized to stabilize supported metal active sites by i) covering high-energy facets most susceptible to degradation, ii) disrupting the physical mobility of active sites, and iii) reinforcing the structure of the underlying catalyst support [3]. However, ALD coatings for catalyst durability with carboxylic acids remains an underdeveloped area of research and literature reports have yet to consider the techno-economic tradeoffs between the ALD manufacturing cost and catalyst lifetime productivity. This study examines low-cycle Al2O3 ALD coatings to stabilize Pd/TiO2 against deactivation during muconic acid hydrogenation. The unique harshness of muconic acid for Pd leaching was evaluated by both experiment and computation. Based on batch reactor screening results, uncoated and ALD coated catalysts were evaluated in a continuous flow reactor for their productivity, stability, and post-reaction regenerability at 700 degrees C. Characterization was performed to assess the impact of ALD coatings on catalyst morphology, as well as following regeneration. Finally, techno-economic analysis models evaluated the value proposition for ALD-coated catalysts within an nth-generation adipic acid biorefinery.

09 BIOMASS FUELS↗
DOE OSTI2026

A Mobile Hot Cell for Conditioning Disused Sealed Radioactive Sources for Storage or Transportation

An innovative Mobile Hot Cell (MHC) has been developed for conditioning Disused Sealed Radioactive Sources (DSRS) category 1 and 2 for storage or transportation. The MHC is designed to provide both Radiological and Biological containment with a maximum capacity of 1000 Ci Co60 or 5000Ci Cs137 source and can be transported via standard cargo containers. This project has been supported through the National Nuclear Safety Administration (NNSA) Offsite Source Recovery Program (OSRP). The project is intended for the international community rather than domestic although domestic use is a possibility. Many countries have significant stockpiles of these devices that are often stored in less-than-optimal circumstances. This necessitates that these devices be addressed expeditiously, and the sources secured. The MHC utilizes robotics, automation, and other non-traditional methods for disassembling, characterizing, and packaging these sources that have reached end of life or are otherwise not needed. These innovative approaches are necessary to facilitate an expedited timeline to efficiently and safely secure these sources in a non-proliferation effort. Conditioning efforts include disassembling the device such as a teletherapy head used for cancer treatment, or blood/research irradiators such that the radioactive sources may be removed safely. The sources are then characterized. Leak checks are performed, dimensions are verified, and serial numbers are confirmed. Upon completion, the sources are typically placed into a Standard Forms Capsule which is seal welded closed. It is leak tested and placed into a Long-Term Storage Shield (LTSS) which can either be secured for storage directly or loaded into an appropriate cask for transportation. Further innovations include multiple deployment scenarios that include a full deployment of MHC components, deployment of the MHC automation internal components to an existing hot cell, deployment of minimally required MHC components and incorporation of sand for shielding, and integration of the MHC for Silo Storage, or Bore Hole Storage efforts. The MHC has evolved from a very specific use case to a “Swiss Army Knife” type of a tool in that it can be readily adapted to a large variety of situations. Innovative approaches such as the use of robotics, Computer Numeric Control (CNC) machining centers, automated welding equipment, HDMI Cameras, and LED lighting are some of the developed technologies incorporated into the MHC design. Shielding is accomplished with a steel walled Base Box which is surrounded by four nesting doll shield shells which when combined limits the external dose rate to 5mr/hr when a 1000 Ci Co60 source is exposed inside.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Acceleration of the Particle Swarm Optimization for Peierls–Nabarro modeling of dislocations in conventional and high-entropy alloys

Dislocations are among the most important defects in determining the mechanical properties of both conventional alloys and high-entropy alloys. The Peierls-Nabarro model supplies an efficient pathway to their geometries and mobility. The difficulty in solving the integro-differential Peierls-Nabarro equation is how to effectively avoid the local minima in the energy landscape of a dislocation core. Among the other methods to optimize the dislocation core structures, we choose the algorithm of Particle Swarm Optimization, an algorithm that simulates the social behaviors of organisms. By employing more particles (bigger swarm) and more iterative steps (allowing them to explore for longer time), the local minima can be effectively avoided. But this would require more computational cost. The advantage of this algorithm is that it is readily parallelized in modern high computing architecture. We demonstrate the performance of our parallelized algorithm scales linearly with the number of employed cores.

36 MATERIALS SCIENCE↗
DOE OSTI2021

First-Principles Study on the Electronic Properties of PDPP-Based Conjugated Polymer via Density Functional Theory

In this study, we focus on computational predictions of the electronic and optical properties of a one-dimensional periodic model of a single chain of a diketopyrrolopyrrole (DPP)-based conjugated polymer (PDPP3T) as a function of electronic configuration changes due to charge injection. Here, we employ density functional theory (DFT) to explore the ground-state and excited-state electronic properties as well as optical properties influenced by charge injection. We utilize both the Heyd–Scuseria–Ernzerhof (HSE06) and Perdew–Burke–Ernzerhof (PBE) functionals to predict the band gap and compute the absorption spectrum. Our DFT results point out that utilizing the HSE06 functional in conjunction with momentum sampling over the Brillouin zone can appropriately predict the band gap and absorption spectrum in good agreement with experimental data. Moreover, we explore the influence of charge-carrier injection on the electronic configuration of the PDPP3T polymer. Our results indicate that the injection of charge carriers into the PDPP3T semiconducting polymer model greatly affects the electrical properties and ends in a low band gap and high mobility of charge carriers in PDPP3T polymers, offering the potential to tailor the material electronic performance for organic photovoltaic and optoelectronic device applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗