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Bioimaging Science Program: 2022 Principal Investigator Meetings Proceedings

The mission of the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program’s Bioimaging Science Program (BSP) is to understand the translation of genomic information into the mechanisms that power living cells, communities of cells, and whole organisms. The goal of BSP is to develop new imaging and measurement technologies to visualize the spatial and temporal relationships of key metabolic processes governing phenotypic expression in plants and microbes. The extended goal of dynamic imaging is to functionally connect cellular components and interdependent organisms. Information about the time and place of chemical reactions in situ can identify causal relationships between biological activators and downstream effectors. BSP held its annual PI meeting virtually February 28–March 1. Contributing investigators are convened to review progress and current state-of-the-art bioimaging research. Holding the 2022 BSP meeting as part of the broader Genomic Science Program (GSP) PI meeting allowed researchers to interact with the extended GSP community. This convergence provided a platform for networking and exchange of ideas with experts in other technologies and in target BSP application areas, helping to forge new multidisciplinary collaborations among investigators from the sister programmatic areas within BER’s Biological Systems Science Division. An important highlight of the BSP meeting was the keynote presentation by Nobel Laureate Dr. Joachim Frank on Time-Resolved Macromolecular Imaging using Cryo-EM. He discussed microfluidic mixing and fast freezing to capture nonequilibrium intermediate states during molecular binding and conformational changes. The action of molecular machines can be captured at nanometer resolution and millisecond discrimination. BSP PIs made presentations describing their research focus and progress in plenary sessions on bioimaging science and on quantum-enabled bioimaging science research projects. BSP research at universities and DOE laboratories is presented in this report. A final discussion of the BSP was organized by meeting plenary session chairs, who prepared the following Executive Summary of current BSP research, research challenges, future opportunities, and potential ideas for expanding the BSP’s impact and interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Multivariate statistics applications in scanning transmission electron microscopy X-ray spectrum imaging

A modern scanning transmission electron microscope (STEM) fitted with an energy dispersive X-ray spectroscopy (EDS) system can quickly and easily produce spectrum image (SI) datasets containing so much information (hundreds to thousands of megabytes) that they cannot be comprehensively interrogated by a human analyst. Therefore, advanced mathematical techniques are needed to glean materials science and engineering insight into the processing-structure-properties relationship of the examined material from the SI data. This review will discuss recent advances in the application of multivariate statistical analysis (MVSA) methods to STEM-EDS SI experiments. In particular, the fundamental mathematics of principal component analysis (PCA) and related methods are reviewed, and advanced methods such as multivariate curve resolution (MCR) are discussed. The applications of PCA and MCR-based techniques to solve difficult materials science problems, such as the analysis of a particle fully embedded in a matrix phase are discussed, as well as confounding effects such as rank deficiency that can confuse the results of MVSA computations. Possible future advances and areas in need of study are also mentioned.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Source of Bright Near-Infrared Luminescence in Gold Nanoclusters

Gold nanoclusters with near-infrared (NIR) photoluminescence (PL) have great potential as sensing and imaging materials in biomedical and bioimaging applications. In this work, Au 21 (S-Adm) 15 and Au 38 S 2 (S-Adm) 20 are used to unravel the underlying mechanisms for the improved quantum yields (QY), large Stokes shifts and long PL lifetimes in gold nanoclusters. Both nanoclusters show decent PL QY. In particular, the Au 38 S 2 (S-Adm) 20 nanocluster shows a bright NIR PL at 900 nm with QY up to 15% in normal solvents (such as toluene) at ambient conditions. The relatively lower QY for Au 21 (S-Adm) 15 (4%) compared to Au 38 S 2 (S-Adm) 20 is attributed to the lowest-lying excited state being symmetry-disallowed, as evidenced by the pressure-dependent anti-spectral shift of the absorption spectra compared to PL. Yet, Au 21 (S-Adm) 15 maintains some emissive properties due to a nearby symmetry-allowed excited state. Furthermore, our results show that suppression of non-radiative decay due to the surface “lock rings” which encircle the Au kernel and the surface “lock atoms” which bridge the fundamental Au-kernel units (e.g., tetrahedra, icosahedra, etc.) is the key to obtain high QYs in gold nanoclusters. Here, the complicated excited-state processes and the small absorption coefficient of the band-edge transition lead to the large Stokes shifts and the long PL lifetimes that are widely observed in gold nanoclusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Subdiffraction instrumentation development and application to the elucidation of biological systems, thin films, and organic photovoltaic devices

Fluorescence and Raman instrumentation was developed to elucidate morphology, information on local environment, and material properties of target systems. Far-field fluorescence and luminescence spectroscopic measurements were performed using a pulsed super-continuum laser source and detector with high temporal resolution. With this arrangement morphologies of structures were coupled with time-correlated data. Polymeric beads and Alexa Fluor 594-phalloidin labeled cellular actin structures of cultured cells were imaged below the diffraction limit using stimulated emission depletion to resolve structures to ≈40nm. Lifetime imaging revealed a 2.0 ± 0.1 ns lifetime for fluorescently-labeled beads in confocal and depletion imaging modes. Depletion imaging was also able to display a change of 2.2 to 2.9 ns for different regions of the cellular actin network of cultured cells with a possible difference in lifetime caused by tryptophan quenching of the dye. Subdiffraction imaging with a resolution of ≈40 nm was also accomplished using luminescence depletion of photostable giant CdSe/14CdS nanocrystal quantum dots in air. Nanocrystal quantum dots, typically not prone to depletion, exhibited this phenomenon when excited with an energy of 50 pJ and 2 nJ of depletion energy. Luminescence depletion required half the energy compared to stimulated emission depletion to achieve the same resolution limit. The luminescence was depleted by as much as ≈92% with no observable photobleaching. Raman measurements of polymer films were performed with 532-nm laser illumination using scanning angle and conventional 180° backscattering modes to determine chemical information. The scanning angle mode achieved an angle resolution of 0.09° and was used to probe a thin layer of polystyrene as well as a diblock copolymer of polystyrene and poly(3-hexylthiophene-2,5-diyl). Enhancements to the Raman signals at selected angles lower than the critical angle for total internal reflection, characteristic of waveguides, were measured. An additional enhancement in the Raman signal results from resonant conditions for the diblock copolymer. The epi-collection geometry was used to gain spectroscopic information regarding to the stability of heterojunction solar cells with the aid of resonance Raman spectroscopy. Raman spectral characteristics corresponding to thiophene-based functional groups were used to relate stability of the polymers under different processing conditions such as solvent and thermal annealing while undergoing laser induced photodegradation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental observation of chiral phonons in monolayer WSe2

Copyright © 2019 SPIE. Chirality characterizes an object that is not identical to its mirror image. In condensed matter physics, Fermions have been demonstrated to obtain chirality through structural and time-reversal symmetry breaking. These systems display unconventional electronic transport phenomena such as the quantum Hall effect and Weyl semimetals. However, for bosonic collective excitations in atomic lattices, chirality was only theoretically predicted and has never been observed. We experimentally show that phonons can exhibit intrinsic chirality in monolayer tungsten diselenide, whose lattice breaks the inversion symmetry and enables inequivalent electronic K and -K valley states. The time-reversal symmetry is also broken when we selectively excite the valley polarized holes by circularly polarized light. Brillouin-zone-boundary phonons are then optically created by the indirect infrared absorption through the hole-phonon interactions. The unidirectional intervalley transfer of holes ensures that only the phonon modes in one valley are excited. We found that such photons are chiral through the transient infrared circular dichroism, which proves the valley phonons responsible to the indirect absorption has non-zero pseudo-angular momentum. From the spectrum we further deduce the energy transferred to the phonons that agrees with both the first principle calculation and the double-resonance Raman spectroscopy. The chiral phonons have significant implications for electron-phonon coupling in solids, lattice-driven topological states, and energy efficient information processing.

Zhu, Hanyu↗

Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science

FIVE TRANSFORMATIVE OPPORTUNITIES FOR DISCOVERY SCIENCE As a result of this effort, it has become clear that the progress made to date on the five Grand Challenges has created a springboard for seizing five new Transformative Opportunities that have the potential to further transform key technologies involving matter and energy. These five new Transformative Opportunities and the evidence supporting them are discussed in this new report, “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science.” Mastering Hierarchical Architectures and Beyond-Equilibrium Matter Complex materials and chemical processes transmute matter and energy, for example from CO2 and water to chemical fuel in photosynthesis, from visible light to electricity in solar cells and from electricity to light in light emitting diodes (LEDs) Such functionality requires complex assemblies of heterogeneous materials in hierarchical architectures that display time-dependent away-from-equilibrium behaviors. Much of the foundation of our understanding of such transformations however, is based on monolithic single- phase materials operating at or near thermodynamic equilibrium. The emergent functionalities enabling next-generation disruptive energy technologies require mastering the design, synthesis, and control of complex hierarchical materials employing dynamic far-from-equilibrium behavior. A key guide in this pursuit is nature, for biological systems prove the power of hierarchical assembly and far- from-equilibrium behavior. The challenges here are many: a description of the functionality of hierarchical assemblies in terms of their constituent parts, a blueprint of atomic and molecular positions for each constituent part, and a synthesis strategy for (a) placing the atoms and molecules in the proper positions for the component parts and (b) arranging the component parts into the required hierarchical structure. Targeted functionality will open the door to significant advances in the harvesting, transforming (e.g., reducing CO2, splitting water, and fixing nitrogen), storing, and use of energy to create new materials, manufacturing processes, and technologies—the lifeblood of human societies and economic growth. Beyond Ideal Materials and Systems: Understanding the Critical Roles of Heterogeneity, Interfaces, and Disorder Real materials, both natural ones and those we engineer, are usually a complex mixture of compositional and structural heterogeneities, interfaces, and disorder across all spatial and temporal scales. It is the fluctuations and disorderly states of these heterogeneities and interfaces that often determine the system’s properties and functionality. Much of our fundamental scientific knowledge is based on “ideal” systems, meaning materials that are observed in “frozen” states or represented by spatially or temporally averaged states. Too often, this approach has yielded overly simplistic models that hide important nuances and do not capture the complex behaviors of materials under realistic conditions. These behaviors drive vital chemical transformations such as catalysis, which initiates most industrial manufacturing processes, and friction and corrosion, the parasitic effects of which cost the U.S. economy billions of dollars annually. Expanding our scientific knowledge from the relative simplicity of ideal, perfectly ordered, or structurally averaged materials to the true complexity of real-world heterogeneities, interfaces, and disorder should enable us to realize enormous benefits in the materials and chemical sciences, which translates to the energy sciences, including solar and nuclear power, hydraulic fracturing, power conversion, airframes, and batteries. Harnessing Coherence in Light and Matter Quantum coherence in light and matter is a measure of the extent to which a wave field vibrates in unison with itself at neighboring points in space and time. Although this phenomenon is expressed at the atomic and electronic scales, it can dominate the macroscopic properties of materials and chemical reactions such as superconductivity and efficient photosynthesis. In recent years, enormous progress has been made in recognizing, manipulating, and exploiting quantum coherence. This progress has already elucidated the role that symmetry plays in protecting coherence in key materials, taught us how to use light to manipulate atoms and molecules, and provided us with increasingly sophisticated techniques for controlling and probing the charges and spins of quantum coherent systems. With the arrival of new sources of coherent light and electron beams, thanks in large part to investments by the U.S. Department of Energy’s Office of Basic Energy Sciences (BES), there is now an opportunity to engineer coherence in heterostructures that incorporate multiple types of materials and to control complex, multistep chemical transformations. This approach will pave the way for quantum information processing and next-generation photovoltaic cells and sensors. Revolutionary Advances in Models, Mathematics, Algorithms, Data, and Computing Science today is benefiting from a convergence of theoretical, mathematical, computational, and experimental capabilities that put us on the brink of greatly accelerating our ability to predict, synthesize, and control new materials and chemical processes, and to understand the complexities of matter across a range of scales. Imagine being able to chart a path through a vast sea of possible new materials to find a select few with desired properties. Instead of the time-honored forward approach, in which materials with desired properties are found through either trial-and-error experiments or lucky accidents, we have the opportunity to inversely design and create new materials that possess the properties we desire. The traditional approach has allowed us to make only a tiny fraction of all the materials that are theoretically possible. The inverse design approach, through the harmonious convergence of theoretical, mathematical, computational, and experimental capabilities, could usher in a virtual cornucopia of new materials with functionalities far beyond what nature can provide. Similarly, enhanced mathematical and computational capabilities significantly enhance our ability to extract physical and chemical insights from vastly larger data streams gathered during multimodal and multidimensional experiments using advanced characterization facilities. Exploiting Transformative Advances in Imaging Capabilities across Multiple Scales Historically, improvements in imaging capabilities have always resulted in improved understanding of scientific phenomena. A prime challenge today is finding ways to reconstruct raw data, obtained by probing and mapping matter across multiple scales, into analyzable images. BES investments in new and improved imaging facilities, most notably synchrotron x-ray sources, free-electron lasers, electron microscopes, and neutron sources, have greatly advanced our powers of observation, as have substantial improvements in laboratory- scale technologies. Furthermore, BES is now planning or actively discussing exciting new capabilities. Taken together, these advances in imaging capabilities provide an opportunity to expand our ability to observe and study matter from the 3D spatial perspectives of today to true “4D” spatially and temporally resolved maps of dynamics that allow quantitative predictions of time-dependent material properties and chemical processes. The knowledge gained will impact data storage, catalyst design, drug delivery, structural materials, and medical implants, to name just a few key technologies. ENABLING SUCCESS Seizing each of these five Transformative Opportunities, as well as accelerating further progress on Grand Challenge research, will require specific, targeted investments from BES in the areas of synthesis, meaning the ability to make the materials and architectures that are envisioned; instrumentation and tools, a category that includes theory and computation; and human capital, the most important asset for advancing the Grand Challenges and Transformative Opportunities. While “Challenges at the Frontiers of Matter and Energy: Transformative Opportunities for Discovery Science” could be viewed as a sequel to the original Grand Challenges report, it breaks much new ground in its assessment of the scientific landscape today versus the scientific landscape just a few years ago. In the original Grand Challenges report, it was noted that if the five Grand Challenges were met, our ability to direct matter and energy would be measured only by the limits of human imagination. This new report shows that, prodded by those challenges, the scientific community is positioned today to seize new opportunities whose impacts promise to be transformative for science and society, as well as dramatically accelerate progress in the pursuit of the original Grand Challenges.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical prediction of fiber orientation in injection-molded short-fiber/thermoplastic composite parts with experimental validation

Numerical prediction of the fiber orientation in the short-glass fiber (GF) reinforced polyamide 6 (PA6) composites with the fiber weight concentration of 30%, 50%, and 70% manufactured by the injection molding process is presented. And the fiber orientation was also directly observed and measured through X-ray computed tomography. During the injection molding process of the short-fiber/thermoplastic composite, the fiber orientation is produced by the flow states and the fiber-fiber interaction. Folgar and Tucker equation is the well known for modeling the fiber orientation in a concentrated suspension. They included into Jeffrey’s equation a diffusive type of term by introducing a phenomenological coefficient to account for the fiber-fiber interaction. Our developed model for the fiber-fiber interaction was proposed by modifying the rotary diffusion term of the Folgar-Tucker equation. This model was presented in a conference paper of the 29{sup th} International Conference of the Polymer Processing Society published by AIP conference proceeding. For modeling fiber interaction, the fiber dynamic simulation was introduced in order to obtain a global fiber interaction coefficient, which is sum function of the fiber concentration, aspect ratio, and angular velocity. The fiber orientation is predicted by using the proposed fiber interaction model incorporated into a computer aided engineering simulation package C-Mold. An experimental program has been carried out in which the fiber orientation distribution has been measured in 100 x 100 x 2 mm injection-molded plate and 100 x 80 x 2 mm injection-molded weld by analyzed with a high resolution 3D X-ray computed tomography system XVA-160α, and calculated by X-ray computed tomography imaging. The numerical prediction shows a good agreement with experimental validation. And the complex fiber orientation in the injection-molded weld was investigated.

42 ENGINEERING↗

3D nanolithography with metalens arrays and spatially adaptive illumination

The growing demand for advanced materials, miniaturized devices and integrated microsystems calls for the reliable fabrication of complex, multiscale, three-dimensional (3D) architectures, a need increasingly addressed through light-based and laser-based processes. However, owing to the field-of-view (FOV) limitations of conventional imaging optics, existing 3D laser nanofabrication techniques face fundamental challenges in throughput, proximity error and stitching defects on the path to scaling. Here, in this study, we present a scalable 3D nanofabrication platform that uses a metalens-generated focal spot array to parallelize two-photon lithography (TPL) beyond centimetre-scale write field areas. Metalenses are ideally suited for producing submicron-scale focal spots for high-throughput nanolithography, as they uniquely feature large numerical apertures (NAs), immersion media compatibility and large-scale manufacturability. We experimentally demonstrate a printing system that uses a 12-cm 2 metalens array to produce more than 120,000 cooperative focal spots, corresponding to a throughput exceeding 10 8 voxels s −1 . By programmatically patterning the focal spot array using a spatial light modulator (SLM), an adaptive parallel printing strategy is developed for precise greyscale linewidth modulation and choreographed printing of semiperiodic and fully aperiodic 3D geometries. We demonstrate parallel printing of replicated microstructures (>50 M microparticles per day), centimetre-scale 3D architectures with feature sizes down to 113 nm, and photonic and mechanical metamaterials. This work demonstrates the potential of 3D nanolithography towards wafer-scale production, showing how TPL could be used at scale for applications in microelectronics, biomedicine, quantum technology and high-energy laser targets.

Materials science↗

Time-stretch microscopy based on time-wavelength sequence reconstruction from wideband incoherent source

Time-stretch microscopy has emerged as an ultrafast optical imaging concept offering the unprecedented combination of the imaging speed and sensitivity. However, dedicated wideband and coherence optical pulse source with high shot-to-shot stability has been mandated for time-wavelength mapping—the enabling process for ultrahigh speed wavelength-encoded image retrieval. From the practical point of view, exploiting methods to relax the stringent requirements (e.g., temporal stability and coherence) for the source of time-stretch microscopy is thus of great value. In this paper, we demonstrated time-stretch microscopy by reconstructing the time-wavelength mapping sequence from a wideband incoherent source. Utilizing the time-lens focusing mechanism mediated by a narrow-band pulse source, this approach allows generation of a wideband incoherent source, with the spectral efficiency enhanced by a factor of 18. As a proof-of-principle demonstration, time-stretch imaging with the scan rate as high as MHz and diffraction-limited resolution is achieved based on the wideband incoherent source. We note that the concept of time-wavelength sequence reconstruction from wideband incoherent source can also be generalized to any high-speed optical real-time measurements, where wavelength is acted as the information carrier.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Pathways to Carbon Liberation: A Systems Approach to Understanding Carbon Transformations and Losses from Thawing Permafrost

Our objective in this project was to discover how microbial communities mediate the fate of carbon in thawing permafrost under climate change. We proposed a systems approach integrating (a) molecular microbial and viral ecology, (b) molecular organic chemistry and stable and radiocarbon isotopes, and (c) state-of-the-art modeling, along a chronosequence of permafrost thaw in subarctic Sweden. The fate of carbon (C) in thawing permafrost is an outstanding challenge of modern biogeochemistry and climate change. Permafrost C pools are large (~1700 PgC), and C dynamics of thawing permafrost complex: old C decomposes as it is liberated from thawing permafrost as CO 2 or CH 4 , with a significant fraction cycling through lake sediments, even as new C accumulates due to thaw-initiated ecological succession. Our work is allowing better prediction of the net effect of these processes. Microbes mediate C dynamics in thawing permafrost, but a mechanistic understanding of how to scale microbial population dynamics, genomic potential, and expression to ecosystem-scale processes has been missing. A key question was: What is the interplay of microbial communities and organic matter chemical structure in the decomposition/preservation of organic C across a thaw gradient? And intriguingly, what (if any) is the role of phage (viruses that infect prokaryotic cells) in mediating these processes? Viruses appear to play a large role in driving oceanic function, but these phenomena are virtually unstudied in terrestrial systems. This endeavor linking microbial and viral dynamics, organic geochemistry and trace gas production will improve models of C cycling in permafrost systems, and clarify the fate of C under future climates. Technical Approach – We conducted a study at Stordalen Mire, Sweden, along a permafrost thaw chronosequence encompassing permafrost palsas and their initial collapse stage, thawing bog sites (dominated by Sphagnum moss), fully-thawed and inundated fen sites (dominated by Eriophorum spp or Carex spp.), and lakes. Our project used cutting edge technologies in both biogeochemistry and molecular microbial ecology to advance systems biology research on microbial carbon cycling through: (a) systems-level mapping of chemical states and ages of organic matter (via FT-ICR-MS and 14 C analysis) along thaw gradients to associated microbial communities, biochemical potentials, and activities (via meta-genomics, -transcriptomics, –proteomics, and viral genomics), and to CO 2 and CH 4 fluxes; (b) experimental incubations using Quantum Dot Probing, to test key hypotheses, arising from (a), about particular microbially-driven biochemical degradation pathways; (c) bioinformatics designed to simultaneously enhance the DOE Knowledgebase, and (d) integrated ecosystem C-cycle modeling testable by soil organic chemical and microbial data. Results from this project spanned 4 categories: (i) integrative across disciplines, and disciplinarily-focused in (ii) microbiology, (iii) biogeochemistry, and (iv) modeling. In integrated understanding of the system, we answered the questions posed above, mapping resident microbes to carbon transformations to reveal a carbon-processing shift with permafrost thaw, and discovering abundant, diverse and habitat-specific viruses that appear to be impacting carbon cycling, while also relating microbial communities to modeled processes. In microbiology-specific papers, we dug into viromes, microbial community networks, and informatic methods, while also introducing a new permafrost-associated phylum and its ecogenomic context. Relevance to DOE FOA - With a focus on discovering how microbial communities mediate the fate of old and new carbon in permafrost systems with climate change, our work directly responds to the call for “–omics driven basic research on the contribution of... microbial communities to C cycling processes in terrestrial ecosystems.” We bridge all three of the focal areas of the call, including (i) “Systems biology studies”, and development of –omics approaches (ii) “to investigate microbial community functional processes”, and (iii) “for imaging and analysis of microbially-mediated carbon cycling.”

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatiotemporal multipartite entanglement

In this Rapid Communication, we propose, following the spirit of quantum imaging, to generalize the theory of multipartite entanglement for the continuous-variable Gaussian states by considering, instead of the global covariance matrix, the local correlation matrix at two different spatiotemporal points ({rho}-vector,t) and ({rho}-vector{sup '},t{sup '}), with {rho}-vector being the transverse coordinate. Our approach makes it possible to introduce the characteristic spatial length and the characteristic time of the multipartite entanglement, which in general depend on the number of 'parties' in the system. As an example, we consider tripartite entanglement in spontaneous parametric down-conversion with a spatially structured pump. We investigate spatiotemporal properties of such entanglement and calculate its characteristic spatial length and time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Ultrafast isomerization in acetylene dication after carbon K-shell ionization

Ultrafast proton migration and isomerization are key processes for acetylene and its ions. However, the mechanism for ultrafast isomerization of acetylene [HCCH]2+ to vinylidene [H2CC]2+ dication remains nebulous. Theoretical studies show a large potential barrier ( > 2 eV) for isomerization on low-lying dicationic states, implying picosecond or longer isomerization timescales. However, a recent experiment at a femtosecond X-ray free-electron laser suggests sub-100 fs isomerization. Here we address this contradiction with a complete theoretical study of the dynamics of acetylene dication produced by Auger decay after X-ray photoionization of the carbon atom K shell. We find no sub-100 fs isomerization, while reproducing the salient features of the time-resolved Coulomb imaging experiment. This work resolves the seeming contradiction between experiment and theory and also calls for careful interpretation of structural information from the widely applied Coulomb momentum imaging method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ultrafast Imaging of Carrier Transport across Grain Boundaries in Hybrid Perovskite Thin Films

For optoelectronic devices based on polycrystalline semiconducting thin films, carrier transport across grain boundaries is an important process in defining efficiency. Here we employ transient absorption microscopy (TAM) to directly measure carrier transport within and across the boundaries in hybrid organic-inorganic perovskite thin films for solar cell applications with 50 nm spatial precision and 300 fs temporal resolution. By selectively imaging sub-bandgap states, our results show that lateral carrier transport is slowed down by these states at the grain boundaries. However, the long carrier lifetimes allow for efficient transport across the grain boundaries. The carrier diffusion constant is reduced by about a factor of 2 for micron-sized grain samples by the grain boundaries. For grain sizes on the order of ~200 nm, carrier transport over multiple grains has been observed within a time window of 5 ns. These observations explain both the shortened photoluminescence lifetimes at the boundaries as well as the seemingly benign nature of the grain boundaries in carrier generation.

14 SOLAR ENERGY↗

Spatially resolved photoluminescence brightening in individual single-walled carbon nanotubes

Single-molecule microscopy was used to image photoluminescence (PL) brightening of individual sodium-dodecyl-sulfate (SDS)-wrapped single-walled carbon nanotubes (SWCNTs) upon the addition of dithiothreitol (DTT). PL enhancement varied for each nanotube (NT), with some brightening by 16% and others by a factor of about 7. Interestingly, NTs that displayed lower initial QY values showed the largest increases in PL enhancement. SDS-SWCNTs longer than the diffraction limit were studied in order to spatially resolve the brightening phenomenon. Quite unexpectedly, a uniform, single-step PL brightening along the NT was consistently observed, suggesting that the PL enhancement is the result of a non-localized process. Furthermore, the even PL brightening seen over SWCNTs that are micrometers long implies that single point defect sites, which are known to be largely responsible for exciton nonradiative decay, play no significant role in the brightening process. Interestingly, affixing the SWCNT strongly to the substrate surface mitigated the PL brightening response, consistent with a hypothesis that surfactant reorganization upon the addition of DTT is responsible for exciton PL brightening.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Contribution of 3-D time-lapse ERT to the study of leachate recirculation in a landfill

Leachate recirculation is a key process in the operation of municipal waste landfills as bioreactors. It aims at increasing the moisture content to optimise the biodegradation. Because waste is a very heterogeneous and anisotropic porous media, the geometry of the leachate plume recirculation is difficult to delineate from the surface at the scale of the bioreactor site. In this study, 3-D time-lapse electrical resistivity tomography (ERT) was used to obtain useful information for understanding leachate recirculation hydrodynamics. The ERT inversion methodology and the electrode arrays were optimised using numerical modelling simulating a 3-D leachate injection scenario. Time-lapse ERT was subsequently applied at the field scale during an experimental injection. We compared ERT images with injected volumes to evaluate the sensitivity of time-lapse ERT to delineate the plume migration. The results show that time-lapse ERT can accomplish the following: (i) accurately locate the injection plume, delineating its depth and lateral extension; (ii) be used to estimate some hydraulic properties of waste.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Concept to diagnose mix with imaging x-ray Thomson scattering

Turbulent mixing of two fluid species is a ubiquitous problem, prevalent in systems such as inertial confinement fusion (ICF) capsule implosions, supernova remnants, and other astrophysical systems. In complex, high Reynolds number compressible high energy density (HED) flows such as these, hydrodynamic instabilities initiate the turbulent mixing process, which can then feedback and alter the mean hydrodynamic motion through nonlinear processes. In order to predict how these systems evolve under turbulent conditions, models are used. However, these models require detailed quantitative data to validate and constrain their detailed physics models as well as improve them. Providing this much needed data is currently at the forefront of HED research but is proving elusive due to a lack of available diagnostics capable of directly measuring detailed flow variables. Thomson scattering is a promising technique in this regard as it provides fundamental conditions of the flow ({rho}, T, Zbar) due to its direct interaction with the small scales of the fluid or plasma and was recently considered as a possible mix diagnostic. With the development of imaging x-ray Thomson scattering (IXRTS) obtaining spatial profiles of these variables is within reach. We propose a novel use of the IXRTS technique that will provide more detailed quantitative data required for model validation in mix experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Universality of Poisson-driven plasma fluctuations in the Alcator C-Mod scrape-off layer

Large-amplitude, intermittent fluctuations are ubiquitous in the boundary region of magnetically confined plasmas and lead to detrimental plasma-wall interactions in next-generation, high duty cycle fusion power experiments. Using gas puff imaging data time series from the scrape-off layer in the Alcator C-Mod device, it is demonstrated in this work that the large-amplitude fluctuations can be described as a super-position of pulses with a fixed shape and a constant duration. By applying a new deconvolution algorithm on the data time series with a two-sided exponential pulse function, the arrival times and amplitudes of the pulses can be estimated, and the measurement time series can be reconstructed with high accuracy. The pulse amplitudes are shown to follow an exponential distribution. The waiting times between pulses are uncorrelated, their distribution has an exponential tail, and the number of arrivals is a linear function of time. This demonstrates that pulse arrivals follow a homogeneous Poisson process. Identical statistical properties apply to both ohmic and high confinement mode plasmas, clearly demonstrating the universality of the fluctuation statistics in the boundary region of Alcator C-Mod.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Physics-Constrained Deep Learning Model for Simulating Multiphase Flow in 3D Heterogeneous Porous Media

Physics-based simulators for multiphase flow in porous media emulate nonlinear processes with coupled physics, and usually require extensive computational resources for software development, maintenance and simulation execution. As a result, a huge demand exists for fast modeling of coupled processes in a wide range of subsurface applications including geological sequestration, hydrocarbon recovery and geothermal energy extraction. In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3-Dimensional (3D) heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural networks, specifically U-Net with successive contracting and expansive steps, and is coupled with an efficient continuity-based smoother to predict flow responses that need spatial continuity. Furthermore, the transient regions are penalized to steer the training process such that the model can accurately capture flow in these regions. The model takes inputs including properties of porous media, fluid properties and well controls, and predicts the temporal-spatial evolution of the state variables (pressure and saturation). While maintaining the continuity of fluid flow, the 3D spatial domain is decomposed into 2D images for reducing training cost, and the decomposition results in an increased number of training data samples and better training efficiency. Additionally, a surrogate model is separately constructed as a postprocessor to calculate well flow rate based on the predictions of state variables from the deep learning model. We use the example of CO 2 injection into saline aquifers, and apply the physics-constrained deep learning model that is trained from physics-based simulation data and emulates the physics process. The model performs prediction with a speedup of ~ 1400 times compared to physics-based simulations, and the average temporal errors of predicted pressure and saturation plumes are 0.27% and 0.099% respectively. Furthermore, water production rate is efficiently predicted by a surrogate model for well flow rate, with a mean error less than 5%. Therefore, with its unique scheme to cope with the fidelity in fluid flow in porous media, the physics-constrained deep learning model can become an efficient predictive model for computationally demanding inverse problems or other coupled processes.

58 GEOSCIENCES↗