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DOE OSTI2022

Non-Kasha fluorescence of pyrene emerges from a dynamic equilibrium between excited states

Pyrene fluorescence after a high-energy electronic excitation exhibits a prominent band shoulder not present after excitation at low energies. The standard assignment of this shoulder as a non-Kasha emission from the second-excited state (S 2 ) has been recently questioned. To elucidate this issue, we simulated the fluorescence of pyrene using two different theoretical approaches based on vertical convolution and nonadiabatic dynamics with nuclear ensembles. To conduct the necessary nonadiabatic dynamics simulations with high-lying electronic states and deal with fluorescence timescales of about 100 ns of this large molecule, we developed new computational protocols. The results from both approaches confirm that the band shoulder is, in fact, due to S 2 emission. We show that the non-Kasha behavior is a dynamic-equilibrium effect not caused by a metastable S 2 minimum. However, it requires considerable vibrational energy, which can only be achieved in collisionless regimes after transitions into highly excited states. This strict condition explains why the S 2 emission was not observed in some experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Classical vs. quantum plasmon-induced molecular transformations at metallic nanojunctions

Chemical transformations near plasmonic metals have attracted increasing attention in the past few years. Specifically, reactions occurring within plasmonic nanojunctions that can be detected via surface and tip-enhanced Raman (SER and TER) scattering were the focus of numerous reports. In this context, even though the transition between localized and nonlocal (quantum) plasmons at nanojunctions is documented, its implications on plasmonic chemistry remain poorly understood. We explore the latter through AFM-TER-current measurements. We use two molecules: i) 4-mercaptobenzonitrile (MBN) that reports on the (non)local fields and ii) 4-nitrothiophenol (NTP) that features defined signatures of its neutral/anionic forms and dimer product, 4,4′-dimercaptoazobenzene (DMAB). The transition from classical to quantum plasmons is established through our optical measurements: It is marked by molecular charging and optical rectification. Simultaneously recorded force and current measurements support our assignments. In the case of NTP, we observe the parent and DMAB product beneath the probe in the classical regime. Further reducing the gap leads to the collapse of DMAB to form NTP anions. The process is reversible: Anions subsequently recombine into DMAB. Our results have significant implications for AFM-based TER measurements and their analysis, beyond the scope of this work. In effect, when precise control over the junction is not possible (e.g., in SER and ambient TER), both classical and quantum plasmons need to be considered in the analysis of plasmonic reactions

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

HBMax: Optimizing Memory Efficiency for Parallel Influence Maximization on Multicore Architectures

The goal of influence maximization is to select k most-influential vertices or seeds in a network, where influence is defined by a given diffusion process. The problem has a number of important applications such as viral marketing, information spread, and epidemic control. Although computing optimal seed set is NP-Hard, due to the submodular nature of the problem efficient approximation algorithms exist. However, even state-of-the-art parallel implementations are limited by a sampling step that incurs large memory footprints. This in turn limits the problem size reach and approximation quality. In this work, we study the memory footprint of the sampling process collecting reverse reachability information in the IMM algorithm over large real-world social networks. We present an adaptive and memory-efficient optimization approach for a state-of-the-art multi-threaded parallel influence maximization algorithm. Our approach,HuffMax, uses a portion of the reverse reachable (RR) sets collected by the algorithm to learn the characteristics of the graph. Then, it compresses the intermediate reverse reachability information with Huffman coding, and queries directly on the compressed data to preserve the memory savings obtained through compression. We also propose an efficient sampling strategy based on the distribution of RR sets, which can further reduce the computation time for typical social networks with long-tail distributions. Considering a NUMA architecture, we scale up our solution on 128-core CPUs and reduce the memory footprint by up to 45.7% with negligible time overhead (or even faster) and without perceivable loss of accuracy.

Chen, Xinyu↗

DOE OSTI2022

Comprehensive Characterization of Multi-Phase Sulfurized Polyacrylonitrile Cathodes for Lithium-Sulfur Batteries

Sulfurized polyacrylonitrile (SPAN) is considered one of the most promising cathode materials to overcome the operational challenges that plague lithium-sulfur (Li-S) batteries. However, material properties and electrochemical performance implications of SPAN prepared under different synthesis conditions are not yet fully investigated. In this study, we show the impacts of different synthesis conditions on the formation of sulfur to PAN bonds and redox reaction mechanisms of multi-phase SPAN via comprehensive material and electrochemical characterizations. In-situ Raman analysis was first applied to study the multi-phase SPAN-based Li-S cells. We found that both elemental sulfur and chemically bonded sulfur are present under the synthesis condition of 300 degree C/3 h along with unreacted PAN. The incompletely sulfurized, multi-phase SPAN exhibited an unusually rapid capacity degradation in the resultant Li-S cells, which is attributed to polysulfide formation and continuously growing interfacial impedance in the Li-S cells. On the other hand, SPAN samples prepared under the synthesis condition of 350 degree C/3 h are found completely sulfurized with chemically bonded sulfur to the PAN backbone without the presence of free elemental sulfur. Complete sulfurization of SPAN led to exceptionally stable cycle performance due to excellent reversible redox processes of chemically bonded sulfur with Li+ in the Li-S cells.

DIRECT ENERGY CONVERSION,ENERGY STORAGE↗

DOE OSTI2023

Parallel Algebraic Multigrid for Fusion and Higher-Order PDEs

Multigrid methods play a key role in large-scale scientific simulation because they are among the fastest and most scalable approaches for solving the underlying sparse linear systems of equations that arise from a wide array of Partial Differential Equation (PDE) discretizations. Algebraic multigrid (AMG) is a special type of multigrid method that depends only on the description of the linear system, giving it better portability and broader applicability than geometric multigrid, as it requires no explicit knowledge of the problem geometry. Even though these methods are widely used today, there are still applications where further development is needed. In this report, we focus on PDEs with higher-order terms (e.g., fourth order), concentrating on a PDE that arises in tokamak edge plasma simulations (a tokamak is a machine that confines a plasma using magnetic fields and is believed to be the leading plasma confinement concept for future fusion power plants). General multigrid relaxes a linear system on coarser grids and reverses this process with interpolation, but standard AMG methods struggle with the aforementioned higher-order PDEs. We investigate cyclic coarsening and interpolation heuristics, as well as new iterative approximation methods of refining the solution at each grid to improve the existing multigrid approach. To this end, we ensure that these techniques are transferable to a parallelized setting with LLNL’s supercomputers.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Advanced Compressors for CO2-Based Power Cycles and Energy

Pumped thermal energy storage (PTES) is a cost-effective method for grid-scale, long-duration electrical energy storage (LDES). PTES uses a heat pump cycle to transfer thermal energy from a low temperature reservoir (LTR) to a high temperature reservoir (HTR), later using a heat engine cycle to reverse the process. A key component of the PTES system, the heat pump compressor, represents a significant driver to the cost, performance and operating characteristics of the PTES system. For grid-scale charging (>100 MW), traditional compressor scaling charts indicate that the operating conditions needed would be best served by a multistage axial compressor. While frame gas turbine compressors at these power ratings exist and operate at higher pressure ratios than needed for the CO2 PTES system, the inlet pressure and fluid density of this application exceed experience values. A conceptual design of a large-scale CO2 axial compressor was completed, including mean-line estimates of the compressor performance at full power conditions. The results of the conceptual design were used to refine the PTES cycle design, and updated operating conditions provided for further aero design optimization. A roughly one third scale of the first three stages of the 100 MW compressor was designed, built, and tested at relevant PTES charging conditions. Results of this test program are compared against high-resolution computational fluid dynamics models.

Compressor Heat↗

DOE OSTI2023

Earth Abundant Oxidation Catalysts for Removal of Contaminants of Emerging Concern from Wastewater: Homogeneous Catalytic Screening of Monomeric Complexes

Twenty novel Mn, Fe, and Cu complexes of ethylene cross-bridged tetraazamacrocycles with potentially copolymerizable allyl and benzyl pendant arms were synthesized and characterized. Multiple X-ray crystal structures demonstrate the cis-folded pseudo-octahedral geometry forced by the rigidifying ethylene cross-bridge and show that two cis coordination cites are available for interaction with substrate and oxidant. The Cu complexes were used to determine kinetic stability under harsh acidic and high-temperature conditions, which revealed that the cyclam-based ligands provide superior stabilization with half-lives of many minutes or even hours in 5 M HCl at 50–90 °C. Cyclic voltammetry studies of the Fe and Mn complexes reveal reversible redox processes indicating stabilization of Fe 2+ /Fe 3+ and Mn 2+ /Mn 3+ /Mn 4+ oxidation states, indicating the likelihood of catalytic oxidation for these complexes. Finally, dye-bleaching experiments with methylene blue, methyl orange, and rhodamine B demonstrate efficient catalytic decolorization and allow selection of the most successful monomeric catalysts for copolymerization to produce future heterogeneous water purification materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Synthetic membranes and methods of use thereof

The present invention relates to synthetic membranes and use of these synthetic membranes for isolation of volatile organic compounds and purification of water. The synthetic membrane includes a hydrophobic polymer layer located on a polymeric membrane support layer. The invention includes a method of isolating volatile organic compounds with the synthetic membrane by contacting a volatile organic mixture with the hydrophobic polymer layer of the synthetic membrane and removing volatile organic compounds from the polymeric membrane support layer of the synthetic membrane by a process of pervaporation. The invention also includes a method of purifying water with the synthetic membrane by contacting an ionic solution with the hydrophobic polymer layer of the synthetic membrane and removing water from the polymeric membrane support layer of the synthetic membrane by a process of reverse osmosis. The invention also relates to methods of isolating non-polar gases by gas fractionation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Synthetic membranes and methods of use thereof

Belfort, Georges↗

DOE OSTI2021

Synthetic membranes and methods of use thereof

Belfort, Georges↗

DOE OSTI2024

An octahedral Mach B-dot probe for 3D flows and magnetic fields in the edge of reversed field pinches

Measurements and simulations show that plasma relaxation processes in the reversed field pinch drive and redistribute both magnetic flux and momentum. To examine this relaxation process, a new 3D Mach B-dot probe has been constructed. This probe collects ion saturation currents through six molybdenum electrodes arranged on the flattened vertices of an octahedron made of boron nitride (BN). The ion saturation current flows through configurable voltage dividers for measurement and returns through one of six selectable return electrodes equally spaced along the 12 cm BN probe arm. In addition, the probe arm houses three B-dot magnetic pickup coils in the BN stalk immediately below to the octahedron, to measure the local magnetic field. Inserted in the Madison Symmetric Torus (MST) during deuterium discharges with 220 kA plasma current, density of 0.8 × 10 13 cm –3 , the probe collects ion saturation currents with sawtooth-like peaks correlated with relaxation events. This compact octahedral design fitting six Mach electrode surfaces within a 1 cm3 cube will enable future multi-point, multi-field probes compatible with the 1.5 in. ports of MST. Such probes will allow for flow circulation, current, and canonical vorticity to be calculated in the center of the finite difference stencil formed by the measurement locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Intermediate-Temperature Reverse Water–Gas Shift under Process-Relevant Conditions Catalyzed by Dispersed Alkali Carbonates

Not Available

Tamakuwala, Kesha N.↗

DOE OSTI2024

Advanced Process Control and Dynamic Optimization of Reversible Solid Oxide Cell Systems for Performance and Long-Term Health

This presentation was delivered at the 2024 Hydrogen Annual Merit Review Meeting. It focuses on three aspects of projects focusing on solid oxide cell systems- advanced control including nonlinear model predictive control and traditional control, dynamic optimization with due consideration of chemical degradation over the cell lifetime, dynamic optimization considering physical degradation.

Allan, Douglas↗

DOE OSTI2023

Code for the manuscript titled "Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces"

We would like to disclose two scripts, written in Jupyter notebook, in which we implement the "Blackout Diffusion Process" described in the manuscript "Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces" (LA-UR-23-20509), to be submitted to the International Conference of Machine Learning (ICML). The abstract of the manuscript is append below. == Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, which occur in many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process. We relate the theory to the existing continuous-state Gaussian diffusion and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce "Blackout Diffusion", which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10 dataset confirm the feasibility of generative diffusion modeling in a discrete space. Generalizing from specific (Gaussian) forward processes to a more general framework also sheds light on how to interpret generative diffusion models and their mathematical structure, which we comment on.

Lin, Yen Ting↗

DOE OSTI2025

A layered Prussian blue analogue as fast-charging negative electrode material for lithium-ion batteries

The simultaneous achievement of fast-charging and high specific capacity remains a critical challenge for lithium-ion battery negative electrodes. Here we report a layered manganese-based Prussian blue analogue, synthesized through vacancy control and subsequent thermal transformation. As a conversion-type negative electrode, this material exhibits high-rate performance, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 , and operates at a moderate average voltage of approximately 1.2 V vs. Li/Li + , which mitigates lithium plating risks. This high-rate capability stems from the analogue’s specific linkage configurations, which facilitate a high content of active transition metal and strong Li+ adsorption at nitrogen sites. The high transition metal content enables a high reversible capacity, while strong Li + adsorption promotes an efficient initial crystalline-to-amorphous transformation. This process induces dynamically reversible component migration during subsequent cycling, thereby enhancing conversion reaction kinetics. Our findings provide insights into the application of Prussian blue analogues as fast-charging negative electrode materials. The development of fast-charging and high-capacity negative electrodes is critical for advanced lithium-ion batteries. Here, authors use a vacancy engineering strategy to develop a layered Prussian blue analogue with competitive rate capability, delivering a specific capacity of 510 mAh g −1 at a specific current of 8 A g −1 .

25 ENERGY STORAGE↗

DOE OSTI2022

Magnetic Energy Conversion in Magnetohydrodynamics: Curvature Relaxation and Perpendicular Expansion of Magnetic Fields

Abstract The mechanisms and pathways of magnetic energy conversion are an important subject for many laboratory, space, and astrophysical systems. Here, we present a perspective on magnetic energy conversion in magnetohydrodynamics through magnetic field curvature relaxation (CR) and perpendicular expansion (PE) due to magnetic pressure gradients, and quantify their relative importance in two representative cases, namely 3D magnetic reconnection and 3D kink-driven instability in an astrophysical jet. We find that the CR and PE processes have different temporal and spatial evolutions in these systems. The relative importance of the two processes tends to reverse as the system enters the nonlinear stage from the instability growth stage. Overall, the two processes make comparable contributions to magnetic energy conversion, with the PE process somewhat stronger than the CR process. We further explore how these energy conversion terms can be related to particle energization in these systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Energy transduction by reversible electron bifurcation

Electron bifurcation is a biological energy conversion process that oxidizes a two-electron donor at medium potential, coupled to the reduction of a high- and a low-potential acceptor species. This process is often fully reversible (can occur close to ΔG ≈ 0), allowing the creation of strong reductants with minimal free energy cost, using compounds with higher reduction potentials. For many years, the internal workings of electron bifurcating enzymes were poorly understood, especially regarding how short-circuit reactions are prevented. Recently, a conserved energy landscape was proposed to naturally insulate against short-circuit reactions, enabling efficient and reversible electron bifurcation (the reversible EB scheme). Here, we review the physical principles that underpin the EB scheme, describe how the reversible EB scheme is distinct from previous views, and outline questions that remain open.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces

Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, including many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process using exact (as opposed to variational) analysis. We relate the theory to the existing continuous-state Gaussian diffusion as well as other approaches to discrete diffusion, and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce “Blackout Diffusion”, which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10, Binarized MNIST, and CelebA datasets confirm the feasibility of our approach. Generalizing from specific (Gaussian) forward processes to discrete-state processes without a variational approximation sheds light on how to interpret diffusion models, which we discuss.

Santos, Javier E.↗