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At least 487 records · Page 27

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DOE OSTI2021

The Value of Watching How Materials Grow: A Multimodal Case Study on Halide Perovskites

Material synthesis is one of the most important aspects in humankinds’ endeavor to discover and create new materials for energy applications. One strategy to tailor materials with desired functions in a rational way is by knowing how functions relate to structure, synthetic variables, arrangement of atoms and molecules, and how functions evolve during synthesis. In order to accelerate materials synthesis, discovery, and optimization by 10 times it is the right time now to integrate computational tools, synthesis, and characterization. One particular barrier to realizing this concept is the understanding of when and how phases form in real time during synthesis, which is challenging to asses by existing theoretical frameworks. In addition, transient or metastable phases with positive free energy above the lowest-free energy ground state can be revealed by such real time (in situ) measurements. Metastable materials are ubiquitous in condensed matter and can show superior properties compared to their equilibrium form. This work discusses the value of emerging multimodal in situ characterizations exemplified on hybrid halide perovskites. Finally, the ways in which the implementation of in situ measurements can advance the materials science synthesis field as well as their role to enable close-loop feedback control and autonomous synthesis are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Alternative Energy Carriers: Unique Interfaces for Electrochemical Hydrogenic Transformations

Abstract The shift toward renewable energy generation sources, characterized by their non‐carbon emitting but variable nature, has spurred significant innovation in energy storage technologies. Advancements in foundational understanding from investments in basic science and clever engineering solutions, coupled with increasing industrial adoption, have resulted in a notable reduction in the cost of storing electricity from variable energy generation sources. These developments have paved the way for the exploration of new and innovative forms of energy storage that deviate from traditional technologies. In this perspective, it is posited that the progress made in energy storage research over recent years has opened the door to the development of energy carriers for technologies that are yet to be realized. To illustrate this concept, examples of alternative energy carriers are provided within the context of unique electrochemical interfaces for electrochemical hydrogenic transformations. The unique properties of these interfaces and electrochemical systems can be leveraged in ways not yet imagined, creating new possibilities for energy storage. A perspective on the progress and challenges for each interface as well as a general outlook for the advancement of energy carrier systems are provided.

25 ENERGY STORAGE↗

DOE OSTI2023

Correlation of Broad Absorption Band with Small Singlet‐Triplet Energy Gap in Organic Photovoltaics

Abstract Organic photovoltaics (OPV) are one of the most effective ways to harvest renewable solar energy, with the power conversion efficiency (PCE) of the devices soaring above 19 % when processed with halogenated solvents. The superior photocurrent of OPV over other emerging photovoltaics offers more opportunities to further improve the efficiency. Tailoring the absorption band of photoactive materials is an effective way to further enhance OPV photocurrent. However, the field has mostly been focusing on improving the near‐infrared region photo‐response, with the absorption shoulders in short‐wavelength region (SWR) usually being neglected. Herein, by developing a series of non‐fullerene acceptors (NFAs) with varied side‐group conjugations, we observe an enhanced SWR absorption band with increased side‐group conjugation length. The underpinning factors of how molecular structures and geometries improve SWR absorption are clearly elucidated through theoretical modelling and crystallography. Moreover, a clear relationship between the enhanced SWR absorption and reduced singlet‐triplet energy gap is established, both of which are favorable for the OPV performance and can be tailored by rational structure design of NFAs. Finally, the rationally designed NFA, BO‐TTBr, affords a decent PCE of 18.5 % when processed with a non‐halogenated green solvent.

Chemistry↗

DOE OSTI2025

An overview of switchgrass phenotypes variability across diverse populations and their implications for conversion to fuels

There have been substantial changes to the human lifestyle over the past two centuries, which are reflected in the amount of fuel we consume to power our day-to-day needs. The way we use these resources has indeed manifested in an overdependence on non-renewable energy sources, such as coal and petroleum, for generating electricity and powering our transportation needs. There is a pressing need to explore alternative ways of fueling our current lifestyle without impacting the environment. Biofuels have long been touted as a sustainable solution for use as drop-in fuels in aviation and maritime applications. Still, they have yet to establish themselves as a competitive commercial alternative, necessitating further research and development. Lignocellulosic biomass is an underutilized resource that is widely accessible for the commercial processing of renewable biofuels. Bioenergy crops, such as switchgrass (Panicum virgatum L.), which can be cultivated on marginal lands with minimal competition for agricultural land, are an ideal and promising candidate for bulk-scale biofuel synthesis. Over the past 30 years, significant progress has been made in breeding and genetically modifying these grasses to enhance their drought resilience and subsequent yields. However, discrepancies in biomass composition can lead to irregular feedstocks for downstream operations, which in turn affect overall production targets for biofuels. Here, this review examines the variability in switchgrass (P. virgatum L.) biomass phenotypes across diverse populations and plant components, and their implications for biofuel conversion. The study highlights significant variations in biomass yield, composition, and cell wall chemistry both between switchgrass genotypes and within individual cultivars. Key findings include differences in cellulose, hemicellulose, and lignin content between leaves and stems, which affect biomass digestibility and ethanol yield. The review also discusses the impact of lignin chemistry, particularly the syringyl/guaicyl (S/G) ratio, on the efficiency of biomass saccharification. Furthermore, it explores how these variations respond differently to various pretreatment techniques, affecting overall biofuel production. We conclude that understanding and quantifying this variability is crucial for optimizing switchgrass as a feedstock for commercial biofuel production, thereby potentially addressing the pressing need for sustainable energy sources in sectors such as aviation.

Kousika, Rohit [Univ. of Tennessee, Knoxville, TN ↗

DOE OSTI2025

Integrated Ammonia Capture and Exchange on Ion‐Exchanged 4A Zeolites

Ammonia poses a challenge in effluent gas streams due to its corrosive nature. However, in fusion settings tritiated ammonia can be formed, leading to both tritium loss in inventory and the generation of reactive species. Therefore, identifying pathways in which both tritium can be recovered, and the ammonia can be easily handled would be beneficial. One such way to do so would be to combine two useful techniques: ammonia sequestration and hydrogen exchange (ND 3 →NH 3 ). However, materials that can both adsorb ammonia and subsequently perform reactions on ammonia have not been well explored. Here, in this work, we present the development of ion-exchanged A-type zeolites to be utilized as a support material for platinum catalysts. In this way, the zeolite can adsorb ammonia and the platinum catalyst can facilitate hydrogen exchange allowing for bifunctional reactivity of the material to be achieved. A variety of elements were explored for their effect on A-type zeolites and resulted in an isotopic difference in the adsorption of ND 3 and NH 3 , noting the use of deuterium as a surrogate for tritium. Several platinum-impregnated zeolites were able to remove ND 3 from the gas stream, indicating that utilizing these materials in isotope recovery processes would improve accountability of these valuable hydrogen isotopes.

Koch, Christopher J. [Savannah River National Labo↗

DOE OSTI2026

Enhancing NO Reduction by CO Over NiO/CeO 2 Catalyst by Optimizing the Metal Oxide–Support Interaction

Noble metal catalysts are widely used in three-way catalysts (TWCs) due to their high efficiency, but their scarcity and high cost drive the need for effective, low-cost alternatives. Here, in this work, a series of NiO/CeO 2 catalysts were engineered by modulating the OH content and crystallite size of the CeO 2 support. This approach yielded Ni species ranging from isolated single atoms to small clusters and larger aggregates, with varied NiO/CeO 2 interaction strengths. Evaluation of their performance in NO reduction by CO, CO oxidation, and the water–gas shift reaction revealed that the NiO/CeO 2 -300 catalyst, featuring small CeO 2 crystallites and highly dispersed NiO clusters, delivered superior activity for NO reduction and CO oxidation. It was demonstrated that small NiO clusters, due to their efficient CO adsorption and activation, were more active than Ni single atoms. Furthermore, the presence of water was found to influence the catalyst stability, with NiO clusters less stable than single atoms likely due to the hydroxylation effect leading to the formation of Ni(OH) 2 . Oxygen storage capacity measurements revealed that performance was governed by a combination of CeO 2 crystallite size and the abundance of NiO/CeO 2 interfaces. These findings demonstrated that the catalytic performance of Ni/CeO 2 systems could be maximized by optimizing the Ni nanostructure and its interaction with CeO 2 support, positioning them as a promising, multifunctional nonprecious alternative for three-way catalysis application.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Evaluating integration and performance of containerized climate applications on a Hewlett Packard Enterprise Cray system

Containers have taken over large swaths of cloud computing as the most convenient way of packaging and deploying applications. The features that containers offer for packaging and deploying applications translate to high performance computing (HPC) as well. At The National Oceanic and Atmospheric Administration, containers provide an easy way to build and distribute complex HPC applications, allowing faster collaboration, portability, and experiment computer environment reproducibility amongst the scientific community. The challenge arises when applications rely on message passing interface (MPI). This necessitates investigation into how to properly run these applications with their own unique requirements and produce performance on par with native runs. We investigate the MPI performance for benchmarks and containerized climate models for various containers covering selection of compiler and MPI library combinations from the Cray provided programming environments on the Cray XC supercomputer GAEA. Performance from the benchmarks and the climate models shows that for the most part containerized applications perform on par with the natively built applications when the system optimized Cray MPICH libraries are bound into the container, and the hybrid model containers have poor performance in comparison. We also describe several challenges and our solutions in running these containers, particularly challenges with heterogeneous jobs for the containerized model runs.

Abraham, Subil↗

DOE OSTI2025

A Methodology for the Analysis of Water Oxidation Electrocatalysts in the Absence of Limiting Current that Avoids the Pitfalls of Existing Methods

Water oxidation is an important reaction studied as a way to generate electrons from water, to promote water splitting and the formation of green hydrogen. When using electrodes to drive homogeneous water oxidation catalysis, cyclic voltammograms are analyzed to provide catalytic rate constants. There are two main methods, foot-of-the-wave analysis (FOWA) and limiting current analysis. FOWA relies on approximations inherent to analyzing water oxidation catalysis, such as determining the formal potential of the catalytic intermediate, E 0 cat . Limiting current methods are the optimal way to analyze catalyst performance but rely on observable limiting current, which is virtually never seen in water oxidation. To avoid those issues, a method is proposed for analyzing nonideal cyclic voltammetry waveshapes in water oxidation: by analyzing rate data across a large range of potentials, an optimal potential, E 0 cat , can be obtained, where catalytic current, i cat , is nearly independent of scan rate and has a linear dependency on buffer concentration. Here, the method is applied to four homogeneous water oxidation catalysts with prior extensive electrochemical elucidation, all of which lack an ideal, purely kinetic waveshape in cyclic voltammetry. Application of the method avoids the biases of the other methods cited for the kinetic analyses of water oxidation catalysts.

14 SOLAR ENERGY↗

DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗

DOE OSTI2023

Subordinated Gaussian Processes for Solar Irradiance

Traditionally the power grid has been a one-way street with power flowing from large transmission-connected generators through the distribution network to consumers. This paradigm is changing with the introduction of distributed renewable energy resources (DERs), and with it, the way the grid is managed. There is currently a dearth of high fidelity solar irradiance datasets available to help grid researchers understand how expansion of DERs could affect future power system operations. Realistic simulations of by-the-second solar irradiances are needed to study how DER variability affects the grid. Irradiance data are highly non-stationary and non-Gaussian, and even modern time series models are challenged by their distributional properties. We develop a subordinated non-Gaussian stochastic model whose simulations realistically capture the distribution and dependence structure in measured irradiance. We illustrate our approach on a fine resolution dataset from Hawaii, where our approach outperforms standard nonlinear time series models.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗

DOE OSTI2020

Evolution of Electric Sector Water Use Under Alternative Electricity Futures

Increasing competition for water resources in the United States could create future challenges for allocating and using thermal cooling water in the U.S. electric power sector. While thermal power plant retirements and the growth of wind and solar technologies can reduce national aggregate power sector cooling water use, local water constraints and growing demand for agricultural or municipal supply could create greater needs for higher-cost alternative water supplies such as groundwater or recycled wastewater. For some regions, these incentives could change future electricity planning and operational decisions. These relationships and impacts are studied here using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS), a national electric sector planning model that has recently been upgraded to include a highly detailed representation of thermal cooling water demand and supply. Thermal power technologies are differentiated by both cooling technology and water source type to track and constrain thermal cooling water use in a way that incorporates both physical and legal water considerations in the United States. This capability is exercised under a range of electricity sector futures with alternative technology costs, fuel prices, and water constraints to illustrate ways that U.S. electric sector water use could evolve under uncertain future electric sector drivers. In exploring changes to regional generation and transmission planning and operation, water requirements, and cost, we highlight the environmental and economic impacts of future power sector water decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Quinoa protein extract: an effective alternative for the fining of wine phenolics

Abstract BACKGROUND Lately, there has been an increasing interest in using plant‐derived proteins for wine phenolic fining. Proteins extracted from cereals, potatoes, and legumes have been proposed as effective fining agents, but only those from pea, wheat, and potatoes have been approved for their use in wine. This work aimed at determining the fining ability of quinoa ( Chenopodium quinoa Willd.) protein extracts (QP), compared to commercial fining agents, on red wines. RESULTS The trials compared the performance of QP (30 and 50 g/hL), two potato protein extracts and gelatin, at two different contact times (48 and 96 h), using Petit Verdot, Malbec, and Cabernet Sauvignon wines. Turbidity, total phenolics, precipitable tannins, catechins, and color characteristics were determined. QP reduced the turbidity of all wines in a similar way to commercial fining agents. Both doses of QP significantly reduced tannins and other phenolic measures, including color intensity reductions, in a similar way to commercial fining agents. CONCLUSION QP behaved as an effective fining agent that deserves further studies in order to improve its performance and advance its characterization. © 2022 Society of Chemical Industry.

Pino‐Ramos, Liudis L.↗

DOE OSTI2024

Structure preserving and energy dissipative contact approaches for implicit dynamics

In this work, several structure preserving and energy dissipative contact approaches are proposed and evaluated. The time integration schemes considered are general with regard to the version of constraint type, but here the emphasis was on mortar contact. The proposed mortar contact approach conserves both linear and angular momentum for mortar contact in a novel way. The proposed time integration scheme can conserve energy or provide strict contact dissipation. In addition, the proposed scheme enforces both gap constraints and gap velocity constraints (i.e., persistency). Using a midstep time integrator often causes energy dissipation during initial impact, here this energy can be recovered in a novel way. Enforcing the gap velocity constraint mitigates the contact chatter of the contact pressure and nodes in many problems. Whereas some approaches enforce the persistency condition and gap constraints simultaneously during the solution of the equations of motion (EOM) requiring multipliers for both constraints included in the equation set, here the gap constraint is solved through the equations of motion and the persistency condition is satisfied in the time integration scheme by the velocity update after the equations of motion. It is shown that this approach is strictly dissipative in that a plastic contact condition can be achieved. Analogous to a coefficient of restitution for rigid bodies, any dissipated energy can then be returned upon release if energy conservation is desired. Structure preserving methods are good for long-time dynamics simulations and energy conserving and strictly dissipative methods can overcome stability issues associated with standard time integration algorithms such as the Newmark method.

42 ENGINEERING↗

DOE OSTI2021

Fractons and Exotic Symmetries from Branes

The emerging study of fractons, a new type of quasi-particle with restricted mobility, has motivated the construction of several classes of interesting continuum quantum field theories with novel properties. One such class consists of foliated field theories which, roughly, are built by coupling together fields supported on the leaves of foliations of spacetime. Another approach, which we refer to as exotic field theory, focuses on constructing Lagrangians consistent with special symmetries (like subsystem symmetries) that are adjacent to fracton physics. A third framework is that of infinite-component Chern-Simons theories, which attempts to generalize the role of conventional Chern-Simons theory in describing (2+1)D Abelian topological order to fractonic order in (3+1)D. The study of these theories is ongoing, and many of their properties remain to be understood. Historically, it has been fruitful to study QFTs by embedding them into string theory. One way this can be done is via D-branes, extended objects whose dynamics can, at low energies, be described in terms of conventional quantum field theory. Further, QFTs that can be realized in this way can then be analyzed using the rich mathematical and physical structure of string theory. In this paper, we show that foliated field theories, exotic field theories, and infinite-component Chern-Simons theories can all be realized on the world-volumes of branes. We hope that these constructions will ultimately yield valuable insights into the physics of these interesting field theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Quantitative methods and modeling to assess COVID–19–interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

State preparation and evolution in quantum computing: a perspective from Hamiltonian moments

Quantum algorithms on the noisy intermediate-scale quantum (NISQ) devices are expected to simulate quan- tum systems that are classically intractable to demonstrate quantum advantages. However, the non-negligible gate error on the NISQ devices impedes the conventional quantum algorithms to be implemented. Practical strategies usually exploit hybrid quantum-classical quantum algorithms to demonstrate potentially useful ap- plications of quantum computing in the NISQ era. Among the numerous hybrid quantum-classical algorithms, recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments, ?f|Hˆn|f? (n = 1, 2, · · · ), with respect to quantum state |f?. In this tutorial, we will give a brief review of these quantum algorithms with focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies based on the quantum computed moments. Furthermore, we will present a tutorial to show how we can measure and compute the Hamiltonian moments of a four-site Heisenberg model, and compute the energy and magnetization of the model utilizing the imaginary time evolution in the real IBM-Q NISQ hardware environment. Along this line, we will further discuss some practical issues associated with these algorithms. We will conclude this tutorial review by overviewing some possible developments and applications in this direction in the near future.

Aulicino, Joseph C.↗

DOE OSTI2023

Adaptive basis sets for practical quantum computing

Electronic structure calculations on small systems such as H 2 , H 2 O, LiH, and BeH 2 with chemical accuracy are still a challenge for the current generation of noisy intermediate-scale quantum (NISQ) devices. One of the reasons is that due to the device limitations, only minimal basis sets are commonly applied in quantum chemical calculations, which allows one to keep the number of qubits employed in the calculations at a minimum. However, the use of minimal basis sets leads to very large errors in the computed molecular energies as well as potential energy surface shapes. One way to increase the accuracy of electronic structure calculations is through the development of small basis sets better suited for quantum computing. In this work, we show that the use of adaptive basis sets, in which exponents and contraction coefficients depend on molecular structure, provides an easy way to dramatically improve the accuracy of quantum chemical calculations without the need to increase the basis set size and thus the number of qubits utilized in quantum circuits. As a proof of principle, we optimize an adaptive minimal basis set for quantum computing calculations on an H 2 molecule, in which exponents and contraction coefficients depend on the H—H distance, and apply it to the generation of H 2 potential energy surface on IBM-Q quantum devices. The adaptive minimal basis set reaches the accuracy of the double-zeta basis sets, thus allowing one to perform double-zeta quality calculations on quantum devices without the need to utilize twice as many qubits in simulations. This approach can be extended to other molecular systems and larger basis sets in a straightforward manner.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Noise Robustness and Experimental Demonstration of a Quantum Generative Adversarial Network for Continuous Distributions

Abstract The potential advantage of machine learning in quantum computers is a topic of intense discussion in the literature. Theoretical, numerical, and experimental explorations will most likely be required to understand its power. There have been different algorithms proposed to exploit the probabilistic nature of variational quantum circuits for generative modeling. In this paper, a hybrid architecture for quantum generative adversarial networks (QGANs) is employed and their robustness in the presence of noise is studied. A simple way of adding different types of noise to the quantum generator circuit is devised, and the noisy hybrid QGANs (HQGANs) are simulated numerically to learn continuous probability distributions, and to show that the performance of HQGANs remains unaffected. The effect of different parameters on the training time is also investigated to reduce the computational scaling of the algorithm and simplify its deployment on a quantum computer. The training on Rigetti's Aspen‐4‐2Q‐A quantum processing unit is then performed, and the results from the training are presented. The authors' results pave the way for experimental exploration of different quantum machine learning algorithms on noisy intermediate‐scale quantum devices.

Anand, Abhinav↗