Showing papers by "Sandia National Laboratories published in 2021"

The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support

Abstract: Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling. The tremendous potential benefits of SA are, however, yet to be fully realized, both for advancing mechanistic and data-driven modeling of human and natural systems, and in support of decision making. In this perspective paper, a multidisciplinary group of researchers and practitioners revisit the current status of SA, and outline research challenges in regard to both theoretical frameworks and their applications to solve real-world problems. Six areas are discussed that warrant further attention, including (1) structuring and standardizing SA as a discipline, (2) realizing the untapped potential of SA for systems modeling, (3) addressing the computational burden of SA, (4) progressing SA in the context of machine learning, (5) clarifying the relationship and role of SA to uncertainty quantification, and (6) evolving the use of SA in support of decision making. An outlook for the future of SA is provided that underlines how SA must underpin a wide variety of activities to better serve science and society.

Quantum Computer Systems for Scientific Discovery

Abstract: The great promise of quantum computers comes with the dual challenges of building them and finding their useful applications. We argue that these two challenges should be considered together, by co-designing full-stack quantum computer systems along with their applications in order to hasten their development and potential for scientific discovery. In this context, we identify scientific and community needs, opportunities, a sampling of a few use case studies, and significant challenges for the development of quantum computers for science over the next 2--10 years. This document is written by a community of university, national laboratory, and industrial researchers in the field of Quantum Information Science and Technology, and is based on a summary from a U.S. National Science Foundation workshop on Quantum Computing held on October 21--22, 2019 in Alexandria, VA.

Development of Quantum Interconnects (QuICs) for Next-Generation Information Technologies

Abstract: Just as classical information technology rests on a foundation built of interconnected information-processing systems, quantum information technology (QIT) must do the same. A critical component of such systems is the interconnect, a device or process that allows transfer of information between disparate physical media, for example, semiconductor electronics, individual atoms, light pulses in optical fiber, or microwave fields. While interconnects have been well engineered for decades in the realm of classical information technology, quantum interconnects (QuICs) present special challenges, as they must allow the transfer of fragile quantum states between different physical parts or degrees of freedom of the system. The diversity of QIT platforms (superconducting, atomic, solid-state color center, optical, etc.) that will form a quantum internet poses additional challenges. As quantum systems scale to larger size, the quantum interconnect bottleneck is imminent, and is emerging as a grand challenge for QIT. For these reasons, it is the position of the community represented by participants of the NSF workshop on Quantum Interconnects that accelerating QuIC research is crucial for sustained development of a national quantum science and technology program. Given the diversity of QIT platforms, materials used, applications, and infrastructure required, a convergent research program including partnership between academia, industry and national laboratories is required.

Quantum Simulators: Architectures and Opportunities

Abstract: Quantum simulators are a promising technology on the spectrum of quantum devices from specialized quantum experiments to universal quantum computers. These quantum devices utilize entanglement and many-particle behaviors to explore and solve hard scientific, engineering, and computational problems. Rapid development over the last two decades has produced more than 300 quantum simulators in operation worldwide using a wide variety of experimental platforms. Recent advances in several physical architectures promise a golden age of quantum simulators ranging from highly optimized special purpose simulators to flexible programmable devices. These developments have enabled a convergence of ideas drawn from fundamental physics, computer science, and device engineering. They have strong potential to address problems of societal importance, ranging from understanding vital chemical processes, to enabling the design of new materials with enhanced performance, to solving complex computational problems. It is the position of the community, as represented by participants of the NSF workshop on "Programmable Quantum Simulators," that investment in a national quantum simulator program is a high priority in order to accelerate the progress in this field and to result in the first practical applications of quantum machines. Such a program should address two areas of emphasis: (1) support for creating quantum simulator prototypes usable by the broader scientific community, complementary to the present universal quantum computer effort in industry; and (2) support for fundamental research carried out by a blend of multi-investigator, multi-disciplinary collaborations with resources for quantum simulator software, hardware, and education.

Durability of anion exchange membrane water electrolyzers

Abstract: Interest in the low-cost production of clean hydrogen is growing. Anion exchange membrane water electrolyzers (AEMWEs) are considered one of the most promising sustainable hydrogen production technologies because of their ability to split water using platinum group metal-free catalysts, less expensive anode flow fields, and bipolar plates. Critical to the realization of AEMWEs is understanding the durability-limiting factors that restrict the long-term use of these devices. This article presents both durability-limiting factors and mitigation strategies for AEMWEs under three operation modes, i.e., pure water-fed (no liquid electrolyte), concentrated KOH-fed, and 1 wt% K2CO3-fed operating at a differential pressure of 100 psi. We examine extended-term behaviors of AEMWEs at the single-cell level and connect their behavior with the electrochemical, chemical, and mechanical instability of single-cell components. Finally, we discuss the pros and cons of AEMWEs under these operation modes and provide direction for long-lasting AEMWEs with highly efficient hydrogen production capabilities.

Towards data-driven next-generation transmission electron microscopy.

Abstract: Electron microscopy touches on nearly every aspect of modern life, underpinning materials development for quantum computing, energy and medicine. We discuss the open, highly integrated and data-driven microscopy architecture needed to realize transformative discoveries in the coming decade.

Covalent Graphene‐MOF Hybrids for High‐Performance Asymmetric Supercapacitors

Abstract: In this work, the covalent attachment of an amine functionalized metal-organic framework (UiO-66-NH2 = Zr6 O4 (OH)4 (bdc-NH2 )6 ; bdc-NH2 = 2-amino-1,4-benzenedicarboxylate) (UiO-Universitetet i Oslo) to the basal-plane of carboxylate functionalized graphene (graphene acid = GA) via amide bonds is reported. The resultant GA@UiO-66-NH2 hybrid displayed a large specific surface area, hierarchical pores and an interconnected conductive network. The electrochemical characterizations demonstrated that the hybrid GA@UiO-66-NH2 acts as an effective charge storing material with a capacitance of up to 651 F g-1 , significantly higher than traditional graphene-based materials. The results suggest that the amide linkage plays a key role in the formation of a π-conjugated structure, which facilitates charge transfer and consequently offers good capacitance and cycling stability. Furthermore, to realize the practical feasibility, an asymmetric supercapacitor using a GA@UiO-66-NH2 positive electrode with Ti3 C2 TX MXene as the opposing electrode has been constructed. The cell is able to deliver a power density of up to 16 kW kg-1 and an energy density of up to 73 Wh kg-1 , which are comparable to several commercial devices such as Pb-acid and Ni/MH batteries. Under an intermediate level of loading, the device retained 88% of its initial capacitance after 10 000 cycles.

Ion-capture electrodialysis using multifunctional adsorptive membranes.

Abstract: Technologies that can efficiently purify nontraditional water sources are needed to meet rising global demand for clean water. Water treatment plants typically require a series of costly separation units to achieve desalination and the removal of toxic trace contaminants such as heavy metals and boron. We report a series of robust, selective, and tunable adsorptive membranes that feature porous aromatic framework nanoparticles embedded within ion exchange polymers and demonstrate their use in an efficient, one-step separation strategy termed ion-capture electrodialysis. This process uses electrodialysis configurations with adsorptive membranes to simultaneously desalinate complex water sources and capture diverse target solutes with negligible capture of competing ions. Our methods are applicable to the development of efficient and selective multifunctional separations that use adsorptive membranes.

First Measurement of Coherent Elastic Neutrino-Nucleus Scattering on Argon.

Abstract: We report the first measurement of coherent elastic neutrino-nucleus scattering (CEvNS) on argon using a liquid argon detector at the Oak Ridge National Laboratory Spallation Neutron Source. Two independent analyses prefer CEvNS over the background-only null hypothesis with greater than 3σ significance. The measured cross section, averaged over the incident neutrino flux, is (2.2±0.7)×10^{-39} cm^{2}-consistent with the standard model prediction. The neutron-number dependence of this result, together with that from our previous measurement on CsI, confirms the existence of the CEvNS process and provides improved constraints on nonstandard neutrino interactions.

Roadmap on emerging hardware and technology for machine learning.

Abstract: Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing. A hardware platform based on emerging devices and new architecture is the hope for future computing with dramatically improved throughput and energy efficiency. Building such a system, nevertheless, faces a number of challenges, ranging from materials selection, device optimization, circuit fabrication and system integration, to name a few. The aim of this Roadmap is to present a snapshot of emerging hardware technologies that are potentially beneficial for machine learning, providing the Nanotechnology readers with a perspective of challenges and opportunities in this burgeoning field.

Calendar aging of silicon-containing batteries

Abstract: High-energy batteries for automotive applications require cells to endure well over a decade of constant use, making their long-term stability paramount. This is particularly challenging for emerging cell chemistries containing silicon, for which extended testing information is scarce. While much of the research on silicon anodes has focused on mitigating the consequences of volume changes during cycling, comparatively little is known about the time-dependent degradation of silicon-containing batteries. Here we discuss a series of studies on the reactivity of silicon that, collectively, paint a picture of how the chemistry of silicon exacerbates the calendar aging of lithium-ion cells. Assessing and mitigating this shortcoming should be the focus of future research to fully realize the benefits of this battery technology. Silicon-containing batteries are increasingly becoming a reality in the mass market, but their calendar aging behaviours have received comparatively little attention. Researchers from the Silicon Consortium Project discuss the issues surrounding the calendar lifetime of silicon anodes for lithium-ion batteries.

Synergistically integrated phosphonated poly(pentafluorostyrene) for fuel cells.

Abstract: Modern electrochemical energy conversion devices require more advanced proton conductors for their broad applications. Phosphonated polymers have been proposed as anhydrous proton conductors for fuel cells. However, the anhydride formation of phosphonic acid functional groups lowers proton conductivity and this prevents the use of phosphonated polymers in fuel cell applications. Here, we report a poly(2,3,5,6-tetrafluorostyrene-4-phosphonic acid) that does not undergo anhydride formation and thus maintains protonic conductivity above 200 °C. We use the phosphonated polymer in fuel cell electrodes with an ion-pair coordinated membrane in a membrane electrode assembly. This synergistically integrated fuel cell reached peak power densities of 1,130 mW cm−2 at 160 °C and 1,740 mW cm−2 at 240 °C under H2/O2 conditions, substantially outperforming polybenzimidazole- and metal phosphate-based fuel cells. Our result indicates a pathway towards using phosphonated polymers in high-performance fuel cells under hot and dry operating conditions. Phosphonated polymers have been proposed as anhydrous proton conductors for fuel cells but anhydride formation of phosphonic acid functional groups lowers conductivity. A synergistically integrated phosphonated poly(pentafluorostyrene) is shown to maintain high protonic conductivity above 200 °C.

Integrating solar energy with agriculture: Industry perspectives on the market, community, and socio-political dimensions of agrivoltaics

Abstract: Large-scale development of solar-generated electricity is hindered in some regions of the U.S. by land use competition and localized social resistance. One approach to alleviate these coupled challenges is agrivoltaics: the strategic co-location of solar photovoltaics and agriculture. To explore the opportunities and barriers for agrivoltaics, in-depth interviews with solar industry professionals were conducted and findings suggest that the potential for an agrivoltaic project to retain agricultural interests and consequently increase local support for development is the most significant opportunity of dual use solar. Capable of increasing community acceptance, participants expect agrivoltaics to play an important role in future solar endeavors, especially in places where development may be perceived as a threat to agricultural interests. The results further reveal the interconnections among the various dimensions of social acceptance and suggest that the growth of agrivoltaics is contingent on market adoption of the technology through community acceptance and supportive local regulatory environments. As solar photovoltaic systems transcend niche applications to become larger and more prevalent, the dimensions of social acceptance, including the opportunities and barriers associated with each dimension, can help inform decision making to enhance the growth of agrivoltaics and thus photovoltaic development. The findings can help land use planners, solar developers, and municipal governments make informed decisions that strategically and meaningfully integrate agriculture and solar, and in turn provide multiple benefits including the retention of agricultural land, local economic development, and broad adoption of solar energy technologies.

Roadmap to Biodegradable Plastics—Current State and Research Needs

Abstract: Plastics, with their ubiquitous presence in our daily lives and environment, pose an uncomfortable conundrum. Producers and consumers are aware of the value of these organic ingredients in material...

From Pulses to Circuits and Back Again: A Quantum Optimal Control Perspective on Variational Quantum Algorithms

Abstract: Perspective: A unified view reveals connections between quantum optimal control and variational quantum algorithms, bringing forward ways of advancing both fields.

Machine learning of noise-resilient quantum circuits

Abstract: The impact of hardware noise on quantum circuits is circumvented using a machine learning strategy that outputs the best circuit design for optimizing the performance of a given algorithmic task under the noisy environment.

LAMP Diagnostics at the Point-of-Care: Emerging Trends and Perspectives for the Developer Community.

Abstract: Introduction: Over the past decade, loop-mediated isothermal amplification (LAMP) technology has played an important role in molecular diagnostics. Amongst numerous nucleic acid amplification assays, LAMP stands out in terms of sample-to-answer time, sensitivity, specificity, cost, robustness, and accessibility, making it ideal for field-deployable diagnostics in resource-limited regions.Areas covered: In this review, we outline the front-end LAMP design practices for point-of-care (POC) applications, including sample handling and various signal readout methodologies. Next, we explore existing LAMP technologies that have been validated with clinical samples in the field. We summarize recent work that utilizes reverse transcription (RT) LAMP to rapidly detect SARS-CoV-2 as an alternative to standard PCR protocols. Finally, we describe challenges in translating LAMP from the benchtop to the field and opportunities for future LAMP assay development and performance reporting.Expert opinion: Despite the popularity of LAMP in the academic research community and a recent surge in interest in LAMP due to the COVID-19 pandemic, there are numerous areas for improvement in the fundamental understanding of LAMP, which are needed to elevate the field of LAMP assay development and characterization.

How Machine Learning Will Revolutionize Electrochemical Sciences.

Abstract: Electrochemical systems function via interconversion of electric charge and chemical species and represent promising technologies for our cleaner, more sustainable future. However, their development time is fundamentally limited by our ability to identify new materials and understand their electrochemical response. To shorten this time frame, we need to switch from the trial-and-error approach of finding useful materials to a more selective process by leveraging model predictions. Machine learning (ML) offers data-driven predictions and can be helpful. Herein we ask if ML can revolutionize the development cycle from decades to a few years. We outline the necessary characteristics of such ML implementations. Instead of enumerating various ML algorithms, we discuss scientific questions about the electrochemical systems to which ML can contribute.

A survey of numerical linear algebra methods utilizing mixed-precision arithmetic:

Abstract: The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of ...

Microwave and Millimeter Wave Power Beaming

Abstract: Power beaming is the efficient point-to-point transfer of electrical energy across free space by a directive electromagnetic beam. This paper clarifies the basic principles of power beaming in simple terms, and proposes a benchmarking methodology for improving the comparative assessment of power beaming systems and technology. An in-depth historical overview tracing the worldwide progress in microwave and millimeter wave (mmWave) experimental demonstrations over the past 60 years shows clear evidence of a significant increase in activity during the last 5 years. In addition, a review of progress in scalable rectenna arrays for the reception of microwave power beaming shows sufficient maturity for new research to initiate on the ruggedization, productization, and system integration aspects of the technology. A review of regulatory issues including spectrum management and safety indicates the need for additional technical solutions and international coordination. Breaking results reported in this paper include 1) data from the first in-orbit flight test of a solar-to-RF “sandwich module”, 2) the construction of multiple US in-orbit demonstrations, planned for 2023 launch, that will demonstrate key technologies for space-based solar power, and 3) a 100-kW mmWave power beaming transmitter demonstrating inherent human life safety.

Switching of metal–oxygen hybridization for selective CO2 electrohydrogenation under mild temperature and pressure

Abstract: Artificial carbon fixation contributes to closing the anthropogenic carbon cycle. However, large-scale conversion of CO2 into selective products remains a challenge. Coupled thermal–electrochemical catalysis could offer an attractive approach to upgrading CO2 into value-added products if selective electrocatalysts and integrated devices were developed. Here we identify a mechanistic route to selectively producing either CO or CH4 with high selectivity (>95%) using Ir–ceria-based catalysts in an intermediate-temperature (400 °C) CO2 electrolyser that operates at low overpotential and ambient pressure. We show that tuning of the Ir–O hybridization by controlling the Ir speciation can alter the catalyst surface chemical environment, enabling the stabilization of specific transition states for the production of either CO or CH4 during electrocatalysis. By achieving CO2 electrohydrogenation in tandem with light-alkane electrodehydrogenation, we further demonstrate that such an advanced electrolyser could be extended to the upgrade of different carbon resources in one-step, significantly enhancing the techno-economic feasibilty of the process. Coupled thermal–electrochemical catalysis offers an attractive approach to upgrading CO2 into value-added products. Now, Ir–ceria-based catalysts in a protonic ceramic CO2 electrolyser are shown to selectively produce either CO or CH4 by tuning the Ir–O orbital hybridization.

Engineering catalyst supports to stabilize PdOx two-dimensional rafts for water-tolerant methane oxidation

Abstract: The treatment of emissions from natural gas engines is an important area of research since methane is a potent greenhouse gas. The benchmark catalysts, based on Pd, still face challenges such as water poisoning and long-term stability. Here we report an approach for catalyst synthesis that relies on the trapping of metal single atoms on the support surface, in thermally stable form, to modify the nature of further deposited metal/metal oxide. By anchoring Pt ions on a catalyst support we can tailor the morphology of the deposited phase. In particular, two-dimensional (2D) rafts of PdOx are formed, resulting in higher reaction rates and improved water tolerance during methane oxidation. The results show that modifying the support by trapping single atoms could provide an important addition to the toolkit of catalyst designers for controlling the nucleation and growth of metal and metal oxide clusters in heterogeneous catalysts. Despite its importance in the context of natural gas engines emissions treatment, methane oxidation remains challenging. Now, the authors introduce an approach to stabilize PdOx rafts on ceria by trapping Pt single atoms in the support resulting in a superior catalyst for this transformation.

A comparison of the blow-out behavior of turbulent premixed ammonia/hydrogen/nitrogen-air and methane–air flames

Abstract: Ammonia has been identified as a promising energy carrier that produces zero carbon dioxide emissions when used as a fuel in gas turbines. Although the combustion properties of pure ammonia are poorly suited for firing of gas turbine combustors, blends of ammonia, hydrogen, and nitrogen can be optimized to exhibit premixed, unstretched laminar flame properties very similar to those of methane. There is limited data available on the turbulent combustion characteristics of such blends and important uncertainties exist related to their blow-out behavior. The present work reports experimental measurements of the blow-out limits in an axisymmetric unconfined bluff-body stabilized burner geometry of NH3/H2/N2-air flame, comprised of 40% NH3, 45% H2, and 15% N2 by volume in the “fuel” blend. Blow-out limits for the NH3/H2/N2-air flames are compared to those of methane–air flames. OH PLIF and OH chemiluminescence images of the flames just prior to blow-out are presented. Furthermore, two large-scale Direct Numerical Simulations (DNS) of temporally evolving turbulent premixed jet flames are performed to investigate differences in the turbulence-chemistry interaction and extinction behavior between the NH3/H2/N2-air and methane–air mixtures. The experiments reveal that the blow-out velocity of NH3/H2/N2-air flames is an order of magnitude higher than that of methane–air flames characterized by nearly identical unstretched laminar flame speed, thermal thickness and adiabatic flame temperature. Results from the DNS support the experimental observation and clearly illustrate that a methane–air mixture exhibits a stronger tendency towards extinction compared to the NH3/H2/N2-air blend for identical strain rates. Furthermore, the DNS results reveal that, even in the presence of intense sheared turbulence, fast hydrogen diffusion into the spatially distributed preheat layers of the fragmented and highly turbulent flame front plays a crucial role in the enhancement of the local heat release rate and, ultimately, in preventing the occurrence of extinction.