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DOE OSTI2021

A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes

Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. Further, we demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Profiling the Quito basin (Ecuador) using seismic ambient noise

SUMMARY Quito, the capital of Ecuador, with more than 2.5 M inhabitants, is exposed to a high seismic hazard due to its proximity to the Pacific subduction zone and active crustal faults, both capable of generating significant earthquakes. Furthermore, the city is located in an intermontane piggy-back basin prone to seismic wave amplification. To understand the basin’s seismic response and characterize its geological structure, 20 broad and medium frequency band seismic stations were deployed in Quito’s urban area between May 2016 and July 2018 that continuously recorded ambient seismic noise. We first compute horizontal-to-vertical spectral ratios to determine the resonant frequency distribution in the entire basin. Secondly, we cross-correlate seismic stations operating simultaneously to retrieve interstations surface-wave Green’s functions in the frequency range of 0.1–2 Hz. We find that Love waves travelling in the basin’s longitudinal direction (NNE–SSW) show much clearer correlograms than those from Rayleigh waves. We then compute Love wave phase-velocity dispersion curves and invert them in conjunction with the HVSR curves to obtain shear-wave velocity profiles throughout the city. The inversions highlight a clear difference in the basin’s structure between its northern and southern parts. In the centre and northern areas, the estimated basin depth and mean shear-wave velocity are about 200 m and 1800 ms−1, respectively, showing resonance frequency values between 0.6 and 0.7 Hz. On the contrary, the basement’s depth and shear-wave velocity in the southern part are about 900 m and 2500 ms−1, having a low resonance frequency value of around 0.3 Hz. This difference in structure between the centre-north and the south of the basin explains the spatial distribution of low-frequency seismic amplifications observed during the Mw 7.8 Pedernales earthquake in April 2016 in Quito.

Pacheco, D. (ORCID:0000000282355096)↗

DOE OSTI2020

Chris Freeman forging the evolution of evolutionary economics

Abstract Every Schumpeterian is an evolutionary economist in his or her own way. Chris Freeman, whose 1995 essay is published in this issue of ICC, favored a rare combination of the Cambridge tradition, a Marxian view of inequalities and Schumpeter’s fascination with innovation as the driving force of capitalism. The article summarizes and discusses this combination and how Freeman generated a challenging agenda for contemporary economics, namely in the context of long wave analysis, the theme for his last book.

Louçã, Francisco↗

DOE OSTI2022

Expanding the genetic engineering toolbox for the metabolically flexible acetogen Eubacterium limosum

Abstract Acetogenic bacteria are an increasingly popular choice for producing fuels and chemicals from single carbon (C1) substrates. Eubacterium limosum is a promising acetogen with several native advantages, including the ability to catabolize a wide repertoire of C1 feedstocks and the ability to grow well on agar plates. However, despite its promise as a strain for synthetic biology and metabolic engineering, there are insufficient engineering tools and molecular biology knowledge to leverage its native strengths for these applications. To capitalize on the natural advantages of this organism, here we extended its limited engineering toolbox. We evaluated the copy number of three common plasmid origins of replication and devised a method of controlling copy number and heterologous gene expression level by modulating antibiotic concentration. We further quantitatively assessed the strength and regulatory tightness of a panel of promoters, developing a series of well-characterized vectors for gene expression at varying levels. In addition, we developed a black/white colorimetric genetic reporter assay and leveraged the high oxygen tolerance of E. limosum to develop a simple and rapid transformation protocol that enables benchtop transformation. Finally, we developed two new antibiotic selection markers—doubling the number available for this organism. These developments will enable enhanced metabolic engineering and synthetic biology work with E. limosum.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A synthetic co-culture for bioproduction of ammonia from methane and air

Abstract Fixed nitrogen fertilizers feed 50% of the global population, but most fixed nitrogen production occurs using energy-intensive Haber–Bosch-based chemistry combining nitrogen (N2) from air with gaseous hydrogen (H2) from methane (CH4) at high temperatures and pressures in large-scale facilities sensitive to supply chain disruptions. This work demonstrates the biological transformation of atmospheric N2 into ammonia (NH3) using CH4 as the sole carbon and energy source in a single vessel at ambient pressure and temperature, representing a biological “room-pressure and room-temperature” route to NH3 that could ultimately be developed to support compact, remote, NH3 production facilities amenable to distributed biomanufacturing. The synthetic microbial co-culture of engineered methanotroph Methylomicrobium buryatense (now Methylotuvimicrobium buryatense) and diazotroph Azotobacter vinelandii converted three CH4 molecules to l-lactate (C3H6O3) and powered gaseous N2 conversion to NH3. The design used division of labor and mutualistic metabolism strategies to address the oxygen sensitivity of nitrogenase and maximize CH4 oxidation efficiency. Media pH and salinity were central variables supporting co-cultivation. Carbon concentration heavily influenced NH3 production. Smaller-scale NH3 production near dispersed, abundant, and renewable CH4 sources could reduce disruption risks and capitalize on untapped energy resources. One-Sentence Summary Co-culture of engineered microorganisms Methylomicrobium buryatense and Azotobacter vinelandii facilitated the use of methane gas as a sole carbon feedstock to produce ammonia in an ambient temperature, atmospheric pressure, single-vessel system.

Biotechnology & Applied Microbiology↗

DOE OSTI2022

Reimagine fire science for the anthropocene

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the “firehose” of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Biomechanical drivers of the evolution of butterflies and moths with a coilable proboscis

Current biomechanical models suggest that butterflies and moths use their proboscis as a drinking straw pulling nectar as a continuous liquid column. Our analyses revealed an alternative mode for fluid uptake: drinking bubble trains that help defeat drag. We combined X-ray phase-contrast imaging, optical video microscopy, micro-computed tomography, phylogenetic models of evolution and fluid mechanics models of bubble-train formation to understand the biomechanics of butterfly and moth feeding. Our models suggest that the bubble-train mechanism appeared in the early evolution of butterflies and moths with a proboscis long enough to coil. We propose that, in addition to the ability to drink a continuous column of fluid from pools, the ability to exploit fluid films by capitalizing on bubble trains would have expanded the range of available food sources, facilitating diversification of Lepidoptera.

Palaoro, Alexandre V.↗

DOE OSTI2021

One-directional polarization transport in electron/nuclear spin chains with loss and gain

Understanding the joint dynamics of electron and nuclear spins is central to core concepts in solid-state magnetic resonance such as spin-lattice relaxation and dynamic nuclear polarization, but a generalization that capitalizes on competing polarization loss and gain channels is still lacking. Here, we study theoretically the non-Hermitian dynamics of hybrid electron/nuclear spin systems in the simultaneous presence of electron spin pumping and spin-lattice relaxation. Focusing on periodic, one-dimensional chains, we find that, by adjusting the electron spin pumping to a critical level, it is possible to steer the flow of nuclear polarization to create site-dependent distributions where either end of the array polarizes in opposite ways, irrespective of the initial state. By contrast, we show that ring-like patterns—where the limit nuclear polarization is uniform—exhibit a non-decaying, externally driven nuclear spin current. Interestingly, cyclic magnetic field modulation can render these processes largely robust to defects in the chain, a response featuring some interesting similarities—and differences—with recent findings in other non-Hermitian physical platforms.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Noncollinear ground states of solids with a source-free exchange correlation functional

In this paper, we expand upon the source-free (SF) exchange correlation (XC) functional developed by Sangeeta Sharma and coworkers to plane-wave density functional theory (DFT) based on the projector augmented wave (PAW) method. This constraint is implemented by the current authors within the VASP source code, using a fast Poisson solver that capitalizes on the parallel three-dimensional fast Fourier transforms (FFTs) implemented in VASP. Using this modified XC functional, we explore the improved convergence behavior that results from applying this constraint to the GGA-PBE+U+J functional. In the process, we compare the noncollinear magnetic ground state computed by each functional and their SF counterpart for a select number of magnetic materials in order to provide a metric for comparing with experimentally determined magnetic orderings. We observe significantly improved agreement with experimentally measured magnetic ground-state structures after applying the source-free constraint. Furthermore, we explore the importance of considering probability current densities in spin-polarized systems, even under no applied field. We analyze the XC torque as well, in order to provide theoretical and computational analyses of the net XC magnetic torque induced by the source-free constraint. Along these lines, we highlight the importance of properly considering the real-space integral of the source-free local magnetic XC field. Our analyses on probability currents, net torque, and constant terms draw additional links to the rich body of previous research on spin-current density functional theory (SCDFT), and pave the way for future extensions and corrections to the SF corrected XC functional.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Quantifying modeling uncertainties when combining multiple gravitational-wave detections from binary neutron star sources

Here, with the increasing sensitivity of gravitational-wave detectors, we expect to observe multiple binary neutron-star systems through gravitational waves in the near future. The combined analysis of these gravitational-wave signals offers the possibility to constrain the neutron-star radius and the equation of state of dense nuclear matter with unprecedented accuracy. However, it is crucial to ensure that uncertainties inherent in the gravitational-wave models will not lead to systematic biases when information from multiple detections is combined. To quantify waveform systematics, we perform an extensive simulation campaign of binary neutron-star sources and analyze them with a set of four different waveform models. For our analysis with 38 simulations, we find that statistical uncertainties in the neutron-star radius decrease to ± 250 m (2% at 90% credible interval) but that systematic differences between currently employed waveform models can be twice as large. Hence, it will be essential to ensure that systematic biases will not become dominant in inferences of the neutron-star equation of state when capitalizing on future developments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Highly excited electron cyclotron for QCD axion and dark-photon detection

We propose using highly excited cyclotron states of a trapped electron to detect meV axion and dark-photon dark matter, marking a significant improvement over our previous proposal and demonstration [One-electron quantum cyclotron as a milli-ev dark-photon detector, .]. When the axion mass matches the cyclotron frequency ω c , the cyclotron state is resonantly excited, with a transition probability proportional to its initial quantum number, n c . The sensitivity is enhanced by taking n c ∼ 10 6 ( 0.1 meV ω c ) 2 . By optimizing key experimental parameters, we minimize the required averaging time for cyclotron detection to t ave ∼ 10 − 6 s, permitting detection of such a highly excited state before its decay. An open–end-cap trap design enables the external photon signal to be directed into the trap, rendering our background-free detector compatible with large focusing cavities, such as the BREAD proposal, while capitalizing on their strong magnetic fields. Furthermore, the axion conversion rate can be coherently enhanced by incorporating layers of dielectrics with alternating refractive indices within the cavity. Collectively, these optimizations enable us to probe the QCD axion parameter space from 0.1 to 2.3 meV (25–560 GHz), covering a substantial portion of the predicted postinflationary QCD axion mass range. This sensitivity corresponds to probing the kinetic mixing parameter of the dark photon down to ε ≈ 2 × 10 − 16 . Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

OmniFold: A Method to Simultaneously Unfold All Observables

Collider data must be corrected for detector effects (“unfolded”) to be compared with many theoretical calculations and measurements from other experiments. Unfolding is traditionally done for individual, binned observables without including all information relevant for characterizing the detector response. We introduce OmniFold, an unfolding method that iteratively reweights a simulated dataset, using machine learning to capitalize on all available information. Our approach is unbinned, works for arbitrarily high-dimensional data, and naturally incorporates information from the full phase space. We illustrate this technique on a realistic jet substructure example from the Large Hadron Collider and compare it to standard binned unfolding methods. This new paradigm enables the simultaneous measurement of all observables, including those not yet invented at the time of the analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Coherent Transfer of Lattice Entropy via Extreme Nonlinear Phononics in Metal Halide Perovskites

Entropy transfer in metal halide perovskites, characterized by significant lattice anharmonicity and low stiffness, underlies the remarkable properties observed in their optoelectronic applications, ranging from solar cells to lasers. The conventional view of this transfer involves stochastic processes occurring within a thermal bath of phonons, where the lattice arrangement and energy flow from higher- to lower-frequency modes. Here, we unveil a comprehensive chronological sequence detailing a conceptually distinct coherent transfer of entropy in a prototypical perovskite CH 3 NH 3 Pbl 3 . The terahertz periodic modulation imposes vibrational coherence into electronic states, leading to the emergence of mixed (vibronic) quantum beat between approximately 3 and 0.3 THz. We highlight a well-structured bidirectional time-frequency transfer of these diverse phonon modes, each developing at different times and transitioning from high to low frequencies from 3 to 0.3 THz, before reversing direction and ascending to around 0.8 THz. First-principles molecular dynamics simulations disentangle a complex web of coherent-phononic coupling pathways and identify the salient roles of the initial modes in shaping entropy evolution at later stages. Capitalizing on coherent entropy transfer and dynamic anharmonicity presents a compelling opportunity to exceed the fundamental thermodynamic (Shockley-Queisser) limit of photoconversion efficiency and to pioneer novel optoelectronic functionalities. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Pathways and Insights from Community Solar: A Guide to Community Energy Storage Success

Community energy assets bring the benefits of renewables to all energy system stakeholders, not just those with sufficient capital, land ownership, and resources. As the price of energy storage continues to decline and energy equity and justice principles are incorporated into policies and planning activities, Community Energy Storage (CES) is poised to follow in the footsteps of Community Solar’s (CS) success. Though CES is in its early stages and faces many unique challenges, it is an invaluable tool on the pathway to decarbonization, with the potential to increase renewable access, energy affordability, resilience, energy independence, wealth creation, and community empowerment. This paper provides a brief review of the history of CS, comparing the market and regulatory advances of CS to the current state of CES. The lessons learned from the rise of CS are then adapted to support those working to increase CES adoption in pursuit of a more equitable and sustainable energy system for all.

community energy planning, community solar, commun↗

DOE OSTI2024

Calculating Behind-the-Meter Energy Storage Incentives on an Avoided Cost Basis

Behind-the-meter (BTM) energy storage offers the potential for shared investment by utilities and their customers, in which both parties share in the costs and benefits of battery investment. Several utilities and a handful of states have begun providing incentives to help customers purchase BTM energy storage, and in exchange, operate that battery on behalf of the customer to realize grid benefits such as meeting peak capacity needs. But there is wide variation in the value and structure of these incentives, suggesting a lack of clarity on the value of BTM storage to the grid and to non-participating customers who fund the incentives for participating customers. This paper provides an objective framework for establishing BTM energy storage incentives based on the avoided cost of generation from a marginal, gas-fired peaking plant. It also conducts several sensitivity analyses to see how those avoided costs vary with emissions pricing, gas prices, plant heat rates, and utility capital structures. This work may be of use to utilities, regulators, and energy system stakeholders in providing a value-based framework for BTM incentive programs that can be used in the absence of policy guidance.

Twitchell, Jeremy B.↗

DOE OSTI2024

Using Mobile Charging Drones to Mitigate Battery Disruptions of Electric Vehicles on Highways

Our research explores innovative solutions to address the challenge of battery disruptions in electric vehicles (EVs) on highways. We propose a centralized fleet ownership model where a company manages a fleet of Mobile Charging Drones (MCDs) guided by a k-VRP (Vehicle Routing Problem) framework. This model is designed to tackle a multi-objective optimization issue with three primary goals: reduction of the overall operating costs, decrease in the cumulative waiting time, and minimization of the combined operating costs and waiting times. This approach extends beyond the usual VRP constraints, encompassing specific limitations for both MCDs and disrupted EVs (DEVs). Additionally, our study delves into the concept of decentralized fleet ownership through the lens of crowdsourcing. Preliminary numerical analyses indicate that the capital cost of MCDs is a significant factor on the charging service, and the system performance is sensitive to DEV owner's value of time (VOT) when VOTs are relatively low.

battery disruption↗

DOE OSTI2023

Disruptive Photovoltaic Technologies Can Accelerate Global Decarbonization

This contribution explores PV manufacturing capacity expansion trajectories needed to achieve the goal of global decarbonization assuming that investors make financially rational decisions avoiding stranded production assets while still effectively exploiting experience curve benefits in both manufacturing process and product design. Substantial production cost savings and timely decarbonization risk mitigation could accrue by adoption and scaling of high efficiency multijunction device architectures and thin film direct bandgap semiconductor technologies that provide lower manufacturing capital intensity. We demonstrate that there is a $1-2 trillion market opportunity for such disruptive technologies while also providing hundreds of billions of dollars of cost savings to reach total decarbonization.

decarbonization↗

DOE OSTI2020

Selective Sampling for Sensor Type Classification in Buildings

A key barrier to applying any smart technology to a building is the requirement of locating and connecting to the necessary resources among the thousands of sensing and control points, i.e., the metadata mapping problem. Existing solutions depend on exhaustive manual annotation of sensor metadata --- a laborious, costly, and hardly scalable process. To reduce the amount of manual effort required, this paper presents a multi-oracle selective sampling framework to leverage noisy labels from information sources with unknown reliability such as existing buildings, which we refer to as weak oracles, for metadata mapping. This framework involves an interactive process, where a small set of sensor instances are progressively selected and labeled for it to learn how to aggregate the noisy labels as well as to predict sensor types. Two key challenges arise in designing the framework, namely, weak oracle reliability estimation and instance selection for querying. To address the first challenge, we develop a clustering-based approach for weak oracle reliability estimation to capitalize on the observation that weak oracles perform differently in different groups of instances. For the second challenge, we propose a disagreement-based query selection strategy to combine the potential effect of a labeled instance on both reducing classifier uncertainty and improving the quality of label aggregation. We evaluate our solution on a large collection of real-world building sensor data from 5 buildings with more than 11,000 sensors of 18 different types. The experiment results validate the effectiveness of our solution, which outperforms a set of state-of-the-art baselines.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗