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DOE OSTI2016

(Invited) Comprehensive Assessment of Oxide Memristors As Post-CMOS Memory and Logic Devices

As CMOS technology approaches the end of its scaling, oxide-based memristors have become one of the leading candidates for post-CMOS memory and logic devices. In orderTo facilitate the understanding of physical switching mechanisms and accelerate experimental development of memristors, we have developed a three-dimensional fully-coupled electrical and thermal transport model, which captures all the important processes that drive memristive switching and is applicable for simulating a wide range of memristors. Moreover, the model is applied to simulate the RESET and SET switching in a 3D filamentary TaOx memristor. Extensive simulations show that the switching dynamics of the bipolar device is determined by thermally-activated field-dominant processes: with Joule heating, the raised temperature enables the movement of oxygen vacancies, and the field drift dominates the overall motion of vacancies. Simulated current-voltage hysteresis and device resistance profiles as a function of time and voltage during RESET and SET switching show good agreement with experimental measurement.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Evaluating the Impact of Residential Solar Contract Cancellations in the United States

The residential solar photovoltaic (PV) market in the United States is growing, despite frequent customer cancellations. Contract cancellations result in lost time and costs that must be borne by installers, often in the form of higher "soft costs" (i.e., non-equipment costs). These costs are often passed on to customers who successfully install PV systems. To date, few studies have attempted to estimate national cancellation rates or model the impacts on installed system costs. In this report, we utilize an installer-provided dataset of 199,665 residential PV-only projects representing about 10% of U.S. installs each year from 2017-2019. With this data, we evaluate cancellation rates and trends from contract signing to install. Next, by leveraging NREL's soft cost model for residential solar, we estimate installer spending through each phase of the pre-install process. Applying our findings on cancellation timelines and rates, we then estimate the potential cost impacts to successful installs from contract cancellations. Our work suggests that the rates and impacts of contract cancellations have been previously underestimated. Namely, we find that cancellations/unsuccessful project are; more common than previous estimates suggest; occur earlier in project timelines, though a significant number happen even after permit/ATB approvals; and contribute significantly to customer acquisition and other soft costs. We also find that cancellation do not appear to be driven by review delays in permitting and interconnection applications.

14 SOLAR ENERGY↗

DOE OSTI2024

A Methodology for Simulating Supercritical CO2 Heat Transfer Experiments Using Machine Learning Models

To support the growth of supercritical carbon dioxide (sCO2) power cycles in the energy industry, this study seeks to train a machine learning model to mirror experimental data to predict new heat transfer data. To do this experimental data was amassed, one preliminary set comprised of 16 test results, and an expanded version comprised of 38 test results. With the goal of predicting experimental apparatus temperatures and pressures, several iterations of models were tested investigating the impact of model hyper-parameters, data inclusion, and data pre-processing on model performance. A total of 15 variations cumulatively of Gaussian Process Regressors, Gradient Boosting Regressors, and Multi-Layer Perceptrons were trained and validated on the preliminary set, and the best algorithm of each class was re-trained on the expanded set. These were compared based on test/train R^2 , test/train mean absolute error (MAE), and validation MAE, to identify the successfulness of these models. It was shown temperatures could be predicted within just a few degrees, showing the potential of this approach. Future research has been identified with approaches to improve pressure and temperature predictions going forward.

Grabowski, Owen↗

DOE OSTI2021

SMART Perovskite Growth: Enabling a Larger Range of Process Conditions

Cost-effective, high-throughput industrial applications of metal-halide perovskites require a highly tolerant method (i.e., wide process window) that produces high-quality materials with a short annealing time. Here, we introduce a Seed Modulation for ARTificially controlled nucleation (SMART) process that enables rapid fabrication of high-quality perovskite films under a wide set of initial input parameters. Additionally, we characterized the thin-film evolution from the perspective of crystallinity, surface potential, diffusivity, surface carrier dynamics, and interfacial recombination. We find that surface and subsurface defects primarily determine the performance of materials and devices. By modulating the seeds for perovskite nucleation, we were able to improve the overall crystallization. We achieved a >20% power conversion efficiency using only a 5 min annealing step, and we found that the annealing window is widened such that differing initial conditions achieve similar quality. Furthermore, we demonstrated reproducibility and performance improvement in larger-area perovskite cells by incorporating the SMART process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Interference effects in the high-order harmonic amplification process in the active medium of a plasma-based X-ray laser modulated by an optical field

We study the process of propagation of high harmonics of optical radiation in an active medium of a plasma-based X-ray laser, simultaneously irradiated by an intense optical field of fundamental frequency. It is shown that for moderate plasma dispersion of the active medium at the frequency of the modulating optical field, the energy and relative amplitudes of the harmonics at the output of the medium are determined by their phases at the entrance to the medium, as well as by the time-delay of the harmonics with respect to the modulating field. These dependences are due to interference of high-order harmonics with a set of multi-frequency fields generated by each of the harmonics in the process of coherent scattering in a modulated active medium. The possibilities of using these effects to increase the efficiency of harmonic amplification, to control the harmonic spectrum, and determine the relative phases at the entrance to the medium are discussed on the example of the active medium of hydrogen-like Li{sup 2+} ions (with a 13.5 nm wavelength of an inverted transition). (paper)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

French Atomic and alternative energies commission decommissioning policy and strategies: What is at stake lessons learned and feedback experience - 15013

Since its creation in 1945, the French Atomic Energy and Alternative Energies Commission has carried out research programmes on civil use of nuclear, and its application. CEA has set up and run various types of installations from research (accelerators, pond reactors, fast reactors, laboratories) to industry (power reactor, processing facilities). There are currently more than several tens of facilities which are presently closed down pending dismantling or in the process of being dismantled by CEA, the governmental body for research and development in nuclear and renewable energies. When operating, all these installations have generated radioactive waste. When they are shutdown, either as a result of the programmes for which they were set up, or due to equipment wearing out or being obsolete, these installations must be cleaned up, dismantled and decommissioned, taking into account their nuclear nature and requirements related to safety and environment. During the decommissioning process, the implementer has to deal with safety and site remediation issues. Dealing with these installations is a long-term programme which must be carefully planned and financed in order to optimise its management. The paper will describe the CEA's decommissioning policy, strategies adopted, and draw up lessons learned and feedback experience, showing that: - Safety is guaranteed, - Dismantling is a technically controllable operation, but R and D actions are to be developed for specific problems as characterization or operation in hostile environment. Moreover all the methods and techniques improve as a result of feedback experience, - The amount of material and waste produced by the dismantling are manageable. The very low, low and intermediate level waste can be stored on existing shallow land burial centres, some new repositories have to be created for specific waste (graphite, radium,...) and for high and intermediate level long live waste, which are stored in interim storage , - The dismantling must be optimized, especially by appliance of a good strategy based on rational industrial choices. - Communication and transparency with stakeholders is essential for global process acceptance, - The lessons learned and how feedback experience could benefit for future decommissioning projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2014

Fundamental Aspects of Selective Melting Additive Manufacturing Processes

Certain details of the additive manufacturing process known as selective laser melting (SLM) affect the performance of the final metal part. To unleash the full potential of SLM it is crucial that the process engineer in the field receives guidance about how to select values for a multitude of process variables employed in the building process. These include, for example, the type of powder (e.g., size distribution, shape, type of alloy), orientation of the build axis, the beam scan rate, the beam power density, the scan pattern and scan rate. The science-based selection of these settings con- stitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy, reactive, dynamic wetting followed by re-solidification. In addition, inherent to the process is its considerable variability that stems from the powder packing. Each time a limited number of powder particles are placed, the stacking is intrinsically different from the previous, possessing a different geometry, and having a different set of contact areas with the surrounding particles. As a result, even if all other process parameters (scan rate, etc) are exactly the same, the shape and contact geometry and area of the final melt pool will be unique to that particular configuration. This report identifies the most important issues facing SLM, discusses the fundamental physics associated with it and points out how modeling can support the additive manufacturing efforts.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Network Reconfiguration for Enhanced Operational Resilience Using Reinforcement Learning

This paper proposes a reinforcement learning-based approach for distribution network reconfiguration(DNR) to enhance the resilience of the electric power supply. Resilience enhancements usually require solving large-scale stochastic optimization problems that are computationally expensive and sometimes infeasible. The exceptional performance of reinforcement learning techniques has encouraged their adoption in various power system control studies, specifically resilience-based real-time applications. In this paper, a single agent framework is developed using an Actor-Critic algorithm (ACA) to determine statuses of tie-switches in a distribution feeder impacted by an extreme weather event. The proposed approach provides a fast-acting control algorithm that reconfigures the feeder topology to reduce or even avoid load shedding. The problem is formulated as a discrete Markov decision process in such a way that a system state captures the system topology and its operational characteristics. An action is made to open or close a specific set of tie-switches after which a reward is calculated to evaluate the practicality and advantage of that action. The iterative Markov process is used to train the proposed ACA under diverse failure scenarios and is demonstrated on the 33-node distribution feeder system. Results show the capability of the proposed ACA to determine proper switching action of tie-switches with accuracy exceeding 93%.

actor critic↗

DOE OSTI2021

How AI Predicts the Untrained and Unseen

Focus Area: Model predictability improvements (Primary); Data optimization (secondary); Data complexity insights (secondary). The Scientific Challenge: If we believe that a future under extreme conditions will look very differently from today, we can likely agree that ML/AI models trained on past and present datasets will not be adequate to make reliable predictions into the future. This is true for water cycling, as well as biogeochemistry and other Earth system components and behaviors. Additionally, ML/AI models are inherently non-physical. Despite the flourishing success of ML/AI in many applications, such as computer vision, natural language process, and gaming, even the most sophisticated AI models don’t understand the very basic physical laws. Therefore, a natural question is: Can we trust ML/AI based predictions of Earth system behaviors that are fundamentally driven by physical laws? So, are physics models with meticulous process representation a better choice? Not exactly. Physical models, when firmly rooted in first principles, work great at predicting behaviors of systems with a well-defined set of boundary conditions and variables. However, as a complex system, the number of parameters and the degree of complexity and dynamics in processes, coupling, and scale dependent emergent behaviors make the Earth system behaviors very challenging to predict with physical models composed of deterministic laws. In addition, due to the lack of fundamental understandings, physical models often implement empirical correlations derived from observations with biases from locality of data generation. Because correlation is not necessarily causation or comply with first principles, scaling of model predictions beyond locality is often invalid. Beyond the limitation of models, physics or AI, our knowledge of the Earth system is limited by the lack of observational technologies and resources. Insufficient data density, dimensionality and diversity only offer a sliced (or projected) view of the Earth system, e.g. Plato’s Cave analogy, limiting our capability to better understand and represent fundamental processes in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Hardware-Conscious Optimization of the Quantum Toffoli Gate

While quantum computing holds great potential in combinatorial optimization, electronic structure calculation, and number theory, the current era of quantum computing is limited by noisy hardware. Many quantum compilation approaches can mitigate the effects of imperfect hardware by optimizing quantum circuits for objectives such as critical path length. Few approaches consider quantum circuits in terms of the set of vendor-calibrated operations (i.e., native gates) available on target hardware. This manuscript expands the analytical and numerical approaches for optimizing quantum circuits at this abstraction level. We present a procedure for combining the strengths of analytical native gate-level optimization with numerical optimization. Although we focus on optimizing Toffoli gates on the IBMQ native gate set, the methods presented are generalizable to any gate and superconducting qubit architecture. Our optimized Toffoli gate implementation demonstrates an 18% reduction in infidelity compared with the canonical implementation as benchmarked on IBM Jakarta with quantum process tomography. Assuming the inclusion of multi-qubit cross-resonance (MCR) gates in the IBMQ native gate set, we produce Toffoli implementations with only six multi-qubit gates, a 25% reduction from the canonical eight multi-qubit implementations for linearly connected qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Ant‐mediated ecosystem functions on a warmer planet: effects on soil movement, decomposition and nutrient cycling

Summary Direct and indirect consequences of global warming on ecosystem functions and processes mediated by invertebrates remain understudied but are likely to have major impacts on ecosystems in the future. Among animals, invertebrates are taxonomically diverse, responsive to temperature changes, and play major ecological roles which also respond to temperature changes. We used a mesocosm experiment to evaluate impacts of two warming treatments (+3·5 and +5 °C, set‐points) and the presence and absence of the ant Formica subsericea (a major mediator of processes in north temperate ecosystems) on decomposition rate, soil movement, soil respiration and nitrogen availability. Replicate 19‐L mesocosms were placed outdoors in lathe houses and continuously warmed for 30 days in 2011 and 85 days in 2012. Warming treatments mimicked expected temperature increases for future climates in eastern North America. In both years, the amount of soil displaced and soil respiration increased in the warming and ant presence treatments (soil movement: 73–119%; soil respiration: 37–48% relative to the control treatments without ants). Decomposition rate and nitrogen availability tended to decrease in the warmest treatments (decomposition rate: −26 to −30%; nitrate availability: −11 to −42%). Path analyses indicated that ants had significant short‐term direct and indirect effects on the studied ecosystem processes. These results suggest that ants may be moving more soil and building deeper nests to escape increasing temperatures, but warming may also influence their direct and indirect effects on soil ecosystem processes.

Del Toro, Israel↗

DOE OSTI2015

Comprehensive, Multi-Source Cyber-Security Events Data Set

This data set represents 58 consecutive days of de-identified event data collected from five sources within Los Alamos National Laboratory’s corporate, internal computer network. The data sources include Windows-based authentication events from both individual computers and centralized Active Directory domain controller servers; process start and stop events from individual Windows computers; Domain Name Service (DNS) lookups as collected on internal DNS servers; network flow data as collected on at several key router locations; and a set of well-defined red teaming events that present bad behavior within the 58 days. In total, the data set is approximately 12 gigabytes compressed across the five data elements and presents 1,648,275,307 events in total for 12,425 users, 17,684 computers, and 62,974 processes. Specific users that are well known system related (SYSTEM, Local Service) were not de-identified though any well-known administrators account were still de-identified. In the network flow data, well-known ports (e.g. 80, 443, etc) were not de-identified. All other users, computers, process, ports, times, and other details were de-identified as a unified set across all the data elements (e.g. U1 is the same U1 in all of the data). The specific timeframe used is not disclosed for security purposes. In addition, no data that allows association outside of LANL’s network is included. All data starts with a time epoch of 1 using a time resolution of 1 second. In the authentication data, failed authentication events are only included for users that had a successful authentication event somewhere within the data set.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Gamma Spectroscopy Detector Candidates and Radioisotope Identification Algorithms for Use in National Security Applications

In 2006, the United States Congress mandated for the Department of Homeland Security (DHS) to screen all cargo containers to protect against terrorist acts and ensure the safety and security of the nation. Containers are screened by gamma and neutron detectors to ensure threat material is not smuggled into the country. However, because commerce is radioactive, detecting the presence of radioactive materials is not sufficient in ensuring the safety and security of the nation. Radioactive materials must also be identified in real time, thus distinguishing threat sources (Uranium-235 and Plutonium-230) from non-threat sources (kitty litter, pot ash, medical isotopes). Screening cargo containers can be considered a two-step process (1) alerting to the presence of radioactive material when gamma counts exceed a threshold setting, and (2) once alerted, identifying the type of radioactive material, which is done by collecting a gamma spectra and analyzing it with an analysis tool/algorithm. For this reason, it is important to evaluate not only emerging technology in neutron and gamma detection, but also investigate new advances in algorithm development for radioisotope identification (RIID). New candidates in detection and on-board algorithm analysis might offer opportunities to make the scanning, detection, and identification process more efficient while still ensuring the health and safety of the public. This research will investigate emerging technology in radiation detection focused on gamma spectroscopy capabilities and RIID algorithms for DHS applications.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

Abstract Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide ( CO 2 ) concentration data at the global scale. However, high‐precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site‐level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process‐based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 to 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO 2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C·yr −1 and 0.08 Pg C·yr −1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. This study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Automatic Attribute Profiles

Morphological attribute profiles are multilevel decompositions of images obtained with a sequence of transformations performed by connected operators. They have been extensively employed in performing multi-scale and region-based analysis in a large number of applications. One main, still unresolved, issue is the selection of filter parameters able to provide representative and non-redundant threshold decomposition of the image. This paper presents a framework for the automatic selection of filter thresholds based on Granulometric Characteristic Functions (GCFs). GCFs describe the way that non-linear morphological filters simplify a scene according to a given measure. Since attribute filters rely on a hierarchical representation of an image (e.g., the Tree of Shapes) for their implementation, GCFs can be efficiently computed by taking advantage of the tree representation. Eventually, the study of the GCFs allows the identification of a meaningful set of thresholds. Therefore, a trial and error approach is not necessary for the threshold selection, automating the process and in turn decreasing the computational time. It is shown that the redundant information is reduced within the resulting profiles (a problem of high occurrence, as regards manual selection). The proposed approach is tested on two real remote sensing data sets, and the classification results are compared with strategies present in the literature.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Search for flavour-changing neutral $tqH$ interactions with $H$ → γγ in $pp$ collisions at $ \sqrt{s} $ = 13 TeV using the ATLAS detector

A search for flavour-changing neutral interactions involving the top quark, the Higgs boson and an up-type quark q (q = c, u) is presented. The proton-proton collision data set used, with an integrated luminosity of 139 fb –1 , was collected at $\sqrt{s}$ = 13 TeV by the ATLAS experiment at the Large Hadron Collider. Both the decay process t → qH in $t\bar{t}$ production and the production process pp → tH, with the Higgs boson decaying into two photons, are investigated. No significant excess is observed and upper limits are set on the t → cH and the t → uH branching ratios of 4.3 × 10 –4 and 3.8 × 10 –4 , respectively, at the 95% confidence level, while the expected limits in the absence of signal are 4.7 × 10 –4 and 3.9 × 10 –4 . Combining this search with ATLAS searches in the H → τ + τ – and H → $b\bar{b}$ final states yields observed (expected) upper limits on the t → cH branching ratio of 5.8 × 10 –4 (3.0 × 10 –4 ) at the 95% confidence level. The corresponding observed (expected) upper limit on the t → uH branching ratio is 4.0 × 10 –4 (2.4 × 10 –4 ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Uncovering novel liquid organic hydrogen carriers: a systematic exploration of chemical compound space using cheminformatics and quantum chemical methods

We present a comprehensive, in silico-based discovery approach to identifying novel liquid organic hydrogen carrier (LOHC) candidates using cheminformatics methods and quantum chemical calculations. We screened over 160 billion molecules from ZINC15 and GDB-17 chemical databases for structural similarity to known LOHCs and employed a data-driven selection criterion connecting molecular features with dehydrogenation enthalpy. This scoring criterion effectively predicts dehydrogenation enthalpies from SMILES strings, streamlining the LOHC screening process. After rigorous screening and down-selection, we compiled a database of 3000 dehydrogenation reactions for the most promising LOHC candidates, setting the stage for future selection based on kinetics and catalysis. This work demonstrates the significant impact of integrating quantum chemistry and cheminformatics in materials discovery, accelerating the selection process while reducing experimental efforts and time. By proposing new molecules as prospective LOHC candidates, our study provides a valuable resource for researchers and engineers in the development of advanced LOHC systems and showcases a successful approach for high-throughput discovery, contributing to more efficient and sustainable energy storage solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

PNNL Review of Federal and State Agency Regulatory Streamlining Practices

All major federal actions that have the potential to significantly affect the environment (e.g., land purchases and/or issuing grants, permits, leases, or licenses) are subject to multiple statutes including the following: • an environmental analysis under the National Environmental Policy Act (NEPA) • potential consultations with the U.S. Fish and Wildlife Service (USFWS) and/or National Marine Fisheries Service (NMFS) under the Endangered Species Act of 1973, as amended (ESA) • potential consultations with State Historical Preservation Officers (SHPOs) and/or tribal nations [often Tribal Historic Preservation Officers (THPOs)] under the National Historic Preservation Act of 1966 (NHPA). Given the size of the federal government and the corresponding variability and complexity in its missions, different branches within the federal government have a fairly wide range of approaches to fulfill their NEPA and consultation requitements. Many of these approaches are founded on the desire to streamline their NEPA and consultation processes while meeting the spirit and letter of the regulations. Some federal and state environmental/engineering agencies have developed web-based dashboards that provide a single web location for permit application submittals. They also use general permits in their various permitting processes. General permits can streamline the permitting process by establishing identical requirements for all eligible applicants. This reduces the time these agencies need to spend reviewing individual permits and setting specific requirements. In addition, general permits do not require a case-specific permit application. This paper presents a sampling of effective agency examples of streamlining the NEPA process and associated agency consultations. It also includes several examples of federal and state agency web portals, online application systems, and general permits that make application processes more efficient and accessible.

54 ENVIRONMENTAL SCIENCES↗