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NASA NTRS2004

Toward a Systematic Approach for Selection of NASA Technology Portfolios

There is an important need for a consistent analytical foundation supporting the selection and monitoring of R&D tasks that support new system concepts that enable future NASA missions. This capability should be applicable at various degrees of abstraction, depending upon whether one is interested in formulation, development, or operations. It should also be applicable to a single project, a program comprised of a group of projects, an enterprise typically including multiple programs, and the overall agency itself. Emphasis here is on technology selection and new initiatives, but the same approach can be generalized to other applications, dealing, for example, with new system architectures, risk reduction, and task allocation among humans and machines. The purpose of this paper is to describe one such approach, which is in its early stages of implementation within NASA programs, and to discuss several illustrative examples.

return on investment↗

DOE OSTI2024

Elucidating the complex interplay between thermodynamics, kinetics, and electrochemistry in battery electrodes through phase-field modeling

Abstract This article highlights applications of phase-field modeling to electrochemical systems, with a focus on battery electrodes. We first provide an overview on the physical processes involved in electrochemical systems and applications of the phase-field approach to understand the thermodynamic and kinetic mechanisms underlying these processes. We employ two examples to highlight how realistic thermodynamics and kinetics can naturally be incorporated into phase-field modeling of electrochemical processes. One is a composite battery cathode with an intercalation compound (Li x FePO 4 ) as the electrochemically active material, and the other is a displacement reaction compound (Li–Cu–TiS 2 ). With the input parameters mostly from atomistic calculations and experimental measurements, phase-field simulations allowed us to untangle the interactions among transport, reaction, electricity, chemistry, and thermodynamics that lead to highly complex evolution of the materials within battery electrodes. The implications of these observations for battery performance and degradation are discussed. Graphical abstract

Andrews, W. Beck (ORCID:0000000287824621)↗

DOE OSTI2023

The 1996 Mid-Atlantic Winter Flood: Exploring Climate Risk through a Storyline Approach

Abstract This article explores the application of thermodynamic perturbations to a historical midlatitude, wintertime, rain-on-snow flood event to evaluate how similar events may evolve under different climate forcings. In particular, we generate a hindcast of the 1996 Mid-Atlantic flood using an ensemble of 14-km variable-resolution simulations completed with the U.S. Department of Energy’s global Energy Exascale Earth System Model (E3SM). We show that the event is skillfully reproduced over the Susquehanna River Basin (SRB) by E3SM when benchmarked against in situ observational data and high-resolution reanalyses. In addition, we perform five counterfactual experiments to simulate the flood under preindustrial conditions and four different levels of warming as projected by the Community Earth System Model Large Ensemble. We find a nonlinear response in simulated surface runoff and streamflow as a function of atmospheric warming. This is attributed to changing contributions of liquid water input from a shallower initial snowpack (decreased snowmelt), increased surface temperatures and rainfall rates, and increased soil water storage. Flooding associated with this event peaks from around +1 to +2 K of global average surface warming and decreases with additional warming beyond this. There are noticeable timing shifts in peak runoff and streamflow associated with changes in the flashiness of the event. This work highlights the utility of using storyline approaches for communicating climate risk and demonstrates the potential nonlinearities associated with hydrologic extremes in areas that experience ephemeral snowpack, such as the SRB.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Abstraction hierarchy to define biofoundry workflows and operations for interoperable synthetic biology research and applications

Lack of standardization in biofoundries limits the scalability and efficiency of synthetic biology research. Here, we propose an abstraction hierarchy that organizes biofoundry activities into four interoperable levels: Project, Service/Capability, Workflow, and Unit Operation, effectively streamlining the Design‑Build‑Test‑Learn (DBTL) cycle. This framework enables more modular, flexible, and automated experimental workflows. It improves communication between researchers and systems, supports reproducibility, and facilitates better integration of software tools and artificial intelligence. Our approach lays the foundation for a globally interoperable biofoundry network, advancing collaborative synthetic biology and accelerating innovation in response to scientific and societal challenges.

Kim, Haseong↗

DOE OSTI2023

Prospects and applications of on-chip lasers

Abstract Integrated silicon photonics has sparked a significant ramp-up of investment in both academia and industry as a scalable, power-efficient, and eco-friendly solution. At the heart of this platform is the light source, which in itself, has been the focus of research and development extensively. This paper sheds light and conveys our perspective on the current state-of-the-art in different aspects of application-driven on-chip silicon lasers. We tackle this from two perspectives: device-level and system-wide points of view. In the former, the different routes taken in integrating on-chip lasers are explored from different material systems to the chosen integration methodologies. Then, the discussion focus is shifted towards system-wide applications that show great prospects in incorporating photonic integrated circuits (PIC) with on-chip lasers and active devices, namely, optical communications and interconnects, optical phased array-based LiDAR, sensors for chemical and biological analysis, integrated quantum technologies, and finally, optical computing. By leveraging the myriad inherent attractive features of integrated silicon photonics, this paper aims to inspire further development in incorporating PICs with on-chip lasers in, but not limited to, these applications for substantial performance gains, green solutions, and mass production.

Zhou, Zhican↗

DOE OSTI2023

Comprehensive Battery Safety Risk Evaluation: Aged Cells versus Fresh Cells Upon Mechanical Abusive Loadings

Abstract Despite their wide applications, lithium‐ion batteries (LIBs) have been struggling with their safety risks arising from different lifetime stages. Here, the NCMA pouch cell is taken as an example, and the safety of both fresh and aged cells from three milestone stages, that is, internal short circuit (ISC) triggering risk, ISC mode, and the subsequent thermal runaway (TR) consequence is investigated. By combining mechanical abusive testing and physics‐based models on commercialized cells with various states‐of‐health (SOH) and states‐of‐charge, it is discovered that the ISC triggering delays with the decay of SOH and soft ISC mode will be triggered more frequently, which is mainly due to the mechanical behaviors of the current collectors. The temperature rises and peak temperature during the subsequent TR also become milder for aged cells due to the reduced capacity and deterministic soft ISC process. Results here provide a mechanistic explanation of the safety risk comparison between the fresh and aged cells, offering cornerstone guidance to the evaluation and design of next‐generation safer LIBs.

25 ENERGY STORAGE↗

DOE OSTI2022

Prognostic importance of the preoperative New‐Naples prognostic score for patients with gastric cancer

Abstract Background The wide applicability of the Naples prognostic score (NPS) is still worthy of further study in gastric cancer (GC). This study aimed to construct a New‐NPS based on the differences in immunity and nutrition in patients with upper and lower gastrointestinal tumors to help obtain an individualized prediction of prognosis. Methods This study retrospectively analyzed patients who underwent radical gastrectomy from April 2014 to September 2016. The cutoff values of the preoperative neutrophil‐to‐lymphocyte ratio (NLR), lymphocyte‐to‐monocyte ratio (LMR), serum albumin (Alb), and total cholesterol (TC) were calculated by ROC curve analysis. ROC and t‐ROC were used to evaluate the accuracy of the prognostic markers. The Kaplan–Meier method and log‐rank test were used to analyze the overall survival probability. Univariate and multivariate analyses based on Cox risk regression were used to show the independent predictors. The nomogram was made by R studio. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C‐index), and decision curve. Results A total of 737 patients were included in training cohort, 411 patients were included in validation cohort. ROC showed that the New‐NPS was more suitable for predicting the prognosis of GC patients. NPS = 2 indicated a poor prognosis. Multivariate analysis showed that CEA ( P = 0.026), Borrmann type ( P = 0.001), pTNM ( P < 0.001), New‐NPS ( P < 0.001), and nerve infiltration ( P = 0.035) were independent risk factors for prognosis. Conclusion The New‐NPS based on the cutoff values of NLR, LMR, Alb, and TC is not only suitable for predicting prognosis but can also be combined with clinicopathological characteristics to construct a nomogram model for GC patients.

Wang, Hao↗

DOE OSTI2024

Optimizing High-Throughput Inference on Graph Neural Networks at Shared Computing Facilities with the NVIDIA Triton Inference Server

Abstract With machine learning applications now spanning a variety of computational tasks, multi-user shared computing facilities are devoting a rapidly increasing proportion of their resources to such algorithms. Graph neural networks (GNNs), for example, have provided astounding improvements in extracting complex signatures from data and are now widely used in a variety of applications, such as particle jet classification in high energy physics (HEP). However, GNNs also come with an enormous computational penalty that requires the use of GPUs to maintain reasonable throughput. At shared computing facilities, such as those used by physicists at Fermi National Accelerator Laboratory (Fermilab), methodical resource allocation and high throughput at the many-user scale are key to ensuring that resources are being used as efficiently as possible. These facilities, however, primarily provide CPU-only nodes, which proves detrimental to time-to-insight and computational throughput for workflows that include machine learning inference. In this work, we describe how a shared computing facility can use the NVIDIA Triton Inference Server to optimize its resource allocation and computing structure, recovering high throughput while scaling out to multiple users by massively parallelizing their machine learning inference. To demonstrate the effectiveness of this system in a realistic multi-user environment, we use the Fermilab Elastic Analysis Facility augmented with the Triton Inference Server to provide scalable and high-throughput access to a HEP-specific GNN and report on the outcome.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstractions by $CH_3\dot{O}$ radical

H-atom abstraction by methoxy radical ($CH_3\dot{O}$) plays an important role in capturing the kinetics of reactions between gasoline components and alcohols. This study focuses on determining the reaction rates and thermodynamic properties of methoxy radical reactions with five gasoline fuel components: n-heptane, iso-octane, 1-hexene, cyclopentane and toluene. Electronic structure calculations were per-formed for all the stationary points with M06-2X/6 -311 ++ g(d,p) method. G3 composite method with atomization method is used for determining Δ f H 0 of all the closed shell and radical species, using which the necessary thermodynamic data of all the species was determined. Coupled cluster theory QCISD(T)/cc-pVXZ (where X = D and T) and Møller-Plesset perturbation theory MP2/cc-pVXZ (where X = D, T and Q) were used to calculate single point energies. Subsequently, rate constants for all hydrogen atom ab-straction channels have been performed using conventional transition state theory with unsymmetric tunneling corrections. A systematic comparison of rates for abstraction from different sites within the same species and same site from different species is done in order to get insights into this reaction class. Here, the computed thermodynamic properties and rate constants were incorporated into a recent gasoline mechanism to investigate the impact of the calculations performed in this work. A shift in predicted NTC (negative temperature coefficient) behavior and significant reduction in model reactivity is observed upon incorporating the rates calculated herein.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Experimental determinations of carbon and hydrogen isotope fractionations and methane clumped isotope compositions associated with ethane pyrolysis from 550 to 600°C

Methane clumped isotope compositions signify the relative natural abundances of rare, doubly substituted isotopic species of methane ( 13 CH 3 D and 12 CH 2 D 2 ) and have emerged as a new isotopic tool to trace the sources, sinks, and lifecycles of methane in the environment. Such measurements can identify equilibration (or reequilibration) temperatures if found to be in isotopic equilibrium or non-equilibrium processes (e.g., kinetically controlled reactions or mixing) if not in isotopic equilibrium. Naturally occurring thermogenic methane—formed by the thermally activated breakdown of larger organic molecules—has been found to have clumped isotope compositions consistent with equilibrium at reasonable gas formation temperatures in some settings and non-equilibrium processes occurring during either formation, migration, storage, or extraction in others. To explore the potential controls on the isotopic composition of thermogenic methane, we conducted isothermal time-series ethane pyrolysis experiments at 550 and 600 °C to measure methane and ethane 13 C/ 12 C and D/H fractionations and methane clumped isotope compositions (resolved 13 CH 3 D and 12 CH 2 D 2 ). We explore the effects of modifying the initial clumped isotope composition of ethane and the addition of water vapor to pyrolysis experiments. We observe that ethane and methane 13 C/ 12 C are controlled by kinetic isotope effects and Rayleigh distillation processes. In contrast, ethane and methane D/H and methane clumped isotope compositions appear to be controlled by a combination of these processes and hydrogen isotope exchange. The hydrogen isotope exchange processes lead to isotopic equilibrium as reaction completion is approached for both D/H (ethane/methane) and methane clumped isotope compositions. Here, we develop a chemical model based on a mass balance approach that accounts for inheritance vs. hydrogen-abstraction formation pathways for singly and doubly substituted isotopologues of ethane and methane that is compared to the experimental data. The model allows the determination of carbon and hydrogen kinetic isotope effects associated with ethane cracking and hydrogen abstraction reactions that, where applicable, we compare to prior theoretical constraints. From the comparison of the model to the experimental data, we infer that the kinetically controlled ethane and methane bulk isotope compositions and methane clumped isotope compositions are controlled by kinetic isotope effects (both primary and secondary) associated with both C–C bond and C–H bond cleavage reactions. Specifically, the methane clumped isotope compositions likely result from a combination of clumped isotope effects associated with ethane breakdown and/or assembly of methane isotopologues (expressed in terms of γ-factor parameters ≠ 1) and combinatorial effects that arise probabilistically. We discuss our experimental results in the context of recent pyrolysis experiments and observations of naturally occurring thermogenic methane. We consider a proposal consistent with observations from nature that the hydrogen isotope exchange reactions that promote equilibration of methane isotopic molecules at or near formation temperature may be facilitated by free radicals generated by pyrolysis reactions. In this framework, isotope exchange effectively ceases when pyrolysis effectively ceases locking in compositions that can be consistent with peak formation temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstraction by $CH_3O\dot{O}$ radicals

Hydrogen atom abstraction by methyl peroxy ($CH_3O\dot{O}$) radicals can play an important role in gasoline/ethanol interacting chemistry for fuels that produce high concentrations of methyl radicals. Detailed kinetic reactions for hydrogen atom abstraction by $CH_3O\dot{O}$ radicals from the components of FGF-LLNL (a gasoline surrogate) including cyclopentane, toluene, 1-hexene, n -heptane, and isooctane have been systematically studied in this work. Here, the M06-2X/6-311 ++ G(d,p) level of theory was used to obtain the optimized structure and vibrational frequency for all stationary points and the low-frequency torsional modes. The 1-D hindered rotor treatment for low-frequency torsional modes was treated at M06-2X/6-31G level of theory. The UCCSD(T)-F12a/cc-pVDZ-F12 and QCISD(T)/CBS level of theory were used to calculate single point energies for all species. High pressure limiting rate constants for all hydrogen atom abstraction channels were performed using conventional transition state theory with unsymmetric tunneling corrections. Individual rate constants are reported in the temperature range from 298.15 to 2000 K. Our computed results show that the abstraction of allylic hydrogen atoms from 1-hexene is the fastest at low temperatures. When the temperature increases, the hydrogen atom abstraction reaction channel at the primary alkyl site gradually becomes dominant. Thermodynamics properties for all stable species and high-pressure limiting rate constants for each reaction pathway obtained in this work were incorporated into the latest gasoline surrogate/ethanol model to investigate the influence of the rate constants calculated here on model predicted ignition delay times.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

How Equivalent Are Equivalent Porous Media?

Abstract Geoenergy and geoengineering applications usually involve fluid injection into and production from fractured media. Accounting for fractures is important because of the strong poromechanical coupling that ties pore pressure changes and deformation. A possible approach to the problem uses equivalent porous media to reduce the computational cost and model complexity instead of explicitly including fractures in the models. We investigate the validity of this simplification by comparing these two approaches. Simulation results show that pore pressure distribution significantly differs between the two approaches even when both are calibrated to predict identical values at the injection and production wells. Additionally, changes in fracture stability are not well captured with the equivalent porous medium. We conclude that explicitly accounting for fractures in numerical models may be necessary under some circumstances to perform reliable coupled thermohydromechanical simulations, which could be used in conjunction with other tools for induced seismicity forecasting.

58 GEOSCIENCES↗

DOE OSTI2021

Close Observation of Hydraulic Fracturing at EGS Collab Experiment 1: Fracture Trajectory, Microseismic Interpretations, and the Role of Natural Fractures

Abstract Despite the wide application of hydraulic fracturing in enhanced geothermal system (EGS) development and unconventional hydrocarbon production, our understanding of the many factors affecting the propagation of hydraulic fractures has relied on circumstantial evidence. This is partly due to the scarcity of direct observations in the subsurface. The EGS Collab project attempts to address these issues in the context of EGS research by performing intermediate‐scale (∼10 m) hydraulic stimulation experiments in a thoroughly characterized and heavily instrumented underground testbed. This paper analyzes the data collected from the first suite of hydraulic fracturing tests in this testbed, consisting of seven stimulation episodes. High‐quality microseismic data delineate five planar features very clearly. Combining fracture‐wellbore intersection observations from distributed temperature sensing (DTS) and visual observations from an open‐hole well, as well as prior in‐situ stress measurements, we conclude with high certainty that the four larger planes were hydraulic fractures. The growth of the hydraulic fractures was temporarily halted by a prominent, open natural fracture in the testbed but they eventually crossed and slightly reoriented under continued stimulation. Mineral‐filled (i.e., healed) natural fractures, though prevalent in the testbed, did not have perceivable effects on hydraulic fracture propagation. The high‐quality, mutually corroborating data sets allowed conclusions to be drawn with high confidence and attests to the advantage of intermediate‐scale experiments in subsurface research.

58 GEOSCIENCES↗

DOE OSTI2021

A quantum encryption design featuring confusion, diffusion, and mode of operation

Abstract Quantum cryptography—the application of quantum information processing and quantum computing techniques to cryptography has been extensively investigated. Two major directions of quantum cryptography are quantum key distribution (QKD) and quantum encryption, with the former focusing on secure key distribution and the latter focusing on encryption using quantum algorithms. In contrast to the success of the QKD, the development of quantum encryption algorithms is limited to designs of mostly one-time pads (OTP) that are unsuitable for most communication needs. In this work we propose a non-OTP quantum encryption design utilizing a quantum state creation process to encrypt messages. As essentially a non-OTP quantum block cipher the method stands out against existing methods with the following features: 1. complex key-ciphertext relation (i.e. confusion) and complex plaintext-ciphertext relation (i.e. diffusion); 2. mode of operation design for practical encryption on multiple blocks. These features provide key reusability and protection against eavesdropping and standard cryptanalytic attacks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

Abstract Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar ( Populus nigra X P. maximowiczii ), switchgrass ( Panicum virgatum ), miscanthus ( Miscanthus giganteus ), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha −1 year −1 ) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L −1 ) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha −1 year −1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Source-agnostic gravitational-wave detection with recurrent autoencoders

Abstract We present an application of anomaly detection techniques based on deep recurrent autoencoders (AEs) to the problem of detecting gravitational wave (GW) signals in laser interferometers. Trained on noise data, this class of algorithms could detect signals using an unsupervised strategy, i.e. without targeting a specific kind of source. We develop a custom architecture to analyze the data from two interferometers. We compare the obtained performance to that obtained with other AE architectures and with a convolutional classifier. The unsupervised nature of the proposed strategy comes with a cost in terms of accuracy, when compared to more traditional supervised techniques. On the other hand, there is a qualitative gain in generalizing the experimental sensitivity beyond the ensemble of pre-computed signal templates. The recurrent AE outperforms other AEs based on different architectures. The class of recurrent AEs presented in this paper could complement the search strategy employed for GW detection and extend the discovery reach of the ongoing detection campaigns.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Modelling nearest neighbour distributions of biased tracers using hybrid effective field theory

ABSTRACT We investigate the application of hybrid effective field theory (HEFT) – which combines a Lagrangian bias expansion with subsequent particle dynamics from N-body simulations – to the modelling of k-nearest neighbour cumulative distribution functions (kNN-CDFs) of biased tracers of the cosmological matter field. The kNN-CDFs are sensitive to all higher order connected N-point functions in the data, but are computationally cheap to compute. We develop the formalism to predict the kNN-CDFs of discrete tracers of a continuous field from the statistics of the continuous field itself. Using this formalism, we demonstrate how kNN-CDF statistics of a set of biased tracers, such as haloes or galaxies, of the cosmological matter field can be modelled given a set of low-redshift HEFT component fields and bias parameter values. These are the same ingredients needed to predict the two-point clustering. For a specific sample of haloes, we show that both the two-point clustering and the kNN-CDFs can be well-fit on quasi-linear scales (≳ 20h−1Mpc) by the second-order HEFT formalism with the same values of the bias parameters, implying that joint modelling of the two is possible. Finally, using a Fisher matrix analysis, we show that including kNN-CDF measurements over the range of allowed scales in the HEFT framework can improve the constraints on σ8 by roughly a factor of 3, compared to the case where only two-point measurements are considered. Combining the statistical power of kNN measurements with the modelling power of HEFT, therefore, represents an exciting prospect for extracting greater information from small-scale cosmological clustering.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms appropriate for training. Considering that these networks often have very different performance characteristics than traditional neural networks, it is often unclear how to set either the network topology or the hyperparameters to achieve optimal performance. In this work, we introduce a Bayesian approach for optimizing the hyperparameters of an algorithm for training binary communication networks that can be deployed to neuromorphic hardware. We show that by optimizing the hyperparameters on this algorithm for each dataset, we can achieve improvements in accuracy over the previous state-of-the-art for this algorithm on each dataset (by up to 15 percent). This jump in performance continues to emphasize the potential when converting traditional neural networks to binary communication applicable to neuromorphic hardware.

Parsa, Maryam↗