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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quancorde: Boosting fidelity with Quantum Canary Ordered Diverse Ensembles

On today's noisy imperfect quantum devices, execution fidelity tends to collapse dramatically for most applications beyond a handful of qubits. It is therefore imperative to employ novel techniques that can boost quantum fidelity in new ways. Here, this paper aims to boost quantum fidelity with Clifford canary circuits by proposing Quancorde: Quantum Canary Ordered Diverse Ensembles, a fundamentally newapproach to identifying the correct outcomes of extremely low-fidelity quantum applications. It is based on the key idea of diversity in quantum devices - variations in noise sources, make each (portion of a) device unique, and therefore, their impact on an application's fidelity, also unique. Quancorde utilizes Clifford canary circuits (which are classically simulable, but also resemble the target application structure and thus suffer similar structural noise impact) to order a diverse ensemble of devices or qubits/mappings approximately along the direction of increasing fidelity of the target application. Quancorde then estimates the correlation of the ensemble-wide probabilities of each output string of the application, with the canary ensemble ordering, and uses this correlation to weight the application's noisy probability distribution. The correct application outcomes are expected to have higher correlation with the canary ensemble order, and thus their probabilities are boosted in this process. Doing so, Quancorde improves the fidelity of evaluated quantum applications by a mean of 8.9x/4.2x (wrt. different baselines) and up to a maximum of 34x.

clifford↗
DOE OSTI2023

A Predictive Prescription Framework for Stochastic Unit Commitment Using Boosting Ensemble Learning Algorithms

To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that materialize on a particular day are influenced by various covariates (such as the day of the week or temperature), SO frameworks typically disregard such side observations, wasting actionable information that could significantly enhance decision quality. Here, this article proposes a contextual SO (CSO) framework for UC under uncertain load, which can effectively exploit covariate observations in conjunction with a class of machine learning (ML) algorithms to improve the out-of-sample performance of UC decisions. It shows how three ML algorithms, adaptive boosting, gradient boosted trees, and extreme gradient boosting, can be used to this end, constituting the first application of these algorithms in any CSO framework. Using real-world data harvested from the New York ISO grid, we measure the out-of-sample performance of the framework in terms of total operation cost, shed load values, locational marginal prices, and total payments by the loads, against several benchmark methods proposed in the literature. The article has an online companion (Yurdakul et al.), wherein we present additional results and lay out further mathematical formulations used in this work.

42 ENGINEERING↗
DOE OSTI2024

Fair Bagging Boosting Models [SWR-24-38]

Fair Bagging Boosting Models is a software implementation of a framework for building, measuring bias and correcting bias in 3 popular forest machine learning models: gradient boosted trees (GBT), random forest (RF), and XGBoost models, using the XGBoost library. The framework takes advantage of the flexibility in XGBoost library to represent gradient boosted tree and random forest models, as well as the ability to use custom loss function.

Ugirumurera, Juliette↗
DOE OSTI2021

Extreme Miller cycle with high intake boost for improved efficiency and emissions in heavy-duty diesel engines

This study experimentally investigates the impact of extreme Miller cycle strategies paired with high intake manifold pressures on the combustion process, emissions, and thermal efficiency of heavy-duty diesel engines. Well-controlled experiments isolating the effect of Miller cycle strategies on the combustion process were conducted at constant engine speed and load (1160 rpm, 1.76 MPa net IMEP) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Late intake valve closing (LIVC) timing strategies were compared to a conventional intake valve profile under either constant cylinder composition, constant engine-out NO x emission, or constant overall turbocharger efficiency (η TC ) to investigate the operating constraints that favor Miller cycle operation over the baseline strategy. Furthermore, utilizing high boost with conventional intake valve closing timing resulted in improved fuel consumption at the expense of sharp increases in peak cylinder pressures, engine-out NO x emissions, and reduced exhaust temperatures. Miller cycle without EGR at constant λ demonstrated LIVC strategies effectively reduce engine-out NO x emissions by up to 35%. However, Miller cycle associated with very aggressive LIVC timings led to fuel consumption penalties due to increased pumping work and exhaust enthalpy. LIVC strategies allowed for increased charge dilution at the baseline NO x constraint of 3.2 g/kWh, resulting in significant fuel consumption benefits over the baseline case without compromising exhaust temperatures or peak cylinder pressures. As Miller cycle implementation was shown to affect the boundary conditions dictating η TC , the LIVC and conventional IVC cases were studied at an equivalent η TC point representative of high boost operation. With high boost, LIVC yielded reduced NO x emissions, reduced peak cylinder pressures, and elevated exhaust temperatures compared to the conventional IVC case without compromising fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Convergence in nonlinear laser wakefield accelerators modeling in a Lorentz-boosted frame

Laser wakefield acceleration modeling using the Lorentz-boosted frame technique in the particle-in-cell code has demonstrated orders of magnitude speedups. A convergence study was previously conducted in cases with external injection in the linear regime and without injection in the nonlinear regime, and the obtained results have shown a convergence within the percentage level. Here, a convergence study is carried out to model electron self-injection in a 2D–3V configuration. It is observed that the Lorentz-boosted frame technique is capable of modeling complex particle dynamics with a significant speedup. This result is crucial to curtail the computational time of the modeling of future chains of laser wakefield accelerator stages with high accuracy.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Economic analysis of the benefits to petroleum refiners for low carbon boosted spark ignition biofuels

A refinery modeling framework is developed to estimate the benefits of blending high-quality biofuels directly with refinery gasoline components for attaining a premium grade fuel (also termed as Co-Optima Boosted SI gasoline here). Our results change the paradigm of bio-blendstocks (BBs) being competitors to fossil components, by identifying opportunities for refineries to add value to their product slate, from some favorable BB properties. This potential value can be characterized by calculating the breakeven value (BEV), as defined down below. The proposed modeling framework incorporates extensive data from (1) projected product over the next few decades, (2) crude oil and refinery products pricing, and (3) fuel specifications. The complete refinery models serve as a basis for assessing the value of biofuels, assuming profitability remains the same for representative petroleum refinery configurations. Our assessment showed wide range of variation of biofuels BEV from $\$$20-$\$$120/bbl, within the considered blending level and crude prices. Further, the BEV was correlated with the fuel octane ratings such as octane numbers (research, RON and motor octane numbers, MON) and both antiknock index (AKI, average of RON and MON) and sensitivity (S, difference between RON and MON), with a slightly higher correlation with the sensitivity. However, the expected decrease in gasoline demand for the upcoming years could negatively impact biofuels demand and value, in a business-as-usual scenario. Our analysis also showed a more valuable bio-blendstocks incorporation in smaller refineries since they can enhance the capabilities for producing specialty, high-value fuels/products, and introduce high octane-barrels into otherwise constrained blending operations. Additional implications towards refiners include opportunities to rebalance operations, access to high-value fuel markets, and synchronization with broader transportation industry trends. Furthermore, results indicate the value of Co-Optima boosted spark ignition (BSI) efficiency gains can extend to refiners to incentivize decarbonization and diversified feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2024

Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems

Abstract We present an innovative approach called boosting Barlow Twins reduced order modeling (BBT‐ROM) to enhance the reliability of machine learning surrogate models for multiphase flow problems. BBT‐ROM builds upon Barlow Twins reduced order modeling that leverages self‐supervised learning to effectively handle linear and nonlinear manifolds by constructing well‐structured latent spaces of input parameters and output quantities. To address the challenge of high contrast data in multiphase flow problems due to injection wells and faults, we employ a boosting algorithm within BBT‐ROM. This algorithm sequentially trains a set of weak models (i.e., inaccurate models), improving prediction accuracy through ensemble learning. To evaluate the performance of BBT‐ROM, we conduct three three‐dimensional multiphase flow problems, including waterflooding and geologic carbon storage (GCS), with varying numbers of input parameter cases and model domain features. The results demonstrate that BBT‐ROM excels at predicting non‐wetting phase saturation (e.g., oil or saturation) and fluid pressure, with average relative errors ranging from 0.5% to 3%. Importantly, BBT‐ROM showcases robustness when faced with limited input parameter space during GCS testing.

58 GEOSCIENCES↗
DOE OSTI2020

Anode Boosted Electrolyzer

The aim of this project is to develop an anode catalyst and anolyte delivery system in renewably powered flow-electrolyzers that utilize waste carbon dissolved in non-potable process water as the anolyte to lower the overall cell potential at which hydrogen is generated (Anode-Boosting) while simultaneously purifying a non-potable water source. This project spans several of the desired aspects in the Renewable Hydrogen Transportation Fuel Pathways of interest: it combines renewably sourced energy with waste hydrocarbons, leading to enhanced water-splitting and eventual delivery and distribution of hydrogen for use in fuel cell powered transportation. Deployment of an Anode-Boosted Electrolysis process will provide a significant improvement in the effective energy efficiency for the generation of hydrogen due to a reduced cell potential and the desirable removal of organic impurities in waste water, offering a route to generating clean hydrogen and clean(er) water.

08 HYDROGEN↗
DOE OSTI2022

Non‐Flammable Ester Electrolyte with Boosted Stability Against Li for High‐Performance Li Metal Batteries

Abstract In traditional non‐flammable electrolytes a trade‐off always exists between non‐flammability and battery performance. Previous research focused on reducing free solvents and forming anion‐derived solid‐electrolyte interphase. However, the contribution of solvated anions in boosting the stability of electrolyte has been overlooked. Here, we resolve this via introducing anions into Li + solvation sheaths using anions with similar Gutmann donor number (DN) to that of solvents. Taking trimethyl phosphate fire‐retardant (DN=23.0 kcal mol −1 ) and NO 3 − (DN=22.2 kcal mol −1 ) as an example, NO 3 − is readily involved in the Li + solvation sheath and reduces the polarity of solvent. This results in boosted stability of electrolyte against Li. The developed non‐flammable electrolyte has low viscosity, high ionic conductivity and is low cost. The reversibility of Li‐Cu cell was improved to 99.49 % and the lifespan of practical LMBs was extended by >100 %.

Wang, Zhijie↗
DOE OSTI2022

Non‐Flammable Ester Electrolyte with Boosted Stability Against Li for High‐Performance Li Metal Batteries

Abstract In traditional non‐flammable electrolytes a trade‐off always exists between non‐flammability and battery performance. Previous research focused on reducing free solvents and forming anion‐derived solid‐electrolyte interphase. However, the contribution of solvated anions in boosting the stability of electrolyte has been overlooked. Here, we resolve this via introducing anions into Li + solvation sheaths using anions with similar Gutmann donor number (DN) to that of solvents. Taking trimethyl phosphate fire‐retardant (DN=23.0 kcal mol −1 ) and NO 3 − (DN=22.2 kcal mol −1 ) as an example, NO 3 − is readily involved in the Li + solvation sheath and reduces the polarity of solvent. This results in boosted stability of electrolyte against Li. The developed non‐flammable electrolyte has low viscosity, high ionic conductivity and is low cost. The reversibility of Li‐Cu cell was improved to 99.49 % and the lifespan of practical LMBs was extended by >100 %.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Spontaneously broken boosts and the Goldstone continuum

The spontaneous breaking of boost invariance is ubiquitous in nature, yet the associated Goldstone bosons are nowhere to be seen. We discuss why some subtleties are to be expected in the Goldstone phenomenon for spontaneously broken boosts, and derive the corresponding quantum mechanical, non-perturbative Goldstone theorem. Despite similarities with more standard Goldstone theorems, we show by examples that ours can be obeyed by quite unusual spectra of low-energy excitations. In particular, for non- relativistic Fermi liquids, we prove that it is obeyed by the particle-hole continuum . To the best of our knowledge, this is the first example of a Goldstone theorem obeyed by a continuum rather than by (approximately stable) single-particle Goldstone boson states in an interacting theory at zero temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Spontaneously broken boosts in CFTs

Conformal Field Theories (CFTs) have rich dynamics in heavy states. We describe the constraints due to spontaneously broken boost and dilatation symmetries in such states. The spontaneously broken boost symmetries require the existence of new low-lying primaries whose scaling dimension gap, we argue, scales as O(1). We demonstrate these ideas in various states, including fluid, superfluid, mean field theory, and Fermi surface states. We end with some remarks about the large charge limit in 2d and discuss a theory of a single compact boson with an arbitrary conformal anomaly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

SAM-I-Am: Semantic boosting for zero-shot atomic-scale electron micrograph segmentation

Image segmentation is a critical enabler for tasks ranging from medical diagnostics to autonomous driving. However, the correct segmentation semantics — where are boundaries located? what segments are logically similar? — change depending on the domain, such that state-of-the-art foundation models can generate meaningless and incorrect results. Moreover, in certain domains, fine-tuning and retraining techniques are infeasible: obtaining labels is costly and time-consuming; domain images (micrographs) can be exponentially diverse; and data sharing (for third-party retraining) is restricted. To enable rapid adaptation of the best segmentation technology, we propose the concept of semantic boosting: given a zero-shot foundation model, guide its segmentation and adjust results to match domain expectations. Here, we apply semantic boosting to the Segment Anything Model (SAM) to obtain microstructure segmentation for transmission electron microscopy. Our booster, SAM-I-Am, serves as a post-processing engine that extracts geometric and textural features of various intermediate masks to perform mask removal and mask merging operations. We demonstrate a zero-shot performance increase of (absolute) +21.35%, +12.6%, +5.27% in mean IoU, and a -9.91%, -18.42%, -4.06% drop in mean false positive masks across images of three difficulty classes over vanilla SAM (ViT-L).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Impact of High-Dose-Rate and Low-Dose-Rate Brachytherapy Boost on Toxicity, Functional and Cancer Outcomes in Patients Receiving External Beam Radiation Therapy for Prostate Cancer: A National Population-Based Study

External beam radiation therapy (EBRT) with brachytherapy boost reduces cancer recurrence in patients with prostate cancer compared with EBRT monotherapy. However, randomized controlled trials or large-scale observational studies have not compared brachytherapy boost types directly.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Impact of Dose-Escalated Chemoradiation on Quality of Life in Patients With Locally Advanced Rectal Cancer: 2-Year Follow-Up of the Randomized RECTAL-BOOST Trial

Dose-escalated chemoradiation (CRT) for locally advanced rectal cancer did not result in higher complete response rates but initiated more tumor regression in the randomized RECTAL-BOOST trial (Clinicaltrials.gov NCT01951521). This study compared patient reported outcomes between patients who received dose-escalated CRT (5 × 3 gray boost + CRT) or standard CRT for 2 years after randomization.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Measurement of the $t\bar{t}$ charge asymmetry in events with highly Lorentz-boosted top quarks in pp collisions at $\sqrt{s}$ = 13 TeV

The measurement of the charge asymmetry in top quark pair events with highly Lorentz-boosted top quarks decaying to a single lepton and jets is presented. The analysis is performed using proton-proton collisions at $\sqrt{s}$ = 13 TeV with the CMS detector at the LHC and corresponding to an integrated luminosity of 138 fb -1 . The selection is optimized for top quarks produced with large Lorentz boosts, resulting in nonisolated leptons and overlapping jets. The top quark charge asymmetry is measured for events with a $t\bar{t}$ invariant mass larger than 750 GeV and corrected for detector and acceptance effects using a binned maximum likelihood fit. The measured top quark charge asymmetry of ($0.42_{-0.69}^{+0.64}$) % is in good agreement with the standard model prediction at next-to-next-to-leading order in quantum chromodynamic perturbation theory with next-to-leading-order electroweak corrections. The result is also presented for two invariant mass ranges, 750–900 and > 900 GeV .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

An unprecedented quinoid–donor–acceptor strategy to boost the carrier mobilities of semiconducting polymers for organic field-effect transistors

Quinoidal–aromatic conjugated polymers hold great application potential in organic field-effect transistors (OFETs). However, the development of high mobility quinoidal–aromatic conjugated polymers still lags behind the more popular donor–acceptor (D–A) conjugated polymers, mainly owing to the lack of a rational design strategy and efficient building block. Herein, a novel quinoid–donor–acceptor (Q–D–A) strategy is demonstrated to modulate the energy-level and boost the charge carrier transport mobility of conjugated polymers as opposed to the D–A system. On the basis of this strategy, a quinoidal–aromatic conjugated polymer, namely PAQM-BT, is designed and synthesized. With the combined use of quinoid, donor and acceptor units in the backbone, the resulting Q–D–A polymer PAQM-BT displays the narrowest bandgap with the deepest-lying lowest unoccupied molecular orbital (LUMO) energy level, highest backbone coplanarity, enhanced thin-film crystallinity and smallest effective hole mass ($m^*_h$) in comparison with the corresponding D–A polymer PT3B1 and quinoid–donor (Q–D) polymer PAQM-3T. Benefitting from the more effective intra- and inter-chain charge transport, as corroborated by experiment and theoretical calculations, OFET devices based on PAQM-BT exhibit a highly boosted hole mobility of up to 5.10 cm 2 V -1 s -1 , which is one and four orders of magnitude higher than that of PAQM-3T and PT3B1, respectively, and is among the highest for quinoidal–aromatic conjugated polymers. Finally, the potent Q–D–A strategy not only allows the energy level to be modulated but also leads to effective charge carrier transport, opening up possibilities to the development of high mobility quinoidal–aromatic conjugated polymers based on a variety of quinoids, donors, and acceptors.

36 MATERIALS SCIENCE↗