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Results for “Selection optimization”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Theory-Guided Synthesis of a Metastable Lead-Free Piezoelectric Polymorph

Many technologically critical materials are metastable under ambient conditions, yet the understanding of how to rationally design and guide the synthesis of these materials is limited. This paper presents an integrated approach that targets a metastable lead-free piezoelectric polymorph of SrHfO 3 . First-principles calculations predict that the previous experimentally unrealized, metastable P4mm phase of SrHfO 3 should exhibit a direct piezoelectric response (d 33 ) of 36.9 pC N -1 (compared to d 33 = 0 for the ground state). Combining computationally optimized substrate selection and synthesis conditions lead to the epitaxial stabilization of the polar P4mm phase of SrHfO 3 on SrTiO 3 . The films are structurally consistent with the theory predictions. A ferroelectric-induced large signal effective converse piezoelectric response of 5.2 pm V -1 for a 35 nm film is observed, indicating the ability to predict and target multifunctionality. Finally, this illustrates a coupled theory-experimental approach to the discovery and realization of new multifunctional polymorphs.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Probing the Dynamic Mechanism of Uncommon Allosteric Inhibitors Optimized to Enhance Drug Selectivity of SHP2 with Therapeutic Potential for Cancer Treatment

There is currently considerable interest in SHP2 as a potential target for treatment of cancer. Mutation in SHP2, particularly the E76A mutation, has been found to seriously confer the phosphatase high activity. Recently, two compounds, 1 and 23, have been reported as potent allosteric inhibitors of both SHP2 wild type (SHP2{sup WT}) and the E76A mutant (SHP2{sup E76A}), with higher activity than other inhibitors. However, the structural and dynamic implications of their inhibitory mechanisms are yet unexplored which deserve further attention. Herein, the MD simulation applies to gain insight into the atomistic nature of each binding mode of inhibitors 1 and 23 in both SHP2{sup WT} and SHP2{sup E76A}. The comparative analysis reveals inhibitor 1 can freeze SHP2{sup WT} and SHP2{sup E76A} in their auto-inhibited conformation better than 23, in agreement with experimental data. GLU250 in both SHP2{sup WT} and SHP2{sup E76A} and ARG111 and ARG229 in SHP2{sup E76A} play a crucial role in the higher activity of 1 compared to 23. The mutation E76A increases the binding affinity of 1 and 23 compared to the wild type, implying that the two inhibitors have been well adopted by the E76A mutant. The findings here can substantially shed light on new strategies for developing novel classes of SHP2 inhibitors with increased potency.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Engineering Catalyst–Electrolyte Microenvironments to Optimize the Activity and Selectivity for the Electrochemical Reduction of CO 2 on Cu and Ag

We report the electrochemical reduction of carbon dioxide (CO 2 R) driven by renewably generated electricity (e.g., solar and wind) offers a promising means for reusing the CO 2 released during the production of cement, steel, and aluminum as well as the production of ammonia and methanol. If CO 2 could be removed from the atmosphere at acceptable costs (i.e., <$100/t of CO 2 ), then CO 2 R could be used to produce carbon-containing chemicals and fuels in a fully sustainable manner. Economic considerations dictate that CO 2 R current densities must be in the range of 0.1 to 1 A/cm 2 and selectivity toward the targeted product must be high in order to minimize separation costs. Industrially relevant operating conditions can be achieved by using gas diffusion electrodes (GDEs) to maximize the transport of species to and from the cathode and combining such electrodes with a solid-electrolyte membrane by eliminating the ohmic losses associated with liquid electrolytes. Additionally, high product selectivity can be attained by careful tuning of the microenvironment near the catalyst surface (e.g., the pH, the concentrations of CO 2 and H 2 O, and the identities of the cations in the double layer adjacent to the catalyst surface).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Discovery and Structure-Based Optimization of Potent and Selective WD Repeat Domain 5 (WDR5) Inhibitors Containing a Dihydroisoquinolinone Bicyclic Core

WD repeat domain 5 (WDR5) is a member of the WD40-repeat protein family that plays a critical role in multiple chromatin-centric processes. Overexpression of WDR5 correlates with a poor clinical outcome in many human cancers, and WDR5 itself has emerged as an attractive target for therapy. Most drug-discovery efforts center on the WIN site of WDR5 that is responsible for the recruitment of WDR5 to chromatin. In this paper, we describe discovery of a novel WDR5 WIN site antagonists containing a dihydroisoquinolinone bicyclic core using a structure-based design. These compounds exhibit picomolar binding affinity and selective concentration-dependent antiproliferative activities in sensitive MLL-fusion cell lines. Furthermore, these WDR5 WIN site binders inhibit proliferation in MYC-driven cancer cells and reduce MYC recruitment to chromatin at MYC/WDR5 co-bound genes. Thus, these molecules are useful probes to study the implication of WDR5 inhibition in cancers and serve as a potential starting point toward the discovery of anti-WDR5 therapeutics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Pore-Space Partition and Optimization for Propane-Selective High-Performance Propane/Propylene Separation

The development of effective propane (C 3 H 8 )-selective adsorbents for the purification of propylene (C 3 H 6 ) from C 3 H 8 /C 3 H 6 mixture is a promising alternative to replace the energy-intensive cryogenic distillation. However, few materials possess the dual desirable features of propane selectivity and high uptake capacity. Here, we report a family of pore-space-partitioned crystalline porous materials (CPM) with remarkable C 3 H 8 uptake capacity (up to 10.9 mmol/g) and the highly desirable, yet uncommon C 3 H 8 selectivity (up to 1.54 at 0.1 bar and 1.44 at 1bar). The selectivity-capacity synergy endows them with record-performing C 3 H 8 /C 3 H 6 separation potential (i.e., C 3 H 6 recovered from the mixture). Moreover, these CPMs exhibit outstanding properties including high stability, low regeneration energy, and multi-modular chemical and geometrical tunability within the same isoreticular framework. Furthermore, the high C 3 H 8 /C 3 H 6 separation performance was further confirmed by the breakthrough experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

ADAPTIVE GROUP TESTING WITH MISMATCHED MODELS

Accurate detection of infected individuals is one of the critical steps in stopping any pandemic. When the underlying infection rate of the disease is low, testing people in groups, instead of testing each individual in the population, can be more efficient. In this work, we consider noisy adaptive group testing design with specific test sensitivity and specificity that select the optimal group given previous test results based on pre-selected utility function. As in prior studies on group testing, we model this problem as a sequential Bayesian Optimal Experimental Design (BOED) to adaptively design the groups for each test. We analyze the required number of group tests when using the updated posterior on the infection status and the corresponding Mutual Information (MI) as our utility function for selecting new groups. More importantly, we study how the potential bias on the ground-truth noise of group tests may affect the group testing sample complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Automatic parameter selection for electron ptychography via Bayesian optimization

Abstract Electron ptychography provides new opportunities to resolve atomic structures with deep sub-angstrom spatial resolution and to study electron-beam sensitive materials with high dose efficiency. In practice, obtaining accurate ptychography images requires simultaneously optimizing multiple parameters that are often selected based on trial-and-error, resulting in low-throughput experiments and preventing wider adoption. Here, we develop an automatic parameter selection framework to circumvent this problem using Bayesian optimization with Gaussian processes. With minimal prior knowledge, the workflow efficiently produces ptychographic reconstructions that are superior to those processed by experienced experts. The method also facilitates better experimental designs by exploring optimized experimental parameters from simulated data.

42 ENGINEERING↗
DOE OSTI2018

Design and optimization of nanoparticle-pigmented solar selective absorber coatings for high-temperature concentrating solar thermal systems

In this paper, we present a systematic approach for the design and optimization of nanoparticle-pigmented solar selective absorbers for operation at 750 °C. Using the scattering and absorption cross-sections calculated by Lorenz-Mie scattering theory as input, we employ a four-flux radiative transfer method to investigate the solar selectivity mechanism and optimize the optical-to-thermal conversion efficiency (η therm ) as a function of the metallic nanoparticle material, the nanoparticle diameter, the volume fraction, and the coating thickness. Among the nanoparticle material candidates in this study, C54-TiSi 2 is the best option with an optimized η therm = 87.0% for a solar concentration ratio of C = 100 and η therm = 94.4% for C = 1000 at 750 °C. NiSi is also a promising candidate comparable to TiSi 2 in thermal efficiency, Experimentally, an un-optimized 200 nm-diameter TiSi 2 nanoparticle-silicone solar selective coating has already achieved η therm = 89.8% for C = 1000 at 750 °C. This performance is consistent with the theoretical model and close to the thermal efficiency of the commercial Pyromark 2500 coatings (90.1%). We also demonstrate that Ni/NiSi core-shell structures embedded in the SiO 1.5 matrix is thermally stable at 750 °C for 1000 h in air. Lastly, these results indicate that silicide cermet coatings are promising to achieve high optical performance and high temperature thermal stability simultaneously.

14 SOLAR ENERGY↗
DOE OSTI2026

Exploring the keV-scale physics potential of CUORE

We present the analysis techniques developed to explore the keV-scale energy region of the Cryogenic Underground Observatory for Rare Events (CUORE) experiment, based on more than 2 metric ton yr of data collected over five years. By prioritizing a stricter selection over a larger exposure, we are able to optimize data selection for thresholds at 10 keV and 3 keV with 691 kg yr and 11 kg yr of data, respectively. We study how the performance varies among the 988-detector array with different detector characteristics and data-taking conditions. We achieve an average baseline resolution of 2.54 ±0.14 keV FWHM and 1.18 ±0.02 keV FWHM for the data selection at 10 keV and 3 keV, respectively. The analysis methods employed reduce the overall background by about an order of magnitude, reaching 2.06±0.05 counts/(keV kg days) and 16±2 counts/(keV kg days) at the thresholds of 10 keV and 3 keV. We evaluate for the first time the near-threshold reconstruction efficiencies of the CUORE experiment, and find these to be 50 ±2% and 26 ±4% at 10 keV and 3 keV, respectively. This analysis provides crucial insights into rare decay studies, new physics searches, and keV-scale background modeling with CUORE. We demonstrate that ton-scale cryogenic calorimeters can operate across a wide energy range, from keV to MeV, establishing their scalability as versatile detectors for rare event and dark matter physics. These findings also inform the optimization of future large mass cryogenic calorimeters to enhance the sensitivity to low-energy phenomena.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2025

A device for volatile organic compound (VOC) analysis from skin using heated dynamic headspace sampling

Abstract Human skin is an important source of volatile organic compounds (VOCs) offering noninvasive methods to gain clinical metabolite information. This work was focused on the development of a skin sampling device based on a dynamic headspace sampling method with the addition of temperature to increase VOC metabolite recovery. The device preconcentrates skin VOC emissions onto a sorbent substrate, which can either be preserved for offline analysis or attached to a real time sensor downstream. In this work, skin VOC samples were analyzed offline using thermal desorption-gas chromatography-mass spectrometry. A list of 10 common skin VOCs was pre-selected to optimize parameters of sampling time, sampling temperature, and sorbent selection. Overall, this study highlights an effective skin VOC sampling technology with a heating dimension (40 °C, rather than 30 °C or no heating) with a sampling time of 15 min (rather than 5 or 30 mins) and onto Tenax TA sorbent (rather than PDMS), which collectively increases the recovery of compounds with lower vapor pressure and decreases the observed variability in skin VOC measurements. Finally, a list of 79 skin VOC compounds were detected and identified within a cohort of 20 young, healthy volunteers.

Biochemistry & Molecular Biology↗
DOE OSTI2017

Measurement of the D + -meson production cross section at low transverse momentum in p p ¯ collisions at s = 1.96 TeV

We report on a measurement of the D + -meson production cross section as a function of transverse momentum (p T ) in proton-antiproton (p$\bar{p}$) collisions at 1.96 TeV center-of-mass energy, using the full data set collected by the Collider Detector at Fermilab in Tevatron Run II and corresponding to 10 fb -1 of integrated luminosity. We use D + →K - π + π + decays fully reconstructed in the central rapidity region |y|<1 with transverse momentum down to 1.5 GeV/c, a range previously unexplored in p$\bar{p}$ collisions. Inelastic p$\bar{p}$ scattering events are selected online using minimally biasing requirements followed by an optimized offline selection. The K - π + π + mass distribution is used to identify the D + signal, and the D + transverse impact-parameter distribution is used to separate prompt production, occurring directly in the hard-scattering process, from secondary production from b-hadron decays. We obtain a prompt D + signal of 2950 candidates corresponding to a total cross section σ(D + ,1.5 T <14.5 GeV/c,|y|<1)=71.9±6.8(stat)±9.3(syst) μb. While the measured cross sections are consistent with theoretical estimates in each p T bin, the shape of the observed p T spectrum is softer than the expectation from quantum chromodynamics. The results are unique in p$\bar{p}$ collisions and can improve the shape and uncertainties of future predictions.

(K-↗
DOE OSTI2021

A Generic Two-Vector Model Predictive Control for Hybrid Multilevel Converters

In this article, a generic two-vector model predictive control (TV-MPC) strategy is proposed for the hybrid multilevel converters (HMCs). The proposed method selects two optimal voltage vectors among all the vector candidates using a geometric positioning approach to reduce the computational burden, which is a common issue in the existing MPC methods for HMC. Then duty cycles of the two selected vectors are optimized to minimize the current tracking error, such that the current tracking performance can be enhanced compared with the conventional MPC. In addition, the voltages of the floating dc capacitors can be balanced by evaluating all switching sequences that belong to the optimal voltage vectors with optimal duty cycles. Here, the concept of the proposed TV-MPC is generic and applicable for any HMCs. A typical HMC based on active neutral-point-clamped topology is adopted as a case study in this work. Comprehensive simulation and experimental studies are performed on an all silicon-carbide HMC prototype to validate the effectiveness of the proposed control scheme.

42 ENGINEERING↗