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Results for “Yield function”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Tailoring electrocatalytic activity of in situ crafted perovskite oxide nanocrystals via size and dopant control

Significance The ability to scrutinize the correlation of dimension, composition, and dopant to electrocatalytic performance renders the development of highly active electrocatalysts. This work reports a general and robust strategy for crafting uniform perovskite oxide nanoparticles (i.e., BaTiO 3 and La- and Co-doped BaTiO 3 ) with controlled sizes and dopant compositions by employing amphiphilic star-like diblock copolymers as nanoreactors. Their size- and dopant-dependent oxygen reduction reaction (ORR) performances are unveiled. Particularly, La- and Co-doped BaTiO 3 nanoparticles exhibit markedly improved ORR activities over the pristine counterparts due to reduced free energy barrier of ORR and increased conductivity as substantiated by density functional theory. The nanoreactor strategy could be conveniently extended to yield various functional nanomaterials of interest with tailored sizes and compositions for electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Massively parallel and universal approximation of nonlinear functions using diffractive processors

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront—e.g., via a spatial light modulator (SLM)—and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions–all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering wavelength-multiplexed nonlinear functions as well as multi-variate and complex-valued functions that are all-optically cascadable. Our analysis also indicates the successful approximation of typical nonlinear activation functions commonly used in neural networks, including the sigmoid, tanh, ReLU (rectified linear unit), and softplus. We numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.

Rahman, Md Sadman Sakib [University of California,↗
DOE OSTI2021

Quantifying the impacts of compound extremes on agriculture

Agricultural production and food prices are affected by hydroclimatic extremes. There has been a growing amount of literature measuring the impacts of individual extreme events (heat stress or water stress) on agricultural and human systems. Yet, we lack a comprehensive understanding of the significance and the magnitude of the impacts of compound extremes. This study combines a fine-scale weather product with outputs of a hydrological model to construct functional metrics of individual and compound hydroclimatic extremes for agriculture. Then, a yield response function is estimated with individual and compound metrics, focusing on corn in the United States during the 1981–2015 period. Supported by statistical evidence, the findings suggest that metrics of compound hydroclimatic extremes are better predictors of corn yield variations than metrics of individual extremes. The results also confirm that wet heat is more damaging than dry heat for corn. This study shows the average yield damage from heat stress has been up to four times more severe when combined with water stress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data Reproducibility of Spin-Echo Small-Angle Neutron Scattering Instruments

Spin-echo small-angle neutron scattering (SESANS) is a unique method to measure structures of materials in real space with length scales from ∼ 30 μm to ∼20 µm. As shown in Figure 1, the accessible length scale of SESANS is given by its ability to encode the momentum transfer into the Larmor phase, namely Φ = $\vec{𝛿}$ ⋅ $\vec{𝑄}$, where $\vec{𝑄}$ is the momentum transfer and $\vec{𝛿}$ is the encoding vector of the setup and its projection along Q (δQ) is called spin-echo length (SEL). The spin echo length, which is synonymous with the spatial correlation distance probed, is defined as the following 𝛿𝑄 ∝ 𝜆 2 𝐵𝐿cot𝜃 where 𝜆 is neutron wavelength, B is magnetic field, L is length of the parallelogram magnetic field region, and 𝜃 is the angle between the inclined magnetic field boundary and the beam direction, as shown in Figure 1. The result of the SESANS experiment is a Hankel transformation of the SANS scattering function I(Q), which yields the correlation function of the sample in real space.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Scaling within the spectral function approach

Scaling features of the nuclear electromagnetic response functions unveil aspects of nuclear dynamics that are crucial for interpreting neutrino-and electron-scattering data. In the large momentum-transfer regime, the nucleon-density response function defines a universal scaling function, which is independent of the nature of the probe. In this work, we analyze the nucleon-density response function of 12 C, neglecting collective excitations. We employ particle and hole spectral functions obtained within two distinct many-body methods, both widely used to describe electroweak reactions in nuclei. We show that the two approaches provide compatible nucleon-density scaling functions that for large momentum transfers satisfy first-kind scaling. Both methods yield scaling functions characterized by an asymmetric shape, although less pronounced than that of experimental scaling functions. Finally, this asymmetry, only mildly affected by final state interactions, is mostly due to nucleon-nucleon correlations, encoded in the continuum component of the hole spectral function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Generating shield response functions using a source independent method - 25587

Generalized questions about shield materials are common and yet difficult to answer analytically. Most forms of quick analysis use simple attenuation. The drawback to such methods is the use of mono-energetic averaged cross sections. Averaging a cross section requires knowledge of the flux a priori. If the flux was known, then some more in-depth calculation was performed negating the need for quick scoping calculations. Source independent methods for assessing the transport medium provide a means of creating response functions that yield general statements about the effectiveness of a shielding material. The following paper uses MCNP 6.2 to generate source independent, energy dependent, response functions for the transport medium that allow for quick scoping of effectiveness of various neutron shields. The source independent method here leveraged FT SCX tally treatment, to assess the performance of various shields such that energy response is preserved. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2021

Statistical Multiobjective Optimization of Thiospinel CoNi 2 S 4 Nanocrystal Synthesis via Design of Experiments

Thiospinels, such as CoNi 2 S 4 , are showing promise for numerous applications, including as catalysts for the hydrogen evolution reaction, hydrodesulfurization, and oxygen evolution and reduction reactions; however, CoNi 2 S 4 has not been synthesized as small, colloidal nanocrystals with high surface-area-to-volume ratios. Traditional optimization methods to control nanocrystal attributes such as size typically rely upon one variable at a time (OVAT) methods that are not only time and labor intensive but also lack the ability to identify higher-order interactions between experimental variables that affect target outcomes. Herein, we demonstrate that a statistical design of experiments (DoE) approach can optimize the synthesis of CoNi 2 S 4 nanocrystals, allowing for control over the responses of nanocrystal size, size distribution, and isolated yield. After implementing a 2 5–2 fractional factorial design, the statistical screening of five different experimental variables identified temperature, Co:Ni precursor ratio, Co:thiol ratio, and their higher-order interactions as the most critical factors in influencing the aforementioned responses. Second-order design with a Doehlert matrix yielded polynomial functions used to predict the reaction parameters needed to individually optimize all three responses. A multiobjective optimization, allowing for the simultaneous optimization of size, size distribution, and isolated yield, predicted the synthetic conditions needed to achieve a minimum nanocrystal size of 6.1 nm, a minimum polydispersity (σ/$\bar{d}$) of 10%, and a maximum isolated yield of 99%, with a desirability of 96%. The resulting model was experimentally verified by performing reactions under the specified conditions. Furthermore, our work illustrates the advantage of multivariate experimental design as a powerful tool for accelerating control and optimization in nanocrystal syntheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Improved loss functions for machine-learned atomic potentials

Machine learning (ML) has become an invaluable tool across a wide array of domains in science as researchers find new ways to leverage its predictive power. This is especially true in chemistry, where ML is used to fit chemical properties or desirable attributes to the local structure of molecules and materials. In the pursuit of greater accuracy, it is relatively simple to increase the size or complexity of such models, although this often requires simultaneously seeking larger datasets in order to both fit and interpret the larger number of parameters. However, it is equally important to assess the quality and relative importance of the data and how these factors impact the training process. We, therefore, investigate the impact of using different loss functions for training neural network potentials (NNPs), as the loss function defines the error and parameter gradients used to train the NNP. In particular, we test the mean-squared error and Huber loss functions and, using insight from these functions, derive a new loss function based on the Asinh function, which yields significant improvement in the accuracy and generality of NNPs. We show that by discounting/minimizing errors and anomalies in the optimization process, both the Huber and Asinh loss functions improve the training of NNPs, leading to a final potential with a greater effective dimensionality.

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

Time‐Dependent Density Functional Theory of Narrow Band Gap Semiconductors Using a Screened Range‐Separated Hybrid Functional

Abstract Predicting the band structure and optical absorption spectra of narrow band gap semiconductors is challenging for electronic structure methods. Here, it is shown shown that density functional theory can yield accurate band structures and time‐dependent density functional theory (TDDFT) can yield accurate optical absorption spectra for these systems. This is achieved by using a screened range‐separated hybrid (SRSH) functional with a single empirical parameter, fit to reproduce the experimental band gap. By comparing TDDFT results based on the SRSH approach with those obtained based on the Heyd–Scuseria–Ernzerhof functional it is shown that screened long‐range exact exchange improves the accuracy of the TDDFT spectra for these systems.

Wing, Dahvyd↗
DOE OSTI2022

Data for Determining Spatially Varying Profit-Maximizing Management Practices for Miscanthus and Switchgrass Production in the Rainfed United States

The compiled datasets include county-level variables used for simulating miscanthus and switchgrass production in 2287 counties across the rainfed US including 5-year (2012-2016) averaged growing season degree days (GDD), 5-year (2012-2016) averaged growing season cumulative precipitation, National Commodity Crop Productivity Index (NCCPI) values, regional dummies (only for miscanthus), the regional-level random effect of the yield response function, N price, land cash rent, the first year fixed cost (only for switchgrass), and separate datasets for simulating an alternative model assuming a constant N rate. The GAMS codes are used to run the simulation to obtain the main results including the age-varying profit-maximizing N rate, biomass yields, and annual profits for miscanthus and switchgrass production across counties in the rainfed US. The STATA codes are used to merge and analyze simulation results and create summary statistics tables and key figures.

Age↗
DOE OSTI2026

A divergent synthetic route to functional copolymer libraries via modular polymers

High-throughput polymer synthesis enables rapid exploration of chemical space but remains limited by batch-to-batch inconsistencies that can obscure structure–property relationship trends. To address this challenge, we developed a synthetic approach to produce multifunctional copolymers using post-polymerization modification of activated ester modular polymers with commercially available amines. Easily derivitized parent polymers—poly(tetrafluorophenyl acrylate) and poly(tetrafluorophenyl styrene sulfonate)—were synthesized by RAFT polymerization to yield single polymer batches containing highly reactive tetrafluorophenyl esters or sulfonate esters on each repeat unit. Tuning post-polymerization modification reaction conditions enabled the addition of sub-stoichiometric amounts of amines (relative to the repeat unit) to yield partially functionalized intermediates that could then be further derivatized. Reaction monitoring by 19 F NMR spectroscopy confirmed good control over these sequential post-polymerization modifications. This synthetic route produced a variety of copolymers with defined comonomer ratios while preserving the underlying polymer structure (degree of polymerization, dispersity, tacticity) for both the acrylate and styrene sulfonate backbones. We further applied this approach in a divergent manner to create a small library of structurally distinct copolymers from a single parent batch in three synthetic steps. This modular, divergent synthesis demonstrates a general route to structurally consistent copolymer libraries that enable systematic studies of structure–property relationships and can accelerate functional materials discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Comparing Model Representations of Physiological Limits on Transpiration at a Semi-arid Ponderosa Pine Site

Mechanistic representations of biogeochemical processes in ecosystem models are rapidly advancing, requiring advancements in model evaluation approaches. Here we quantify multiple aspects of model functional performance to evaluate improved process representations in ecosystem models. We compare semi-empirical stomatal models with hydraulic constraints against more mechanistic representations of stomatal and hydraulic functioning at a semi-arid pine site using a suite of metrics and analytical tools. We find that models generally perform similarly under unstressed conditions, but performance diverges under atmospheric and soil drought. The more empirical models better capture synergistic information flows between soil water potential and vapor pressure deficit to transpiration, while the more mechanistic models are overly deterministic. Although models can be parameterized to yield similar functional performance, alternate parameterizations could not overcome structural model constraints that underestimate the unique information contained in soil water potential about transpiration. Additionally, both multilayer canopy and big-leaf models were unable to capture the magnitude of canopy temperature divergence from air temperature, and we demonstrate that errors in leaf temperature can propagate to considerable error in simulated transpiration. This study demonstrates the value of merging underutilized observational data streams with emerging analytical tools to characterize ecosystem function and discriminate among model process representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A stable 15-member bacterial SynCom promotes Brachypodium growth under drought stress

Introduction: Rhizosphere microbiomes are known to drive soil nutrient cycling and influence plant fitness during adverse environmental conditions. Field-derived robust Synthetic Communities (SynComs) of microbes mimicking the diversity of rhizosphere microbiomes can greatly advance a deeper understanding of such processes. However, assembling stable, genetically tractable, reproducible, and scalable SynComs remains challenging. Methods: Here, we present a systematic approach using a combination of network analysis and cultivation-guided methods to construct a 15-member SynCom from the rhizobiome of Brachypodium distachyon. This SynCom incorporates diverse strains from five bacterial phyla. Genomic analysis of the individual strains was performed to reveal encoded plant growth-promoting traits, including genes for the synthesis of osmoprotectants (trehalose and betaine) and Na+/K+ transporters, and some predicted traits were validated by laboratory phenotypic assays. Results: The SynCom demonstrates strong stability both in vitro and in planta. Most strains encoded multiple plant growth-promoting functions, and several of these were confirmed experimentally. The presence of osmoprotectant and ion transporter genes likely contributed to the observed resilience of Brachypodium to drought stress, where plants amended with the SynCom recovered better than those without. We further observed preferential colonization of SynCom strains around root tips under stress, likely due to active interactions between plant root metabolites and bacteria. Discussion: Our results demonstrate that trait-informed construction of synthetic communities can yield stable, functionally diverse consortia that enhance plant resilience under drought. Preferential colonization near root tips points to active, localized plant-microbe signaling as a component of stress-responsive recruitment. This stable SynCom provides a scalable platform for probing mechanisms of plant-microbe interaction and for developing microbiome-based strategies to improve soil and crop performance in variable environments.

Yadav, Archana↗
DOE OSTI2025

Tetracene Functionalized Si(111) Achieves Enhanced Solar-to-Chemical Energy Conversion via Molecular Acceptor States

The properties of semiconductor|liquid interfaces play a critical role in determining the efficiency of solar-to-hydrogen (STH) conversion. Here, we investigate how molecular functionalization of Si(111) and Si(111)|TiO 2 surfaces impacts photoelectrochemical (PEC) hydrogen production efficiency. We find that functionalization of ∼3% of the atop sites of Si(111) with either 9-anthracene (Anth) or 5-tetracene (Tet), with the remaining sites passivated by methyl groups, provides substrates with high electronic quality and low surface oxide densities, as determined by X-ray photoelectron spectroscopy (XPS) measurements. Surface photovoltage (SPV) spectroscopy shows that surfaces modified with Anth or Tet exhibit an increased photovoltage, with Tet-functionalized surfaces yielding an additional 192 meV relative to methyl-terminated Si(111), indicating improved charge separation for Si-Tet. Further improvement in onset potential was achieved by replacing a nitrogen-containing TiO 2 atomic layer deposition (ALD) precursor (TDMAT) with a precursor lacking nitrogen (TTIP), which eliminates the parasitic defect band in the TiO 2 overlayer (p-Si(111)-Tet|TTIP-TiO 2 |Pt: V OC = +0.283 ± 0.041 V vs RHE). Density functional theory (DFT) analysis demonstrates that compared with Anth-modified Si(111), the Tet-modified surface exhibits more hybridized Si(111)-Tet states closer to the silicon band edges. Mercury contact current–voltage (I–V, dark) measurements quantified the relative interfacial density of states of Si-Tet, Si-Anth and Si-Me surfaces─revealing that the interfacial state density was highest for Si-Tet. This suggests that such hybridized interfaces serve to capture better photoexcited charge, which enables facile electron transfer to molecular acceptors in solution. Altogether, the data indicate that beneficial hybrid molecular LUMO surface states interacting with the Si conduction band edge results in improved hydrogen evolution (HER) performance for p-Si devices.

Group theory↗
DOE OSTI2018

Modeling the physisorption of graphene on metals

Many processes of technological and fundamental importance occur on surfaces. Adsorption is one of these phenomena that has received the most attention. However, it presents a great challenge to conventional density functional theory. By starting with the Lifshitz-Zaremba-Kohn second-order perturbation theory, we develop a long-range van der Waals (vdW) correction for physisorption of graphene on metals. The model importantly includes quadrupole-surface interaction and screening effects. The results show that, when the vdW correction is combined with the Perdew-Burke-Enzerhof functional, it yields adsorption energies in good agreement with the random-phase approximation, significantly improving upon other vdW methods. We also find that, compared with the leading-order interaction, the higher-order quadrupole-surface correction accounts for about 25$\%$ of the total vdW correction, suggesting the importance of the higher-order term.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A matheuristic for design and dispatch of a utility-connected distributed energy system

Modeling distributed power generation systems often requires complicated mathematical expressions that present challenges for commercial optimization solvers. Here, this paper presents a matheuristic to solve a mixed-integer optimization model that informs decisions regarding the design and dispatch of a utility-connected microgrid. We deploy a genetic algorithm to search the system design space and a linear program to solve the economic dispatch problem. The model is a component of a web tool that requires solutions within a few minutes. Our method yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of our test cases compared to only 10% of our test cases by a traditional optimization solver in the same amount of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Large-scale production of 88 Y and 88 Zr/ 88 Y generators: A proof of concept study for a 70 MeV H – cyclotron

Here, the large-scale production of 88 Y with proton-induced reactions has been investigated from the perspective of new generation 70 MeV H – cyclotrons. Tandem target configurations are presented for both the direct production of 88 Y as well as for producing 88 Zr/ 88 Y generators. Based on the relevant excitation functions, physical yields have been derived for 88 Y production with Y 2 O 3 /SrCO 3 tandem targets and 88 Zr production with Zr/Y 2 O 3 tandem targets. Yields are presented for optimized targets (i.e. optimum yield) as well as for balanced thermal loads on the individual targets. Liquid 88 Zr/ 88 Y generators have been produced using both natural Zr and Nb target materials, the former for dedicated productions and the latter as a byproduct by processing spent irradiated Nb capsules which normally would constitute radioactive waste. These stock solutions, which contain both the target material and 88 Zr precursor, are retained virtually unchanged after processing except for the removal of 88 Y on AG MP-50 macroporous cation-exchange resin. Methods are presented for the preparation of Nb stock solutions in hydrofluoric acid and Zr stock solutions in sulfuric acid. It is shown that multi-Ci productions of 88 Y are feasible at a 70 MeV cyclotron facility, suitable for the needs of fracking applications. In addition, 88 Zr/ 88 Y generators can provide 88 Y with very high specific activity, suitable for labelling of biomolecules.

07 ISOTOPE AND RADIATION SOURCES↗