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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 1,333 records · Page 74

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DOE OSTI2024

Installation protocol for charge transfer dissociation mass spectrometry on ion trapping mass spectrometers

Abstract Rationale Charge transfer dissociation (CTD) is a novel fragmentation technique that demonstrates enhanced structural characterization for a wide variety of molecules compared to standard fragmentation techniques like collision‐induced dissociation (CID). Alternative fragmentation techniques, such as electron transfer dissociation, electron capture dissociation, and ultraviolet photodissociation, also overcome many of the shortfalls of CID, but none of them are a silver bullet that can adequately characterize a wide variety of structures and charge states of target compounds. Given the diversity of structural classes and their occasional obstinance towards certain activation techniques, alternative fragmentation techniques are required that rely on novel or alternative modes of activation. Methods Herein, we present a step‐by‐step protocol for the installation of CTD on a quadrupole ion trap mass spectrometer and best practices for optimizing the signal‐to‐noise ratio and acquisition times for CTD mass spectra. Results In addition to two CTD installations in the Jackson laboratory, CTD has also been installed, and is currently in operation, on two 3D ion trap mass spectrometers in France: one in the laboratory of Dr. David Ropartz and Dr. Hélène Rogneaux at INRAE in Nantes, and the other in the laboratory of Dr. Jean‐Yves Salpin at Université d'Évry Val‐d'Essonne, part of the Paris‐Saclay University system. Conclusions Here, we provide a visual protocol to help others accomplish the instrument modification.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Rapid In Situ Ligand‐Exchange Process Used to Prepare 3D PbSe Nanocrystal Superlattice Infrared Photodetectors

Abstract Colloidal semiconductor nanocrystals are important building blocks for low‐cost, solution‐processed electronic devices with tunable functionalities. Considerable progress is made in improving charge transport through nanocrystal films by exchanging long insulating ligands with shorter passivating ligands. To take full advantage of this strategy, it is equally important to fabricate close‐packed structures that reduce the average interparticle spacing. Yet it remains a challenge to retain long‐range, close‐packed order after ligand exchange. Here, a novel one‐step in situ ligand‐exchange method is demonstrated that enables rapid (5 min) ligand exchange of nanocrystal films, which are more than 50 layers thick. Using this simple and efficient method, it is shown that the face‐centered cubic ordering of 500 nm thick PbSe nanocrystal films is retained after ligand exchange from oleic acid to benzoic acid. Moreover, it is demonstrated that PbSe nanocrystal photodetectors with a well‐ordered structure have superior optoelectronic properties compared to disordered films; ordered films have a 16× higher responsivity of ≈0.25 A W −1 at 1 V and a 2× faster response time. As far as it is known, this is the first report to realize a rapid one‐step ligand exchange through a thick superlattice film with retention of long‐range order.

infrared detecton↗

DOE OSTI2022

3D LiMn 2 O 4 nThin Film Deposited by ALD: A Road toward High-Capacity Electrode for 3D Li-Ion Microbatteries

Miniaturized electronics suffer from a lack of energy autonomy. In that context, the fabrication of lithium-ion solid-state microbatteries with high performance is mandatory for powering the next generation of portable electronic devices. Here, the fabrication of a thin film positive electrode for 3D Li-ion microbatteries made by the atomic layer deposition (ALD) method and in situ lithiation step is demonstrated. The 3D electrodes based on spinel LiMn 2 O 4 films operate at high working potential (4.1 V vs Li/Li + ) and are capable of delivering a remarkable surface capacity (approximate to 180 mu Ah cm -2 ) at low C-rate while maintaining more than 40 mu Ah cm -2 at C/2 (time constant = 2 h). Both the thickness of the electrode material and the 3D gain of the template are carefully tuned to maximize the electrode performance. Further, advanced characterization techniques such as transmission electron and X-ray transmission microscopies are proposed as perfect tools to study the conformality of the deposited films and the interfaces between each layer: no interdiffusion or segregation are observed. This work represents a major issue towards the fabrication of 3D-lithiated electrode by ALD-without any prelithiation step by electrochemical technique-making it an attractive solution for the fabrication of 3D Li-ion solid-state microbatteries with semiconductor processing methods.

3D Li-ion micro-batteries↗

DOE OSTI2022

Monolayer Plasmonic Nanoframes as Large‐Area, Broadband Metasurface Absorbers

Abstract Broadband absorbers are useful ultraviolet protection, energy harvesting, sensing, and thermal imaging. The thinner these structures are, the more device‐relevant they become. However, it is difficult to synthesize ultrathin absorbers in a scalable and straightforward manner. A general and straightforward synthetic strategy for preparing ultrathin, broadband metasurface absorbers that do not rely on cumbersome lithographic steps is reported. These materials are prepared through the surface‐assembly of plasmonic octahedral nanoframes (NFs) into large‐area ordered monolayers via drop‐casting with subsequent air‐drying at room temperature. This strategy is used to produce three types of ultrathin broadband absorbers with thicknesses of ≈200 nm and different lattice symmetries (loose hexagonal, twisted hexagonal, dense hexagonal), all of which exhibit efficient light absorption (≈90%) across wavelengths ranging from 400–800 nm. Their broadband absorption is attributed to the hollow morphologies of the NFs, the incorporation of a high‐loss material (i.e., Pt), and the strong field enhancement resulting from surface assembly. The broadband absorption is found to be polarization‐independent and maintained for a wide range of incidence angles (±45°). The ability to design and fabricate broadband metasurface absorbers using this high‐throughput surface‐based assembly strategy is a significant step toward the large‐scale, rapid manufacturing of nanophotonic structures and devices.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Hierarchically Templated Synthesis of 3D‐Printed Crosslinked Cyclodextrins for Lycopene Harvesting

Abstract Plants produce a wide range of bioactive phytochemicals, such as antioxidants and vitamins, which play crucial roles in aging prevention, inflammation reduction, and reducing the risk of cancer. Selectively harvesting these phytochemicals, such as lycopene, from tomatoes through the adsorption method is cost‐effective and energy efficient. In this work, a templated synthesis of 3D‐printed crosslinked cyclodextrin polymers featuring nanotubular structures for highly selective lycopene harvesting is reported. Polypseudorotaxanes formed by triethoxysilane‐based telechelic polyethylene glycols and α‐cyclodextrins (α‐CDs) are designed as the template to (1) synthetically access urethane‐based nanotubular structures at the molecular level, and (2) construct 3D‐printed architectures with designed macroscale voids. The polypseudorotaxane hydrogels showed good rheological properties for direct ink writing, and the 3D‐printed hydrogels were converted to the desired α‐CD polymer network through a three‐step postprinting transformation. The obtained urethane‐crosslinked α‐CD monoliths possess nanotubular structures and 3D‐printed voids. They selectively adsorb lycopene from raw tomato juice, protecting lycopene from photo‐ or thermo‐degradations. This work highlights the hierarchically templated synthesis approach in developing functional 3D‐printing materials by connecting the bottom‐up molecular assembly and synthesis with the top‐down 3D architecture control and fabrication.

Chemistry↗

DOE OSTI2026

Decoding α-MoC 1− x Nanoparticle Formation in Continuous Flow via Machine Learning

Molybdenum carbide nanoparticles (α-MoC 1−x NPs) are promising catalysts that offer noble-metal-like performance at lower cost. We report a mild continuous-flow synthesis of α-MoC 1−x NPs from Mo(CO) 6 , coupled with in-line spectroscopic monitoring and machine learning (ML)-based analysis to quantify precursor conversion and product formation in real time. A multilayer perceptron ML model was found to accurately deconvolute complex, nonlinear spectral patterns, enabling identification of a two-step reaction pathway, involving precursor conversion to an amorphous intermediate followed by intraparticle crystallization to α-MoC 1−x NPs, with the first step being rate limiting. Ex situ small angle X-ray scattering (SAXS) and X-ray diffraction (XRD) validation confirm the predicted concentration profiles and crystallization behavior. This integrated approach showcases how ML can empower insights into NP nucleation and growth, paving the way for self-driving, flow-based platforms for NP synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Improved Primary Reference Cell Calibrations for Higher Accuracy Photovoltaic Cell and Module Performance Measurements

The adoption of photovoltaic (PV) modules for clean electricity relies on accurate measurements of their performance, which are essential for estimating their energy production potential. Herein, the calibration chain of PV cells and modules, with particular emphasis on primary reference cell calibrations, is discussed. Also, herein, the direct sunlight method the group has developed for these calibrations is presented and critical improvements and upgrades that lead to calibration uncertainty as low as 0.45% are discussed. The ultimate motivation behind this work is to provide low‐uncertainty performance measurements of PV modules, and lowering the calibration uncertainty of primary reference cells is a key first step toward achieving this goal. As the use of solar electricity continues to grow, the demand for primary reference cell calibrations inevitably increases beyond what the small handful of primary calibration laboratories can provide today. Therefore, this work can serve as a useful guide for implementing primary PV reference cell calibrations using the outdoor method, as well as outlining the critical elements required to make these calibrations highly accurate.

Osterwald, Carl R.↗

DOE OSTI2023

Seed‐Assisted Growth for Scalable and Efficient Perovskite Solar Modules

Perovskite solar modules (PSMs) have shown remarkable photovoltaic potentials, but they still suffer from large power conversion efficiency (PCE) loss on scale‐up and instability due to inferior uniformity and crystallization over large areas. Herein, the scalable production of efficient and stable PSMs using a suite of all‐scalable fabrication methods featuring a two‐step blade/dip‐coating approach to deposit the perovskite absorber layer is demonstrated. Rubidium chloride is introduced to embed (PbI 2 ) 2 RbCl complex seeds in the first‐deposited PbI 2 precursor, which assists in uniform crystallization of the perovskite layer with high crystallinity and reduced defect density over large areas. Following the optimization of RbCl additives, a champion PSM with 17.9% PCE on a 7.6 × 7.6 cm 2 substrate with a 37 cm 2 aperture area is achieved. Moreover, the RbCl‐incorporated PSMs demonstrate excellent reproducibility and stability under continuous 1 sun illumination. This work shows that the two‐step blade/dip coating is a promising method for producing high‐efficiency and stable PSMs on an industrially relevant scale.

Energy & Fuels↗

DOE OSTI2022

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗

DOE OSTI2025

Use of Frit‐Disc Crucible Sets to Make Solution Growth More Quantitative and Versatile

The recent availability of step‐edge, frit‐disc crucible sets (generally sold as Canfield Crucible Sets or CCS) has led to multiple innovations associated with the group's use of solution growth. The use of CCS allows for the clean separation of liquid from solid phases during the growth process. This clean separation enables the reuse of the decanted liquid, either allowing for simple, economic, savings associated with recycling expensive precursor elements or allowing for the fractionation of a growth into multiple, small steps, revealing the progression of multiple solidifications. Clean separation of liquid from solid phases also allows for the determination of the liquidus line (or surface) and the creation, or correction, of composition–temperature phase diagrams. The reuse of clean decanted liquid has also allowed to prepare liquids ideally suited for the growth of large single crystals of specific phases by tuning the composition of the melt to the optimal composition for growth of the desired phase, often with reduced nucleation sites. Finally, it is discussed how solution growth and CCS use can be harnessed to provide a plethora of composition–temperature data points defining liquidus lines or surfaces with differing degrees of precision to either test or anchor artificial intelligence and/or machine‐learning‐based attempts to augment and extend the limited experimentally determined database.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Characterization of Mammalian In Vivo Enhancers Using Mouse Transgenesis and CRISPR Genome Editing [Book Chapter]

Embryonic morphogenesis is strictly dependent on tight spatiotemporal control of developmental gene expression, which is typically achieved through the concerted activity of multiple enhancers driving cell type-specific expression of a target gene. Mammalian genomes are organized in topologically associated domains, providing a preferred environment and framework for interactions between transcriptional enhancers and gene promoters. While epigenomic profiling and three-dimensional chromatin conformation capture have significantly increased the accuracy of identifying enhancers, assessment of subregional enhancer activities via transgenic reporter assays in mice remains the gold standard for assigning enhancer activity in vivo. Once this activity is defined, the ideal method to explore the functional necessity of a transcriptional enhancer and its contribution to target gene dosage and morphological or physiological processes is deletion of the enhancer sequence from the mouse genome. Here we present detailed protocols for efficient introduction of enhancer-reporter transgenes and CRISPR-mediated genomic deletions into the mouse genome, including a step-by-step guide for pronuclear microinjection of fertilized mouse eggs. We provide instructions for the assembly and genomic integration of enhancer-reporter cassettes that have been used for validation of thousands of putative enhancer sequences accessible through the VISTA enhancer browser, including a recently published method for robust site-directed transgenesis at the H11 safe-harbor locus. Together, these methods enable rapid and large-scale assessment of enhancer activities and sequence variants in mice, which is essential to understand mammalian genome function and genetic diseases.

cis-regulatory elements↗

DOE OSTI2021

Formative vs. Summative Dependence in Human Reliability Analysis

Dependence in human reliability analysis (HRA) is the concept that once an initial human error has occurred, subsequent human errors are more likely. The approach almost universally adopted in HRA was first introduced in the Technique for Human Error Rate Prediction (THERP). In THERP, calculated human error probabilities (HEPs) are adjusted for dependence in the final step of quantification. This final adjustment for dependence involves anchoring the HEP to a set of values corresponding to low through complete dependence. The effect is to increase the HEP. In this paper, we propose formative dependence, which occurs at the onset of quantification. We demonstrate that dependence should be considered earlier in the calculation process, because it is not actually necessary to calculate the HEP when it is subsequently overridden by the dependence anchors. By applying dependence first in the calculation, processing steps can be eliminated, making for more efficient analysis.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Environmental Benefits of Closing the Solar Manufacturing and Recycling Loop: Preparation of Solar Manufacturing Inventories

The cumulative global solar panel waste stream is projected to reach between 60 and 78 million tonnes by 2050. Steps towards developing, demonstrating, and implementing processes that recover glass, metals, and semiconductor materials from end-of-life solar panels have already been taken. However, these processes result in the downcycling of most secondary solar materials. Critically, the costs and benefits of capturing these secondary materials for use in new solar panels are unknown. To evaluate the environmental benefit associated with solar material recycling and reuse in next generation panels, prior inventories must be updated and prepared for integration with recycling processes to examine the benefit of closing the material loop between solar panel end-of-life and new panel manufacturing. This current work describes steps taken to upgrade existing inventories that detail the manufacturing of cadmium-telluride (CdTe) panels from the Ecoinvent -v2.2 life cycle inventory database to Ecoinvent -v3. During this update, material inventories were modified to capture different realistic material supply chains within the constraints of Ecoinvent -v3. Materials discussed in detail in this work include primary flat glass, aluminum, steel, copper, and CdTe. This work demonstrated that environmental indicators such as embodied carbon, acidification, and terrestrial eutrophication associated with solar panel production can be reduced by 25% to over 40% through improved primary material sourcing.

CdTe solar panels↗

DOE OSTI2023

Toward an Autonomous Workflow for Single Crystal Neutron Diffraction

The operation of the neutron facility relies heavily on beamline scientists. Some experiments can take one or two days with experts making decisions along the way. Leveraging the computing power of HPC platforms and AI advances in image analyses, here we demonstrate an autonomous workflow for the single-crystal neutron diffraction experiments. The workflow consists of three components: an inference service that provides real-time AI segmentation on the image stream from the experiments conducted at the neutron facility, a continuous integration service that launches distributed training jobs on Summit to update the AI model on newly collected images, and a frontend web service to display the AI tagged images to the expert. Ultimately, the feedback can be directly fed to the equipment at the edge in deciding the next-step experiment without requiring an expert in the loop. With the analyses of the requirements and benchmarks of the performance for each component, this effort serves as the first step toward an autonomous workflow for real-time experiment steering at ORNL neutron facilities.

Yin, Junqi↗

DOE OSTI2023

Loop-by-loop differential equations for dual (elliptic) Feynman integrals

We present a loop-by-loop method for computing the differential equations of Feynman integrals using the recently developed dual form formalism. We give explicit prescriptions for the loop-by-loop fibration of multi-loop dual forms. Then, we test our formalism on a simple, but non-trivial, example: the two-loop three-mass elliptic sunrise family of integrals. We obtain an ε-form differential equation within the correct function space in a sequence of relatively simple algebraic steps. In particular, none of these steps relies on the analysis of q-series. Then, we discuss interesting properties satisfied by our dual basis as well as its simple relation to the known ε-form basis of Feynman integrands. The underlying K3-geometry of the three-loop four-mass sunrise integral is also discussed. Finally, we speculate on how to construct a “good” loop-by-loop basis at three-loop.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Generalizing the relativistic quantization condition to include all three-pion isospin channels

We present a generalization of the relativistic, finite-volume, three-particle quantization condition for non-identical pions in isosymmetric QCD. The resulting formalism allows one to use discrete finite-volume energies, determined using lattice QCD, to constrain scattering amplitudes for all possible values of two- and three-pion isospin. As for the case of identical pions considered previously, the result splits into two steps: the first defines a non-perturbative function with roots equal to the allowed energies, E n (L), in a given cubic volume with side-length L. This function depends on an intermediate three-body quantity, denoted K d f , 3 , which can thus be constrained from lattice QCD in- put. The second step is a set of integral equations relating K d f , 3 to the physical scattering amplitude, M 3 . Both of the key relations, En(L) ↔ K d f , 3 and K d f , 3 ↔ M 3 , are shown to be block-diagonal in the basis of definite three-pion isospin, Iπππ , so that one in fact recovers four independent relations, corresponding to Iπππ = 0, 1, 2, 3. We also provide the generalized threshold expansion of K d f , 3 for all channels, as well as parameterizations for all three-pion resonances present for Iπππ = 0 and Iπππ = 1. As an example of the utility of the generalized formalism, we present a toy implementation of the quantization condition for Iπππ = 0, focusing on the quantum numbers of the ω and h 1 resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Fitting a deep generative hadronization model

Hadronization is a critical step in the simulation of high-energy particle and nuclear physics experiments. As there is no first principles understanding of this process, physically-inspired hadronization models have a large number of parameters that are fit to data. Deep generative models are a natural replacement for classical techniques, since they are more flexible and may be able to improve the overall precision. Proof of principle studies have shown how to use neural networks to emulate specific hadronization when trained using the inputs and outputs of classical methods. However, these approaches will not work with data, where we do not have a matching between observed hadrons and partons. In this paper, we develop a protocol for fitting a deep generative hadronization model in a realistic setting, where we only have access to a set of hadrons in data. Our approach uses a variation of a Generative Adversarial Network with a permutation invariant discriminator. We find that this setup is able to match the hadronization model in Herwig with multiple sets of parameters. This work represents a significant step forward in a longer term program to develop, train, and integrate machine learning-based hadronization models into parton shower Monte Carlo programs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

An Adaptive Geometry-Free Thermo-Mechanical Model for Directed Energy Deposition Process Modeling

This presentation describes a novel, geometry-free thermo-mechanical model with adaptive subdomain con- struction to accurately predict the thermal conditions, distortions, and residual stresses throughout the directed energy deposition (DED) process. A novel finite element workflow is designed to con- duct the numerical analysis, based on the multi-app and data transfer capabilities in the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE). Unlike with traditional methods, the part geometry in this model is not predefined. Instead, it is a combined effect of the processing parameters and material properties. At each time step, the model utilizes a subdomain construction paradigm to model the material deposition. A specialized mesh adaptivity scheme is incorporated to provide an accurate prediction while reducing the overall computational cost. The results generated by the proposed model show general agreement with the experimental measurements for the single track scan with varying processing parameters and demonstrate reasonable predictions for higher material buildups.

36 MATERIALS SCIENCE↗