Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Protocols”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of cycling conditions on lithium-ion battery performance for electric vertical takeoff and landing applications

The development of better electrochemical energy storage systems has sparked significant interest in using Li-ion batteries for electric vertical takeoff and landing (eVTOL) applications. To ensure the optimal performance and safety of onboard batteries, their behavior under different charging/discharging protocols and environmental conditions must be understood. Here, this paper presents a comprehensive evaluation of commercial Li-ion batteries for eVTOL applications, focusing on their responses to varying charging/discharging strategies and mechanical vibrations experienced during flight. Through controlled experiments, the effects of rapid cycling on battery performance were investigated, including effects on lifespan, capacity, and internal resistance. Additionally, the impact of mechanical vibrations on battery behavior was assessed to identify potential challenges for onboard batteries. The results of this study revealed intriguing insights into the interplay between temperature, vibration, and battery performance. This work contributes to the broader adoption of electric aerial transportation, promising a greener and safer future for urban mobility.

18650 cells↗
DOE OSTI2025

Predicting Si-Anode Calendar Life Using Machine Learning: Correlating Electrolyte Properties and Electrochemical Signals

This study evaluates novel electrolytes tailored for Si-containing anodes to promote calendar-life. Drawing inspiration from advancements in electrolytes for Li-metal cells, the work investigates correlations between predicted electrolyte properties and measured electrochemical performance using several machine-learning models. By leveraging machine learning and advanced modeling techniques, this study aims to establish predictive frameworks that accelerate calendar-aging experiments and inform rational electrolyte design for Si-containing cells. In the present study, fifteen different electrolytes are evaluated in a Si-containing cell using an accelerated calendar-life protocol. For each electrolyte considered, 87 properties (features) from the Advanced Electrolyte Model were produced to identify key property/performance relationships. In this study, the best performing electrolytes were generally those formulations that included non-coordinating fluoroether solvents, and the most predictive features for long-term calendar-life were features related to salt concentration and electrolyte viscosity as well as early capacity, ionic conductivity, and Coulombic efficiency measurements. The framework developed in this study correlating electrolyte properties to measured electrochemical performance is expected to accelerate electrolyte design for Si-containing anodes and ultimately enable high-energy-density, long-life Li-ion batteries.

25 - ENERGY STORAGE↗
DOE OSTI2026

An Accelerated Testing and Analysis Framework for Qualification of Battery Materials Part I: A Case Study with LFP Cathodes

The growing demand for batteries used within automotive, aviation, and grid applications has exacerbated the need to supplement critical battery material feedstocks, such as those for anode and cathode active materials. New or supplementary material sources, however, universally comprise unique properties that can affect the lifetime and performance of resultant batteries. Even minor differences between new sources and established supplies can delay qualification, making it difficult for new suppliers to commercialize and resulting in a less resilient supply chain. Accordingly, the influence of composition, microstructure, and morphology on electrochemical performance should be characterized quickly and accurately to accelerate commercialization of new sources. This work introduces a tiered framework to assess new material viability and understand the influence of physicochemical properties on battery performance. The Tier 1 testing described here is rapid and low-effort to recognize materials with fundamental flaws and potentially disqualify them. Later testing would require more effort but provide higher-fidelity information with a goal of application-based validation. A case study examining commercial sources of LiFePO4 (LFP) is presented, using Tier 1 of the protocol to identify rapid electrochemical and physicochemical signals that correlate with performance and provide early go/no-go decisions for LFP materials without requiring long-term cycling.

25 ENERGY STORAGE↗
DOE OSTI2023

An infrared spectral database for gas-phase quantitation of volatile per- and polyfluoroalkyl substances (PFAS)

We report the construction of a database of vetted infrared spectra specifically targeting volatile fluorocarbon gases that may be emitted during thermal treatment of per- and polyfluoroalkyl substances (PFAS) to assist understanding of treatment processes and improve quantification. To populate this database, protocols derived from the Pacific Northwest National Laboratory (PNNL) infrared spectral database are used, curtailing the species selection for this data set. Each spectrum in the database is a weighted average derived from 10 or more individual measurements at different partial pressures (static method) or flow rates (dissemination method) to yield good fidelity of both strong and weak infrared signatures, with each composite spectrum ranging from = 6500 cm-1 to = 600 cm-1 with an apodized resolution of 0.112 cm-1. This resolution was chosen to fully resolve all spectral features, recognizing that atmospheric pressure broadening results in nearly all ro-vibrational lines having linewidths = 0.1 cm-1. As an example case, application of the database is demonstrated via identification and quantification of dominant 1H-perfluoroheptane and perfluorohept-1-ene fluorocarbon products resulting from thermal decomposition of perfluorooctanoate (PFOA) below 450 °C.

Infrared, Gas-phase spectra, FTIR, Spectral databa↗
DOE OSTI2022

Custom-designed heat treatment simultaneously resolves multiple challenges facing 3D-printed single-crystal superalloys

Single-crystal Ni-based superalloys are currently the material of choice for turbine blade applications, especially with the emerging additive manufacturing (AM) that facilitates the manufacture/repair of these single crystals. This promising AM route, however, comes with a dilemma: in the fusion and heat affected zones after e-beam or laser induced melting, one needs a solutionizing annealing to relieve the residual stresses and homogenize the chemical/microstructure. The super-solvus solutionizing temperature is usually adopted from the protocol for the cast superalloys, which almost always causes recrystallization and stray grain growth, resulting in a polycrystalline microstructure and degrading the high-temperature mechanical performance. Here, in this paper, we demonstrate a custom-designed post-printing heat treatment to replace the conventional super-solvus one. The recovery and relatively low temperature diminish the driving force for recrystallization and the movement of stray grain boundaries, without suffocating the chemical/microstructural homogenization thanks to the narrow dendrite width and short element segregation distance. The optimal duration of the heat treatment is proposed to achieve atomic-diffusion mediated chemical homogenization while limiting γ'-particle coarsening in the interdendritic regions. Our strategy makes it practically feasible to resolve several bottleneck problems with one processing/treatment, removing a seemingly formidable obstacle to effective additive manufacturing of superalloy single crystal products.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Robust natural nanocomposites realizing unprecedented ultrafast precise molecular separations

Synthetic polymer membranes can potentially reduce the large energy and carbon footprints that are typically associated with traditional chemical separation technologies. Unfortunately, current production protocols negate the green benefits of membrane separation. To address this bottleneck, here we report the use of natural materials monosaccharide – glucose and polydopamine and Zr-based metal organic frameworks (MOFs) to fabricate ultrathin nanocomposite membranes via interfacial polymerization reaction. The synergistic effect of these three materials on angstrom-scale molecular transport both in organic solvent and aqueous environment was elucidated using a series of complementary techniques. We demonstrate such nature-inspired nanocomposite membranes enable structural stability even in polar aprotic solvents, and unparalleled ultra-fast, low-pressure, precise separations in both nanofiltration modes, which easily surpass state-of-the-art membranes relying on unsustainable materials. Finally, the multi-functionality of saccharide nanocomposites was elegantly harnessed to impact separation applications that contribute towards a better living environment.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Catalysts by pyrolysis: Direct observation of chemical and morphological transformations leading to transition metal-nitrogen-carbon materials

Transition metal-nitrogen-carbon materials (M-N-C catalysts) are promising electrocatalysts in polymer electrolyte fuel cells (PEFCs) and electrolyzer applications. High temperature treatment in inert atmosphere (pyrolysis) is the essential, most common method for the synthesis of M-N-C catalysts and critical to achieve high electrocatalytic activity and electronic conductivity. To this day, despite many uses and successful implementations in materials manufacturing, pyrolysis has been an entirely empirical technology, with process control and optimization relying exclusively on “Edisonian” approach. The knowledge gap in the mechanism about how the precursor is being transformed into catalysts hinders further development of the M-N-C catalysts regardless of the precursor class and processing protocols. In this work, we probed the morphological evolution and chemical transformation of a nitrogen-containing charge transfer organic salt, mixed with transition metal (iron) salt and amorphous silica powder (precursor) during the pyrolysis process via a combination of in situ synchrotron and laboratory-based diagnostic techniques. The pyrolysis process is found to be divided into three stages. During a controlled temperature ramp, the selected organic N-C precursor (nicarbazin) began melting and decomposing just below 400 °C, forming a certain number of micrometer-scale pores and pathways. With increase in temperature from 400 °C to 900 °C, amorphous carbon domains started forming, and reduced (metallic) iron nanoclusters appeared, being dispersed uniformly throughout the carbonaceous matrix. When temperature advanced above 900 °C, graphitization of carbon commenced, associated with appearance and evolution of atomically dispersed metal-nitrogen moieties in the carbonaceous matrix. As the graphitization advanced further, a secondary process of agglomeration of metal nanoparticles occurred. Multi-analytical technique observations conducted here provide a base for rational design and optimization of M-N-C electrocatalysts via pyrolysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ToF-SIMS in material research: A view from nanoscale hydrogen detection

Hydrogen in materials has attracted tremendous interest as its incorporation leads to significant alterations in nanoscale structure, composition, and chemistry, impacting functional properties. It has also been integral to nuclear fusion reactors and is considered a future clean energy source. However, nanoscale characterization and manipulation of hydrogen in materials are challenging as only a selected few analytical techniques can readily detect hydrogen, among which time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a unique and powerful one due to its excellent detection limit along with decent depth and lateral resolutions. Here, in this review, we discuss, using selected examples, how to detect and quantify hydrogen in materials by ToF-SIMS and its impact on revealing the hydrogenation/protonation-induced novel functional states in different classes of materials. In addition, we present our protocols on sample preparation and experimental conditions optimization, allowing us to achieve the best possible results. Finally, we highlight future research directions that can lead to the discovery of novel functional states and ultimately provide a deeper understanding of scientific questions in materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Orientation matters: Measuring the correct surface of polyamide membranes with quartz crystal microbalance

The surface of polyamide reverse osmosis (RO) membranes which regulates interface-dominated phenomena, such as partitioning and fouling, is the one facing the feed during operation. However, the opposite surface of the polyamide selective layer, the one facing the permeate and in contact with the polysulfone porous support, is commonly analyzed in quartz crystal microbalance (QCM) measurements due to limitations of state-of-the-art transfer methodologies. Such measurements on the back surface cannot be generalized because the polyamide layer is chemically and morphologically asymmetric. Herein, we introduce a simple method to coat QCM sensors with polyamide active layers in the correct orientation (i.e., exposing their front surface) and show that interface-dominated phenomena differ significantly between orientations. We start by describing a transfer protocol to coat any surface with a polyamide layer on its front surface orientation. We then systematically analyze the chemical and morphological differences between the two surfaces of the polyamide layer of a commercial RO membrane. Finally, we demonstrate that interface-dominated phenomena depend on the orientation by showing that NaCl partitioning at pH 6 was 1.3 to 2.3-fold higher on the front surface and that organic fouling with humic acid occurred at a lower rate on this surface. The new method presented herein enables measurements on the front surface of polyamide RO membranes, which should be the standard in any future QCM studies.

Fouling behavior↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Rechargeable alkaline zinc–manganese oxide batteries for grid storage: Mechanisms, challenges and developments

Rechargeable alkaline Zn–MnO 2 (RAM) batteries are a promising candidate for grid-scale energy storage owing to their high theoretical energy density rivaling lithium-ion systems (~400 Wh/L), relatively safe aqueous electrolyte, established supply chain, and projected costs below $100/kWh at scale. In practice, however, many fundamental chemical and physical processes at both electrodes make it difficult to achieve commercially competitive energy density and cycle life. In this paper, we present a detailed and timely analysis of the constituent materials, current commercial status, electrode processes, and performance-limiting factors of RAM batteries. We also examine recently reported strategies in RAM and related systems to address these issues through additives and modifications to the electrode materials and electrolyte, special ion-selective separators and/or coatings, and unconventional cycling protocols. We conclude with a critical summary of these developments and discussion of how future studies should be focused toward the goal of energy-dense, scalable, and cost-effective RAM systems.

25 ENERGY STORAGE↗
DOE OSTI2020

New frontiers in atom probe tomography: a review of research enabled by cryo and/or vacuum transfer systems

There has been a recent surge in the use of cryo and/or vacuum specimen preparation and transfer systems that are broadening the scope of research enabled by the microscopy technique of atom probe tomography. This is driven by the fact that, like for many microscopes, the application of atom probe to air and temperature sensitive materials or wet biological specimens has previously been limited by through-air-transfer and through-vacuum-transfer at room temperature. Here we provide an overview of the critical areas of research that require these new transfer and analysis protocols, as well as a review of current advances in transfer devices, environmental cells and glove boxes for controlled sample manipulation. This includes the study of catalysis and corrosion, the application of atom probe to biological samples, the study of liquid-solid interfaces, natural ageing investigations and the analysis of hydrogen in metals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Journal Pre-proof3D printed polylactic acid and acrylonitrile butadiene styrene fluidicstructures for biological applications: tailoring bio-material interfaceviasurface modification

Three-dimensional (3D) printing is a rapidly growing technology that best fits for cell culture and other biological applications due to its potential to build immensely complex structures from customized designs. However, use of 3D printed structures for cell adhesion, proliferation, and activation requires tailoring of surface characteristics. In this context, this work investigates the use of two biocompatible 3D printable polymer materials, Poly-L-lactic Acid (PLA) and Acrylonitrile Butadiene Styrene (ABS) for bio applications, and the effect of their post-printing surface modification processes to achieve desired bio functionality. Three post-printing surface modification techniques, alkaline hydrolysis, ultraviolet ozone plasma irradiation and gold thin film deposition are performed with the objective of introducing useful levels of surface functionalities. Poly-L-lysine (PLL) labelled with FITC chromophore is immobilized on the surface modified samples following standard protocols. The effect of surface roughness and porosity of the 3D printed structures on the polypeptide immobilization is compared on as-printed versus mechanically polished surfaces. Different characterization methods, viz., Fluorescence microscopy, Raman Spectroscopy and UV–vis spectroscopy, are used to study the efficacy of the surface modification and PLL immobilization techniques. Our results demonstrated denser PLL attachment on polished hydrolyzed PLA and ABS surfaces which enables the use of these printable polymers for a range of applications such as tissue scaffolds and microfluidics.

3D Printing, PLA, ABS, Biodegradable Polymer, Surf↗
DOE OSTI2022

Two-step annealing induced structural rejuvenation: A cause for memory effect in metallic glasses

The structural origin of the memory effect is still elusive in glassy materials. Here, in this letter, the memory effect in a series of metallic glasses (MGs) is observed by two step annealing using differential scanning calorimetry (DSC) and molecular dynamics simulations. It demonstrates that the Kovacs peak can be reflected from not only the system potential energy but also the atomic dynamics, showing the memory effect could originate from the formation of more loose packing configurations around mobile atoms by structural rejuvenation in the second step of high temperature annealing. In contrast, the high-low temperature annealing protocol can only induce the monotonic relaxation. Therefore, our results pave a pathway to better understand the origin of memory effect in MGs and other glassy materials from their dynamics and local atomic structure.

Memory effect↗
DOE OSTI2024

Tutorial: Extracting entanglement signatures from neutron spectroscopy

This tutorial is a pedagogical introduction to recent methods of computing quantum spin entanglement witnesses from spectroscopy, with a special focus on neutron scattering on quantum spin systems. We offer a brief introduction to the concepts and equations, define a data analysis protocol, and discuss the interpretation of three entanglement witnesses: one-tangle, two-tangle, and Quantum Fisher Information. We also discuss practical experimental considerations, and give three examples of extracting entanglement witnesses from experimental data: Copper Nitrate, KCuF 3 , and NiPS 3 .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

More buck-per-shot: Why learning trumps mitigation in noisy quantum sensing

Quantum sensing is one of the most promising applications for quantum technologies. However, reaching the ultimate sensitivities enabled by the laws of quantum mechanics can be a challenging task in realistic scenarios where noise is present. While several strategies have been proposed to deal with the detrimental effects of noise, these come at the cost of an extra shot budget. Given that shots are a precious resource for sensing – as infinite measurements could lead to infinite precision – care must be taken to truly guarantee that any shot not being used for sensing is actually leading to some metrological improvement. In this work, we study whether investing shots in error-mitigation, inference techniques, or combinations thereof, can improve the sensitivity of a noisy quantum sensor on a (shot) budget. We present a detailed bias–variance error analysis for various sensing protocols. Our results show that the costs of zero-noise extrapolation techniques outweigh their benefits. We also find that pre-characterizing a quantum sensor via inference techniques leads to the best performance, under the assumption that the sensor is sufficiently stable.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Optimizing lossy state preparation for quantum sensing using Hamiltonian engineering

One of the most prominent platforms for demonstrating quantum sensing below the standard quantum limit is the spinor Bose–Einstein condensate. While a quantum advantage using several tens of thousands of atoms has been demonstrated in this platform, it faces an important challenge: atom loss. Atom loss is a Markovian error process modeled by Lindblad jump operators, and a no-go theorem, which we also show here, states that the loss of atoms in all spin components reduces the quantum advantage to a constant factor. Here, we show that this no-go theorem can be circumvented if we constrain atom losses to a single spin component. Moreover, we show that in this case, the maximum quantum Fisher information with N atoms scales as N 3/2 , establishing that a scalable quantum advantage can be achieved despite atom loss. Although Lindblad jump operators are generally non-Hermitian and non-invertible, we use their Moore–Penrose inverse to develop a framework for constructing several states with this scaling of Fisher information in the presence of losses. We use Hamiltonian engineering with realistic Hamiltonians to develop experimental protocols for preparing these states. Finally, we discuss possible experimental techniques to constrain the losses to a single spin mode.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Timing and synchronization of the DUNE neutrino detector

The DUNE neutrino experiment far detector has a fiducial mass of 40 kt. The O(1 M) readout channels are distributed over the 4 x 10kt modules and need to be synchronized to O(10 ns) with a reliable, simple, affordable system. For the majority of channels a simple DC-balanced protocol is used, with clock and synchronization information encoded on the same fibre. The remaining channels use “White Rabbit” (IEEE-1588). Small scale tests show a timing jitter of <100 ps. The DUNE timing system has been successfully prototyped at the ProtoDUNE-SP detector at CERN.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗