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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Navigating the obstacles of carbon-negative technologies

Nine years after the Paris Agreement was adopted, it is clear that negative-emission technologies are required to keep 1.5°C, or even 2°C, of global warming in reach. Yet carbon dioxide removal (CDR) strategies remain rife with political, technical, economic, environmental, and geographic challenges. Here, this Voices surveys the pitfalls of incorporating carbon-negative technologies into climate mitigation plans and asks: how can we navigate around the challenges to make CDR a reliable component of climate mitigation?

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Rigor and Reproducibility in Electrocatalysis: Best Practices for Operando Studies

Operando measurements have rapidly expanded the scope of electrocatalysis by enabling direct observation of catalytic interfaces under working conditions and by linking structural, compositional, and spectroscopic observables to activity and selectivity. However, the growth of operando methods has outpaced the adoption of broadly shared experimental standards, creating persistent challenges in reproducibility, interpretation, and comparison across laboratories and platforms. This perspective synthesizes discussions from the 2025 National Science Foundation Workshop on Rigor and Reproducibility in Electrocatalysis and outlines a practical framework for the rigorous use of operando measurements in electrocatalysis. We highlight three recurring needs: careful implementation of complex methods to avoid overinterpretation; recognition that (subtle) differences in reactor architecture, hydrodynamics, and electrical boundary conditions can alter apparent kinetics and selectivity; and transparent reporting standards that enable meaningful cross-comparison without constraining measurement-specific cell innovation. Focusing on widely used techniques (including X-ray and vibrational spectroscopies, mass spectrometry, and electron microscopy), we discuss technique-specific pitfalls, cross-validation strategies, and recurring platform-agnostic considerations such as mass transport, current distribution, temporal-resolution mismatches, and catalyst evolution. This Perspective aims to strengthen the mechanistic inference and improve the reproducibility, comparability, and predictive value of operando electrocatalysis research.

X-ray absorption spectroscopy↗
DOE OSTI2026

Bioorthogonal Click Chemistry for Antibody-Free Profiling of Acetylation, Propionylation, and Butyrylation in Pseudomonas aeruginosa and Methicillin-Resistant Staphylococcus aureus

Lysine acylation is a posttranslational modification (PTM) conserved in all domains of life and is essential for regulating diverse biological processes. Traditional methods for investigating acylation rely on anti-acyl-lysine antibodies, which are costly and time-consuming and often exhibit variable affinity. To remedy these pitfalls, we developed an antibody-free method for bacterial acylome enrichment using bioorthogonal click chemistry coupled with tandem mass spectrometry. We applied this approach to the pathogens Pseudomonas aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) to explore the biological significance of acylation in each organism. We characterized the acetylome, propionylome, and butyrylome in P. aeruginosa UCBPP-PA14 and the acetylome and propionylome in MRSA. Comparative analyses revealed unique PTM dynamics showing that acylation regulated a wide range of cellular functions, including metabolism, antibiotic resistance, virulence, and stress response. This work establishes the first antibody-free enrichment method for defining bacterial acylomes and provides new insight into global lysine acylation networks in pathogenic bacteria.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Missing microbial eukaryotes and misleading meta-omic conclusions

Meta-omics is commonly used for large-scale analyses of microbial eukaryotes, including species or taxonomic group distribution mapping, gene catalog construction, and inference on the functional roles and activities of microbial eukaryotes in situ. Here, we explore the potential pitfalls of common approaches to taxonomic annotation of protistan meta-omic datasets. We re-analyze three environmental datasets at three levels of taxonomic hierarchy in order to illustrate the crucial importance of database completeness and curation in enabling accurate environmental interpretation. We show that taxonomic membership of sequence clusters estimates community composition more accurately than returning exact sequence labels, and overlap between clusters can address database shortcomings. Clustering approaches can be applied to diverse environments while continuing to exploit the wealth of annotation data collated in databases, and selecting and evaluating these databases is a critical part of correctly annotating protistan taxonomy in environmental datasets. We argue that ongoing curation of genetic resources is crucial in accurately annotating protists in in situ meta-omic datasets. Moreover, we propose that precise taxonomic annotation of meta-omic data is a clustering problem rather than a feasible alignment problem.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Best practices for in-situ and operando techniques within electrocatalytic systems

In-situ and operando techniques in heterogeneous electrocatalysis are a powerful tool used to elucidate reaction mechanisms. Ultimately, they are key in determining concrete links between a catalyst’s physical/electronic structure and its activity en route to designing next-generation systems. To this end, the exact execution and interpretation of these lines of experiments is critical as this determines the strength of conclusions that can be drawn and what uncertainties remain. Instead of focusing on how techniques were used to understand systems, as is the case with most reviews on the topic, this work instead initiates a nuanced discussion of 1) how to best carry out each technique and 2) initiate a nuanced analysis of which level of insights can be drawn from the set of in-situ or operando experiments/controls carried out. We focus on several commonly used techniques, including vibrational (IR, Raman) spectroscopy, X-ray absorption spectroscopy and electrochemical mass spectrometry. In addition to this, we include sections of reactor design and the link with theoretical modelling that are applicable across all techniques. While we focus on heterogeneous electrocatalysis, we make links when appropriate to the areas of photo- and thermo-catalytic systems. We highlight common pitfalls in the field, how to avoid them, and what sets of complementary experiments may be used to strengthen the analysis. We end with an overview of what gaps remain in in-situ and operando techniques and what innovations must be made to overcome them.

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

Identification of the glassy state in nanoparticles by transmission electron microscopy

Identification of amorphous phases in nanoparticles by atomic-resolution transmission electron microscopy (TEM) requires analyses such as tilt-angle-dependent TEM imaging and single-nanoparticle electron diffraction, rather than relying on a single TEM image. Here, the disordered structures of amorphous nanoparticles offer unique atomic configurations and properties that differ from the properties of their crystalline counterparts. These characteristics have motivated the exploration of such materials for mechanical, sensing and catalytic applications. In addition, the formation of amorphous metal nanoparticles is an important endeavour to understand the process of vitrification and the nature of the glassy state. Atomic-resolution transmission electron microscopy (TEM) is increasingly being used as a tool for characterizing structures of nanoparticles produced by vitrification. In this Comment, we discuss the pitfalls of using TEM for ascertaining whether nanoparticles are amorphous. We also make recommendations of best practices.

Alcorn, Francis M. [Sandia National Laboratories (↗
DOE OSTI2026

Challenges and alternatives to empirical orthogonal functions for earth system data

Empirical orthogonal functions (EOFs) applied to gridded Earth system data enables users to diagnose modes of variability with relative ease. Yet, many challenges to interpretation exist such that they must be used with awareness and intention when applied to gridded climate data, especially with large ensembles. Utilizing data from two different Earth system modelling large ensemble frameworks, the Energy Exoscale Earth System Model and the Community Earth System Model, as well as reanalysis data, common EOF pitfalls are summarized and discussed. Challenges include erroneous mode swapping, sign flipping, and the temporal variability of the centers of action. For modes of variability with similar contribution to variance, mode swapping is not uncommon. Sign flipping can occur with almost any mode where the pattern is correct, but the sign is arbitrary. Although the variability of the center of action is not necessarily problematic, it potentially complicates interpretation over multi-century timescales. A wide variety of alternative methods to EOFs exist, but fitness-for-purpose must be evaluated. Additionally, illustrations of alternative methods and examples of proper use are provided. Alternative methods fit into three categories: EOF variants, linear methods, and multilinear methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analyses of circular solutions for advanced plastics waste recycling

A circular plastics economy can leverage the lightweight, strong and durable characteristics of macromolecular materials, while simultaneously reducing the negative environmental impacts associated with polymer waste. Advanced recycling technologies provide an opportunity to valorize plastics waste and extend the lifespan of these materials by converting waste into new monomers, polymers or specialty chemicals. Although many advanced technologies appear promising, assessments of economic and environmental sustainability are often not conducted in a standardized fashion and neglect factors such as plastics waste transportation, sorting and pretreatment. These shortcomings can lead to inaccurate or misleading predictions, reduce opportunities for optimization and limit industrial relevance. In this Review, we highlight select industrial case studies to underscore the notable consequences of underestimating the complexity of real-life consumer plastics waste. In addition, the current challenges associated with the assessment of the industrial viability of laboratory-scale processes are explored. Here, by discussing relevant analysis frameworks and system boundaries, along with potential analytical pitfalls, future research will be guided beyond chemical considerations and toward impactful circular solutions.

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

Efficiently predicting pressure-composition-temperature diagrams to discover low-stability metal hydrides

Quantitatively accurate computational predictions of metal hydride thermodynamics are challenging but critical for alloy performance optimization across a multitude of technological domains, including hydrogen storage, compression, purification, and getters. Recent machine learning approaches have demonstrated great success in this area, but can potentially suffer from several shortcomings since they rely on imbalanced experimental training data and can have poor out-of-distribution (ood) test performance. Here, in this study, we circumvent such pitfalls by developing a computationally efficient, first principles-based workflow for direct prediction of metal hydride phase equilibrium, i.e., the pressure-composition-temperature (PCT) diagram. We then demonstrate its utility on predicting low stability hydrides derived from compositionally complex C14 Laves phase AB2 alloys. Specifically, we computationally predict and then experimentally validate an AB 2 alloy series (z < 0.6 for Ti 2−z Zr z CrMnFeNi) with ideal hydriding thermodynamics for a two-stage metal hydride-based compressor for pressurizing boil off from liquefied hydrogen. Importantly, this study lays the groundwork for accurate and efficient discovery/optimization of ood, low-stability hydrides for which purely data-driven approaches lack sufficient accuracy.

08 HYDROGEN↗
DOE OSTI2025

Structure of iridium oxide catalysts dictates performance differences for proton exchange membrane water electrolyzers

Proton exchange membrane water electrolyzers (PEMWEs) are promising zero-emission technologies. However, their high cost remains a barrier to widespread adoption. Iridium oxide is commonly used as an oxygen evolution reaction (OER) catalyst, and its cost and scarcity make it essential to reduce its loading while increasing its activity. Evaluation of iridium oxide activity should be carried out in the membrane electrode assembly (MEA) configuration to replicate realistic operating conditions. Herein, we present a comprehensive benchmarking framework to accurately evaluate the amorphous and crystalline iridium oxides at the MEA level. By systematically varying the catalyst loading, this study confirmed that each MEA was utilized uniformly, presenting intrinsic electrochemical properties independent of the loading. Through intrinsic charge density determined by voltammetry, we established two electrochemical descriptors to evaluate catalyst redox reactions. The mass activity was evaluated by correlating current vs. loading, and the slope provides loading-independent mass activity. The effect of the porous transport layer on OER activity was discussed, identifying a ‘background’ current at zero-loading. In conclusion, this study highlights potential pitfalls in MEA-level catalyst screening and underscores the importance of the loading study for reliable results.

Kwon, Obeen [University of California, Irvine, CA ↗
DOE OSTI2024

Signatures of clustering accessible with a Time Projection Chamber: TexAT

Many experimental observables in clustering require high-sensitivity, almost background-free measurements. The use of Time Projection Chambers (TPCs) over the past 15 years have demonstrated their capability as a step change in the accessibility of many of these observables, as well as the possibility to study clustering via new techniques. A summary of the difficulties and pitfalls of determining the type of clustering from observables is briefly discussed, with a focus on α-condensation and the possibility of an additional (Efimov) 0 + state in 12 C, below the Hoyle state. The expansion of the technique used to tackle this challenge to study 3α + p clustering in 13 N is also discussed, highlighting the exciting opportunities TPCs provide to study clustering inaccessible by conventional means. Finally, an overview of the recent and upcoming advances in TPC technology is given as well as listing additional future challenges that are needed to be overcome, in the context of discussing the next-generation upgrade to the existing TexAT TPC, known as TeBAT (TExas Birmingham Active Target).

Bishop, Jack↗
DOE OSTI2025

A quantitative figure of merit for battery SEI films and their use as functional solid-state electrolytes

As a key passivation film that governs battery operation, the solid electrolyte interphase (SEI) has long been credited for enabling high-performance batteries or blamed for their eventual death. However, qualitative descriptions of the SEI often found in the literature (e.g., “conductive,” “passivating”) highlight our incomplete understanding of this layer, where even the most basic properties foundational to SEI function remain difficult to measure. Here, we quantify SEI conductivities and SEI transference numbers using a separator-free Cu|SEI|Li architecture that treats the SEI as a functional solid-state electrolyte (SSE). We find that while any SEI property alone (e.g., electronic conductivity) is weakly correlated (R 2 < 0.67) with battery performance (e.g., Coulombic efficiency), a strong correlation (R 2 > 0.99) can be achieved by defining the “SEI cT number” as a product between the SEI transference number (T) and the ratio of SEI conductivities (c). Analogous to the thermoelectric figure of merit (i.e., zT ), SEI cT quantitatively benchmarks the holistic impact of SEI properties on battery performance and underscores the pitfalls of citing such properties in isolation. Perhaps most strikingly, we demonstrate that Li metal deposition and stripping at room temperature is possible in our separator-free Cu|SEI|Li cell, confirming that the SEI can function precisely as an SSE. Together, these results enrich our understanding of the SEI, not just as a passivation layer but as a functional structure that can potentially have important implications for solid-state batteries.

Science & Technology - Other Topics↗
DOE OSTI2024

Collective coordinate fix in the path integral

Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parametrize a manifold of zero modes and more broadly provide judicious coordinates on the space of fields. However, changing from local coordinates around a saddle point to more global collective coordinates is remarkably subtle. The main complication is that the mapping from local coordinates to collective coordinates is generically multivalued. Consequently one is forced to either restrict the domain of path integral in a delicate way, or otherwise correct for the multivaluedness by dividing the path integral by certain intersection numbers. We provide a careful treatment of how to fix collective coordinates while accounting for these intersection numbers, and then demonstrate the importance of the fix for free theories. We also provide a detailed study of the fix for interacting theories and show that the contributions of higher intersections to the path integral can be nonperturbatively suppressed. Using a variety of examples ranging from single-particle quantum mechanics to quantum field theory, we explain and resolve various pitfalls in the implementation of collective coordinates. Published by the American Physical Society 2024

Bhattacharya, Arindam (ORCID:0000000244578926)↗
DOE OSTI2026

Understanding Large-Scale Dynamos in Unstratified Rotating Shear Flows

For this work, we combine simulations with new analyses that overcome previous pitfalls to explicate how nonhelical mean-field dynamos grow and saturate in unstratified, magnetorotationally driven turbulence. Shear of the mean radial magnetic field amplifies the azimuthal component. Radial fields are regenerated by velocity fluctuations that induce shear of radial magnetic fluctuations, followed by Lorentz and Coriolis forces that source a negative off-diagonal component in the turbulent diffusivity tensor. We present a simple schematic to illustrate this dynamo growth. A different part of the Lorentz force forms a third-order correlator in the mean electromotive force that saturates the dynamo.

accretion disk & black-hole plasma↗
DOE OSTI2026

Predicting Adaptively Chosen Observables in Quantum Systems

Recent advances have demonstrated that 𝒪⁡(log 𝑀) measurements suffice to predict 𝑀 properties of arbitrarily large quantum many-body systems. However, these remarkable findings assume that the properties to be predicted are chosen independently of the data. This assumption can be violated in practice, where scientists adaptively select properties after looking at previous predictions. This work investigates the adaptive setting for three classes of observables: local, Pauli, and bounded-Frobenius-norm observables. We prove that Ω⁡(√𝑀) samples of an arbitrarily large unknown quantum state are necessary to predict expectation values of 𝑀 adaptively chosen local and Pauli observables, where the system size scales exponentially and polynomially in 𝑀, respectively. We also present computationally efficient algorithms that achieve this information-theoretic lower bound. In contrast, for bounded-Frobenius-norm observables, we devise an algorithm requiring only 𝒪⁡(log 𝑀) samples, independent of system size. These results highlight the potential pitfalls of adaptivity in analyzing data from quantum experiments and provide algorithmic tools to safeguard against erroneous predictions in quantum experiments.

Machine learning↗
DOE OSTI2025

A Survey on the Design, Detection, and Prevention of Pre-Silicon Hardware Trojans

The complexity of the semiconductor design lifecycle and globalized manufacturing process creates concern over the threat of deliberate malicious alterations, or hardware Trojans, being inserted into microelectronic designs. This has resulted in a significant corpus of hardware Trojan research including Trojan design and benchmarking efforts and development of corresponding metrics and detection and prevention techniques, over the last two decades. In this survey, we first highlight efforts in Trojan design and benchmarking, followed by a cataloging of seminal and recent works in Trojan detection and prevention and their accompanied metrics. Given the volume of literature in this field, this survey considers only pre-silicon techniques. We make this distinction between pre- and post-silicon to properly scope and provide appropriate context into the capabilities of existing hardware Trojan literature. Each major section (design, prevention, and detection) is accompanied by insights, and common pitfalls, which we highlight can be addressed by future research.

42 ENGINEERING↗
DOE OSTI2024

Inferring Reliability Model Parameters from Expert Opinion

Here, we propose a method for constructing bathtub models of reliability from opinion. The method is intended for reliability studies early in the design and prototyping of a new system, before data concerning reliability has become available. A stylized bathtub curve is presented for soliciting best engineering judgement from technical experts. By pooling these stylized curves, we produce data that can be used to infer parameters for a piece-wise Weibull model of reliability. A numerical example demonstrates the practicality of the method while also highlighting potential pitfalls when working with subjective data.

42 ENGINEERING↗
DOE OSTI2025

Applying Corrective Machine Learning in the E3SM Atmosphere Model in C++ (EAMxx)

The Simplified Cloud-Resolving E3SM Atmosphere Model (SCREAM) is the newest addition to the family of Earth System Models capable of explicitly resolving convective systems. SCREAM is a kilometer-scale configuration of the advanced E3SM Atmosphere Model (EAMxx), designed for heterogeneous systems. While the enhanced accuracy of kilometer-scale modeling offers significant benefits, it comes with a substantial computational cost, limiting feasible simulation durations to only a few years, even on the fastest supercomputers. Machine learning presents an opportunity for scientists to achieve the high accuracy of storm-resolving models at a significantly reduced cost. Building on the previous success of applying corrective machine learning (ML) to the FV3 model, this study explores the effects of implementing corrective ML in EAMxx-SCREAM. We also address the computational challenges of integrating the corrective ML, which is written in Python, with the C++/Kokkos EAMxx driver, as well as the potential pitfalls of generalizing an approach that was effective with one atmosphere model to another.

54 ENVIRONMENTAL SCIENCES↗