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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation

Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiring significant human effort on annotations. This poses challenges for applications in the chemical field, such as catalysis, where many advancements have traditionally relied on trial-and-error investigations and incremental adjustment of variables. This hinders catalysis science and technology progress in addressing emerging energy and environmental crises. In this work, we propose a few-shot NER model that can quickly adapt to extract new types of chemical entities by using only a limited number of annotated examples. Our model employs a metric-learning approach to transfer entity similarity knowledge from high-resource chemical domains (with abundant annotations) to enable effective entity recognition in low-resource specialized domains (limited annotation). We validate the effectiveness of our model on a few-shot chemical NER benchmark built based on six existing chemical NER data sets. Experiments show that the proposed few-shot NER model can achieve reasonable performance with only 5 examples per entity type and shows consistent improvement as the number of examples increases. Furthermore, we demonstrate how the proposed model can be trained with large language model (LLM) annotated data, opening a new pathway for rapid adaptation of NER systems. Furthermore, our approach leverages the knowledge broadness of large language models for chemistry while distilling this knowledge into a lightweight model suitable for efficient and in-house use.

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

Highly Selective Electrocatalytic Reduction of CO 2 into Methane on Cu–Bi Nanoalloys

Methane (CH 4 ), the main component of natural gas, is one of the most valuable products facilitating energy storage via electricity conversion. However, the poor selectivity and high overpotential for CH 4 formation with metallic Cu catalysts prevent realistic applications. Introducing a second element to tune the electronic state of Cu has been widely used as an effective method to improve catalytic performance, but achieving high selectivity and activity toward CH 4 remains challenging. Here, we successfully synthesized Cu–Bi NPs, which exhibit a CH 4 Faradaic efficiency (FE) as high as 70.6% at -1.2 V versus reversible hydrogen electrode (RHE). The FE of Cu–Bi NPs has increased by approximately 25-fold compared with that of Cu NPs. DFT calculations showed that alloying Cu with Bi significantly decreases the formation energy of *COH formation, the rate-determining step, which explains the improved performance. Further analysis showed that Cu that has been partially oxidized because of electron withdrawal by Bi is the most possible active site.

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

Monitoring Redox Processes in Lithium-Ion Batteries by Laboratory-Scale Operando X-ray Emission Spectroscopy

Tracking changes in the chemical state of transition metals in alkali-ion batteries is crucial to understanding the redox chemistry during operation. X-ray absorption spectroscopy (XAS) is often used to follow the chemistry through observed changes in the chemical state and local atomic structure as a function of the state-of-charge (SoC) in batteries. In this study, we utilize an operando X-ray emission spectroscopy (XES) method to observe changes in the chemical state of active elements in batteries during operation. Operando XES and XAS were compared by using a laboratory-scale setup for four different battery systems: LiCoO 2 (LCO), Li[Ni 1/3 Co 1/3 Mn 1/3 ]O 2 (NMC111), Li[Ni 0.8 Co 0.1 Mn 0.1 ]O 2 (NMC811), and LiFePO 4 (LFP) under a constant current charging the battery in 10 h (C/10 charge rate). We show that XES, despite narrower chemical shifts in comparison to XAS, allows us to fingerprint the battery SOC in real time. We further demonstrate that XES can be used to track the change in net spin of the probed atoms by analyzing changes in the emission peak shape. As a test case, the connection between net spin and the local chemical and structural environment was investigated by using XES and XAS in the case of electrochemically delithiated LCO in the range of 2–10% lithium removal.

25 ENERGY STORAGE↗
DOE OSTI2020

Photoelectrochemical Nitrogen Reduction to Ammonia on Cupric and Cuprous Oxide Photocathodes

Photoelectrochemical N 2 reduction enables the production of NH 3 under ambient conditions using water as the hydrogen source. Furthermore, by utilizing solar energy, photoelectrochemical N 2 reduction can significantly reduce the energy input required for N 2 reduction. In this study, photoelectrochemical N 2 production was investigated using CuO and Cu 2 O photocathodes that are known to be poorly catalytic for water reduction, the major reaction competing with N 2 reduction. When tested under simulated solar illumination with isotopically labeled 15 N 2 in 0.1 M KOH solution, the CuO and Cu 2 O photocathodes produced 15 NH 3 with a Faradaic efficiency of 17% and 20% at 0.6 V and 0.4 V vs. RHE, respectively. These potentials are significantly more positive than the thermodynamic reduction potential of N 2 , which demonstrates how the use of photoexcited electrons in the CuO and Cu 2 O photocathodes can reduce the energy input required for NH 3 production. Here, the use of photoexcited electrons in these photocathodes for N 2 reduction, water reduction, and photocorrosion was carefully examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗