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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 37 records · Page 2

Grid Architecture Mapping to Understand Transformation (GAMUT): Concept Definition

The electric power system is undergoing significant transformation driven by changes in the generation mix, increasing reliance on information and communication technologies, evolving customer expectations, and a dynamic cyber-physical environment. To address these challenges, substantial investments will be made over the next decade to create a flexible, affordable, secure, reliable, and resilient electric system. In response, the U.S. Department of Energy's Office of Electricity is developing knowledge management tools aimed at systematically documenting technology pilots and demonstration projects. This initiative seeks to improve understanding of operating contexts, planning steps, and integration requirements for innovative grid technologies. The Department of Energy project leverages Grid Architecture principles to collect and organize insights into the interdependencies, requirements, and capabilities of various grid solutions. By employing a systematic approach, the project aims to perform a feasibility study for the development of a software tool that will support stakeholders, including regulators, transmission and distribution system operators, distributed energy resources aggregators, and technology providers. By offering a systematic, software-based framework to document technologies, understand their benefits and impacts, and inform deployment strategies, the proposed Grid Architecture Mapping to Understand Transformation (GAMUT) Tool is intended to reduce costs, enhance decision-making, and facilitate scaling and effective deployment of new technologies. The feasibility study will evaluate the technical and financial viability of the GAMUT Tool, identifying stakeholder needs and assessing risks and mitigation strategies. Ultimately, the GAMUT team aims to develop an initial minimal viable product, followed by staged improvements, to aid in the modernization of the electric grid, contributing to a more sustainable and resilient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distribution Transformer Demand: Understanding Demand Segmentation, Drivers, and Management Through 2050

The National Renewable Energy Laboratory (NREL) has been working closely with the U.S. Department of Energy's Office of Electricity (OE) to understand the critical drivers and potential means of managing distribution transformer demand through 2050. This effort has consulted with utility representative organizations and transformer manufacturers to understand the problem, characterized the in-service assets, and modeled future demand. Distribution transformers, or service transformers, range from 10 to 5,000 kilovolt-amperes (kVA), have a high-side voltage of less than 34.5 kilovolts, and have step-down power delivery for customer end use. This research will help the manufacturing sector understand production requirements and better inform utility strategies for managing their demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Improving Cyber Situational Understanding

Effective cybersecurity operations require the ability to analyze large amounts of information to assess security risks and formulate defensive strategies against adversaries. This has become more complex in recent years as the sprawl and interconnectivity of devices grows through implementation of virtualization, cloud computing, and Internet of Things (IoT). The amount of data and analysis required for effective cybersecurity command and control decisions far exceeds humans’ capacity to perform manually. We characterize the analysis problem as cyber situational understanding. The research presented to improve cyber situational understanding focuses on vulnerability analysis and threat intelligence. Regarding vulnerabilities, entities must analyze and plan work for between thousands and tens of thousands of software vulnerabilities annually. Entities heavily use network firewalls to limit vulnerability exposure. As a result, some of these vulnerabilities permit exposure to adversarial exploitation, whereas others are inaccessible and therefore present negligible risk of exploitation. Distinguishing between high and low risk software vulnerabilities requires a deep understanding of the vulnerability, network firewall protection, and characteristics of the targeted device. This problem is solved by extracting network service features from vulnerability data features using both machine-learning and natural language processing. Then, the network firewall topology is parsed to determine which vulnerabilities are reachable by adversaries. Ultimately, a state-based safety analysis ascertains which vulnerabilities are unsafe. A related vulnerability analysis problem occurs in cybersecurity operations when associating an entity’s hardware and software assets to public vulnerability databases. Assets often reveal hardware and software through installation artifacts and network service identification, and entities store these artifacts in inventory databases. However, software and hardware vendors apply a standard Common Platform Enumeration (CPE) naming convention when publicly reporting vulnerabilities. Associating these two datasets often requires many hours to days of manual inspection. The proposed solution automates the mapping approach of human analysts using fuzzy matching techniques, natural language processing, and, ultimately, machine learning to present a small set of recommendations for mapping the two datasets. The result significantly reduces human analysis time and reduces the occurrence of false positives in vulnerability notifications. Finally, cyber threat intelligence (CTI) requires associating cyber observable artifacts, such as IP addresses, URIs, and file hashes, with cyber threat tactics, techniques, and procedures. Unfortunately, most CTI data is compartmentalized across multiple organizations and cannot be shared due to the legal and reputational risk with cyber threat being associated with the entity. The approach to solving this problem inovlves using a distributed ledger with anonymous token spending and authentication. This allows a consortium of semi-trusted entities to share the workload of curating CTI for a threat sharing community’s cooperative benefit.

Huff, Philip↗

What's on the menu? Examining native apex‐ and invasive meso‐predator diets to understand impacts on ecosystems

Abstract Understanding how carnivores impact ecological communities is essential for guiding effective management actions and conserving biodiversity. Quantifying predators' diets, including prey selectivity, allows for the assessment of the relative effects native and invasive predators may have on prey populations. In Australia, populations of a native, terrestrial apex predator, the dingo Canis dingo/C. familiaris , and introduced and invasive subordinate mesopredators, the European red fox Vulpes vulpes and feral cat Felis catus , co‐occur, but there is limited understanding of their relative impacts on native and invasive prey in different ecosystems. To assess the possible effects of dingoes, foxes and cats on prey, we examined their diet and prey selectivity across a ~10,000 km 2 semi‐arid mallee ecosystem. Using macroscopic scat analysis, we identified strong dietary niche separation. Larger‐bodied dingoes primarily consumed large marsupial herbivores, whereas foxes and cats primarily consumed smaller prey, including introduced and native rodents and birds. Foxes had the broadest diet, and the greatest dietary overlap with cats ( = 0.81), compared with dingoes ( = 0.50) or between dingoes and cats ( = 0.36). Livestock were identified in 2% of dingo and 7% of fox scats. Cats and foxes consumed more than 15 times the volume of small native mammals compared with dingoes, including threatened species such as fat‐tailed dunnarts Sminthopsis crassicaudata . Cats and foxes also selectively consumed small mammals relative to their estimated availability and consumed fewer large mammals. In contrast, dingoes consumed fewer birds and more echidnas relative to their availability. Our results suggest limited intraguild competition within this semi‐arid ecosystem, as dingoes are primarily exerting top‐down pressure on large herbivores, whereas invasive mesopredators are disproportionately impacting smaller prey, including threatened native mammals. Practical implication . Our findings suggest that ongoing conservation management of dingoes, red foxes and feral cats must consider the variation in diets, impacts on prey and ecological roles of these different predator species, and avoid indiscriminate lethal control methods. Quantifying actual, rather than assumed, impacts of predators on threatened native species, large herbivores and livestock is essential to achieve effective and integrated ecosystem management.

Mason, Rachel T. [School of Life and Environmental↗

Understanding Depolymerization and Repolymerization Toward Repurposing Polymer Waste Into Valuable Chemicals & Materials

The versatility of synthetic polymers has led to their continual and escalating production that has accompanied mismanagement at their end-of-life. Exploring and understanding complementary avenues to repurpose plastic waste beyond traditional mechanical recycling can unlock new opportunities in providing feedstock flexibility, securing supply chains, recovering valuable materials, and enabling new valorization paths. Chemical recycling allows for the return to monomers, tailored oligomers, and polymers, even from mixed states of post-consumer waste plastics. This review article summarizes our research team's efforts on elucidating key insights surrounding plastic depolymerization and repolymerization into valorized products. We revealed organocatalyst design rules lead to highly effective and selective deconstruction of condensation polymers. The intricacies of tailoring the reaction environment to produce products of specific lengths and desired functionalities transform low-value waste feedstocks into high-performance materials with embedded circularity. Other types of polymers, including polyolefins and polyakenamers, have also been designed and converted into valuable products. There remain opportunities for further developments such as low-energy and precision depolymerization, adoption of cutting-edge small molecule transformation to access functionalized polymer scaffolds typically inaccessible otherwise, as well as precision design and understanding through the aid of advanced tools.

Galan, Nick [ORNL]↗

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts↗

Spatial analysis of cell patterning to aid genetic and phenotypic understanding of grass stomatal density: A case study in maize

Biological processes involve complex hierarchies where composite traits result from multiple component traits. However, holistically understanding of how sets of component traits interact to underpin genotype-to-phenotype relationships is generally lacking. Stomatal density (SD) is a tractable model system for exploring how high-throughput phenotyping (HTP) data could be exploited by a new spatial analysis approach to better understand a developmentally and functionally important trait. SD is a composite trait, resulting from various components related to cell identity and size, which are themselves governed by a series of spatio-developmental processes. Data from 192 recombinant inbred lines of maize [Zea mays (L.)] were analyzed by a new stomatal patterning phenotype (SPP) to (1) describe the average spatial probability distribution of the nearest neighboring stomata; (2) derive a core set of component traits related to cell size, cell packing, and positional probabilities; (3) build a structural equation model of component traits underlying SD; and (4) identify stomatal patterning quantitative trait loci (QTL). The core set of SPP-derived traits explained 74% of the variation in SD. Analyzing SPP component traits allowed some loci previously identified as generic SD QTL to be recognized as specific to lateral versus longitudinal elements of stomatal patterning. Therefore, this study highlights how novel insights can be gained by decomposing a composite trait (e.g., SD) into a set of component traits that were present in HTP data but not previously exploited.

59 BASIC BIOLOGICAL SCIENCES↗

Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling

One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.

2D modelling↗

Exploring Fission–Fusion Synergies to Accelerate Compatibility Understanding

To address the significant commercial interest in fusion energy, it will be necessary to accelerate the compatibility research associated with liquid breeders including Li, eutectic Pb–Li and LiF-BeF 2 (FLiBe) molten salt. Particularly for FLiBe, compatibility understanding is limited especially for fusion relevant materials such as reduced activation ferritic-martensitic steels, SiC and V alloys. The historical knowledge associated with molten salt reactors (MSRs) and recent work to commercialize MSRs can benefit fusion research. Recent experimental and modeling work has improved understanding and this knowledge can be applied to fusion relevant materials. For liquid metals (LMs), the comparisons to Li and Pb–Li are less direct but nevertheless can help guide the pathway toward commercialization. For Pb–Li, Al-rich coatings have been shown to inhibit dissolution and potentially increase operating temperatures. For commercialization, the experience with sensors and on-line cleanup can help guide future developments. Thus, it is worth considering the potential for fission-related research with LMs and molten salts to help accelerate fusion research.

36 MATERIALS SCIENCE↗

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis.

54 ENVIRONMENTAL SCIENCES↗

Understanding and mitigating degradation in amine-based sorbents for CO 2 direct air capture

The success of direct air capture (DAC) of CO 2 depends on sorbents that combine high capacity, low energy requirements, and long-term durability. Amine-based sorbents-including solid-supported aminopolymers, grafted amines, and amine-functionalized resins-remain the leading candidates, but their limited lifetimes drive up costs and constrain deployment. In this review, we outline the current understanding of amine-based sorbent degradation with an emphasis on clearly identifying what is known about structure-property-performance relationships, as well as important knowledge gaps. More specifically, we discuss how polymer chemistry, sorbent design variables, and environmental and process conditions contribute to performance loss. In parallel, we outline how advances in spectroscopy, modeling, and accelerated testing are beginning to illuminate chemical and physical degradation mechanisms. Looking forward, we identify future research directions that will be critical for gaining a deeper understanding of degradation, as well as opportunities for developing innovative mitigation strategies for improving the lifetime of amine-based sorbents.

organic↗

Advances in understanding vacuum break dynamics in liquid helium-cooled tubes for accelerator beamline applications

Understanding air propagation and condensation following a catastrophic vacuum break in particle accelerator beamlines cooled by liquid helium is essential for ensuring operational safety. This review summarizes experimental and theoretical work conducted in our cryogenics lab to address this issue. Systematic measurements were performed to study nitrogen gas propagation in uniform copper tubes cooled by both normal liquid helium (He I) and superfluid helium (He II). These experiments revealed a nearly exponential deceleration of the gas front, with stronger deceleration observed in He II-cooled tubes. To interpret these results, a one-dimensional (1D) theoretical model was developed, incorporating gas dynamics, heat transfer, and condensation mechanisms. The model successfully reproduced key experimental observations in the uniform tube system. However, recent experiments involving a bulky copper cavity designed to mimic the geometry of a superconducting radiofrequency (SRF) cavity revealed strong anisotropic flow patterns of nitrogen gas within the cavity, highlighting limitations in extrapolating results from simplified tube geometries to real accelerator beamlines. To address these complexities, we outline plans for systematic studies using tubes with multiple bulky cavities and the development of a two-dimensional (2D) model to simulate gas dynamics in these more intricate configurations. As a result, these efforts aim to provide a comprehensive understanding of vacuum breaks in particle accelerators and improve predictive capabilities for their operational safety.

Beamline tube↗

DECOVALEX-2023: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX initiative is an international research collaboration (www.decovalex.org), initiated in 1992, for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of the complex perturbations and coupled processes in geologic repositories and how these impact long-term performance predictions. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2023, started in early 2020 and ended in late 2023. More than fifty research teams associated with 17 international DECOVALEX partner organizations participated in the comparative evaluation of eight modeling tasks covering a wide range of spatial and temporal scales, geological formations, and coupled processes. This Virtual Special Issue on DECOVALEX-2023 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes. While primarily focused on radioactive waste, much of the work included here has wider application to many geoengineering topics.

Coupled processes↗

The impact of $γN$ and $γ^∗N$ interactions on our understanding of nucleon excitations

We review recent progress in our understanding of the nucleon excitation spectrum. Thanks to dedicated efforts at facilities such as ELSA, MAMI and Jefferson Lab, several new nucleon resonances have been discovered, and evidence for previously elusive states has been significantly improved. Numerous decay channels have been observed for the first time, and resonance properties are being extracted from these data by several groups through coupled-channel analyses of varying complexity. Electroproduction experiments have provided further insights into the internal structure of light baryon resonances – for example, the long-debated Roper resonance N (1440) is observed as a three-quark state with a significant meson-cloud component. While the non-relativistic quark model remains a valuable tool for organizing the spectrum of nucleon and Δ resonances, a variety of theoretical frameworks have emerged to offer deeper understanding, including phenomenological quark models, holographic QCD, functional methods, effective field theories, and lattice QCD. We examine the interplay between these approaches, highlight their respective strengths and explore how they complement each other in shaping our knowledge of light baryon resonances. We address several open questions in baryon spectroscopy, including the nature of the enigmatic Λ (1405), ongoing searches for exotic states such as hybrid baryons and pentaquarks, and the dichotomy between microscopic descriptions of baryons in terms of quarks and gluons versus effective hadronic descriptions based on meson-baryon dynamics.

Baryon resonances↗

Understanding the Effect of Sample Geometry on Temperature Distribution during Optical Floating Zone Crystal Growth in Vacuum Environment through Heat Transfer Modeling

Optical floating zone furnaces (OFZ) have had a transformative impact on fundamental science due to their ability to rapidly produce large single crystals of a wide variety of complex materials. However, a quantitative understanding of the OFZ growth environment is generally lacking due to the difficulty of measuring the local sample temperatures during OFZ growth, as well as to the general lack of information about the temperature-dependent physical parameters needed to model heat transfer. To overcome these challenges, we apply a physics-based heat transfer model, parametrized by measurements from synchrotron experiments and a machine-learning (ML) algorithm, to simulate the temperature distributions of samples heated in an OFZ furnace in a vacuum environment. This model is used to quantitatively understand how the sample maximum temperature and temperature gradient (key parameters that influence the success of crystal growth) are affected by the rod size, rod shape, and heat-zone position on the rod. The results of this study can be applied to make informed decisions on how crystal growth parameters can be tuned to modify temperature profiles and to optimize crystal growth outcomes even when data on internal sample temperature profiles (e.g., those obtained through in situ synchrotron experiments) are not accessible.

36 MATERIALS SCIENCE↗

Understanding the Dissolution and Passivation of an Aluminum Electrode during Electrocoagulation of Groundwater Using Neutron and X-ray Reflectometry

An aluminum (Al)-based electrocoagulation (EC) system can effectively remove dissolved silica and hardness in groundwater. The effectiveness of Al-EC in terms of pollutant removal, Faradaic efficiency, and energy consumption depends on the interfacial electrolysis or passivation of the electrode in water. Thus, understanding the electrolysis reaction at the liquid/electrode interface during operation is important for sustainable EC deployment. Here, a continuous flow-through Al-EC system was tested with various groundwater simulants, i.e., chloride (Cl – )-based, sulfate (SO 4 2– )-based, and mixed solutions. High pollutant removal with low energy consumption was observed in Cl – -based groundwater treatment, while low pollutant removal with high energy consumption was observed in SO 4 2– -based groundwater. For example, the required energy per unit mass of Al dosing in SO 4 2– -based groundwater is three times higher than that in Cl – -based groundwater at 10 mA/cm 2 . However, increasing the Cl – concentration significantly reduces this energy demand. In SO 4 2– -based groundwater, the silicate removal efficiency drops from 85.1% to 24.0% compared to that for Cl – -based groundwater, while Mg 2+ and Ca 2+ removal efficiencies decrease to 0.6% from 15.8% and 5.7% from 44.8%, respectively. To better understand this EC performance, we used in situ neutron reflectometry (NR) to examine the interfacial dynamics of Al dissolution and passivation at a 100 nm scale occurring on the surface of the sacrificial Al electrodes during EC. Ex situ X-ray reflectometry (XRR) was also used to support the in situ NR results. Both NR and XRR results revealed that Al dissolution is influenced by the presence of Cl – in the simulants, while a passivating layer forms on the electrode in a SO 4 2– -based solution. In the Cl – -based solution, anodic Al dissolution occurred locally and inhomogeneously across the surface of the Al anode film, resulting in a localized thickness reduction over time. In the SO 4 2– -based solution, no apparent dissolution of the Al anode was identified. Instead, Al underwent oxidation, forming an amorphous Al 2 O 3 surface layer within the Al electrode film that increased in thickness over time. In the mixed solution, both anodic Al dissolution and surface Al 2 O 3 layer formation occurred, indicating that Al dissolution and surface Al 2 O 3 layer formation are attributable to the Cl – and SO 4 2– ions, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding (La,Sr)(Co,Fe)O$_{3-δ}$ Phase Instability within SOECs Using a Combined Experimental and Atomistic Modeling Approach

Understanding the onset of degradation in the air electrode within solid oxide electrolysis cells (SOECs), and the subsequent impact on cell performance, is a critical step in mitigating the performance losses and stability issues of SOECs. In an effort to identify early onset degradation phenomena, SOECs were characterized as fabricated and after testing potentiostatically at 1.3 V for 1000 h at 750 °C. SOEC air electrodes composed of a 1:1 composite of La 0.6 Sr 0.4 Co 0.2 Fe 0.8 O 3–δ (6428-LSCF) and Gd 0.1 Ce 0.9 O 1.95 (GDC) were studied using synchrotron X-ray diffraction (XRD), scanning transmission electron microscopy coupled with energy dispersive X-ray spectroscopy (STEM-EDS), and X-ray absorption near-edge spectroscopy (XANES) to evaluate the changes in the air electrode structurally and chemically. These techniques show the migration of Sr species from the air electrode through pores in the GDC barrier layer, progressing to the electrolyte boundary, where it accumulates and reacts with (Zr 0.84 Y 0.16 )O 2–δ (YSZ) to form SrZrO 3 . Microscopy results are paired with atomistic simulations to better understand the relationship between the thermodynamic instability of 6428-LSCF and cell fabrication/testing conditions. First-principles calculations reveal that LSCF-6428 is not stable during cell manufacturing and testing conditions, which supports the experimental identification of secondary phases in both as-fabricated and tested cells. Together, these results demonstrate that the challenging environments encountered by SOECs during cell manufacturing and operation lead to instabilities of the target 6428-LSCF anode material and underscore the need for more durable, high-performing SOEC components.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanistic Investigation of the Ce(III) Chloride Photoredox Catalysis System: Understanding the Role of Alcohols as Additives

Photocatalytic C–H activation is an emerging area of research. While cerium chloride photocatalysts have been extensively studied, the role of alcohol additives in these systems remains a subject of ongoing discussion. It was demonstrated that the photocatalyst [NEt 4 ] 2 [Ce IV Cl 6 ] ( 1 ) produces •Cl and added alcohols exhibit zero-order kinetics. Prior studies by other researchers suggested that 1 and alcohols lead to cerium alkoxide [Ce–OR] and alkoxy radical intermediates. Here, to understand these seemingly divergent mechanistic proposals, an expanded investigation comparing cerium(IV) catalyst 1 and cerium(III) complex [NEt 4 ] 3 [Ce III Cl 6 ] ( 2 ), which exhibit markedly different reactivity and C–H selectivity, is disclosed. Our findings reveal that alcohol additives accelerate the conversion of cerium(III) to cerium(IV) catalysts, forming key intermediates such as [NEt 4 ] 2 [Ce III Cl 5 (HOCH 3 )] ( 5 ) and [NEt 4 ] 2 [Ce IV Cl 5 (OCH 3 )] ( 6 ), driven by excited-state di-tert-butyl azodicarboxylate under blue light irradiation. The active complex 6 releases the •OCH 3 radical, in sharp contrast to •Cl radicals initiated by cerium(IV) photoredox catalyst 1 . These different reactivity and selectivity profiles can be understood in the context of complex 5 generation and in situ formation of base to afford complex 6 . Experimental validation shows enhanced selectivity toward C–H bonds with different reactivity with catalyst 1 and methanol upon the addition of base and decreased selectivity with catalyst 2 and methanol upon the addition of acid. These findings unify the previously contrasting observations of cerium halide/alkoxide photocatalytic systems and provide a comprehensive understanding on the essential role of base/acid and alcohol in selectivity and reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗