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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The influence of synthesis method on the microstructure and catalytic performance of Y0.07Sr0.93Ti0.8Fe0.2O3-δ in synthetic biogas operated solid oxide fuel cells

Highlights: • Fabrication method leads to differences in phase composition and chemical stability. • Grain size and their distribution in a catalytic layer were different. • The best long-term stability in biogas showed a Pechini-method fabricated material. - Abstract: The Y{sub 0.07}Sr{sub 0.93}Ti{sub 0.8}Fe{sub 0.2}O{sub 3-δ} (YSTF) material was fabricated using three different synthesis methods: modified polymer precursor method (MPP), Pechini method and a solid state reaction method. It was applied as an anode catalytic material for biogas reforming in solid oxide fuel cells. Clear differences in the microstructure of fabricated catalytic layers were found, mainly with respect to a grain size and distribution of grains. This led to some differences in biogas diffusion through the layer as well as in an amount of active sites for a biogas reforming. Also different chemical stability of each compound was observed in the fuel cell operating conditions. The best long-term stability in biogas was found for a fuel cell with the YSTF{sub P}echini catalytic layer (sintered in air at 1100 °C for 2 h) and the lowest one for a fuel cell with the YSTF{sub M}PP layer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Spin–lattice and electron–phonon coupling in 3d/5d hybrid Sr3NiIrO6

Abstract While 3 d -containing materials display strong electron correlations, narrow band widths, and robust magnetism, 5 d systems are recognized for strong spin–orbit coupling, increased hybridization, and more diffuse orbitals. Combining these properties leads to novel behavior. Sr 3 NiIrO 6 , for example, displays complex magnetism and ultra-high coercive fields—up to an incredible 55 T. Here, we combine infrared and optical spectroscopies with high-field magnetization and first-principles calculations to explore the fundamental excitations of the lattice and related coupling processes including spin–lattice and electron–phonon mechanisms. Magneto-infrared spectroscopy reveals spin–lattice coupling of three phonons that modulate the Ir environment to reduce the energy required to modify the spin arrangement. While these modes primarily affect exchange within the chains, analysis also uncovers important inter-chain motion. This provides a mechanism by which inter-chain interactions can occur in the developing model for ultra-high coercivity. At the same time, analysis of the on-site Ir 4+ excitations reveals vibronic coupling and extremely large crystal field parameters that lead to a t 2 g -derived low-spin state for Ir. These findings highlight the spin–charge–lattice entanglement in Sr 3 NiIrO 6 and suggest that similar interactions may take place in other 3 d /5 d hybrids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A study of degradation mechanisms in PVDF-based photovoltaic backsheets

Abstract Commercial backsheets based on polyvinylidene fluoride (PVDF) can experience premature field failures in the form of outer layer cracking. This work seeks to provide a better understanding of the changes in material properties that lead to crack formation and find appropriate accelerated tests to replicate them. The PVDF-based backsheet outer layer can have a different structure and composition, and is often blended with a poly(methyl methacrylate) (PMMA) polymer. We observed depletion of PMMA upon aging with sequential (MAST) and combined (C-AST) accelerated stress testing. In field-aged samples from Arizona and India, where PVDF crystallizes in its predominant α-phase, the degree of crystallinity greatly increased. MAST and C-AST protocols were, to some extent, able to replicate the increase in crystallinity seen in PVDF after ~ 7 years in the field, but no single-stress test condition (UV, damp heat, thermal cycling) resulted in significant changes in the material properties. The MAST regimen used here was too extreme to produce realistic degradation, but the test was useful in discovering weaknesses of the particular PVDF-based outer layer structure studied. No excessive β-phase formation was observed after aging with any test condition; however, the presence of β-phase was identified locally by Fourier transform infrared spectroscopy (FTIR). We conclude that both MAST and C-AST are relevant tests for screening outdoor failure mechanisms in PVDF backsheets, as they were successful in producing material degradation that led to cracking.

14 SOLAR ENERGY↗
DOE OSTI2022

Energy-resolved and time-dependent unimolecular dissociation of hydroperoxyalkyl radicals (˙QOOH)

Hydroperoxyalkyl radicals (˙QOOH) are transient intermediates in the atmospheric oxidation of volatile organic compounds and combustion of hydrocarbon fuels in low temperature (<1000 K) environments. The carbon-centered ˙QOOH radicals are a critical juncture in the oxidation mechanism, but have generally eluded direct experimental observation of their structure, stability, and dissociation dynamics. Recently, this laboratory demonstrated that a prototypical ˙QOOH radical [˙CH 2 (CH 3 ) 2 COOH] can be synthesized by an alternative route, stabilized in a pulsed supersonic expansion, and characterized by its infrared (IR) spectroscopic signature and unimolecular dissociation rate to OH radical and cyclic ether products. The present study focuses on a partially deuterated ˙QOOD analog ˙CH 2 (CH 3 ) 2 COOD, generated in the laboratory by H-atom abstraction from partially deuterated tert-butyl hydroperoxide, (CH 3 ) 3 COOD. IR spectral features associated with jet-cooled and isolated ˙QOOD radicals are observed in the vicinity of the transition state (TS) barrier leading to OD radical and cyclic ether products. Furthermore, the overtone OD stretch (2ν OD ) of ˙QOOD is identified by IR action spectroscopy with UV laser-induced fluorescence detection of OD products. Direct time-domain measurement of the unimolecular dissociation rate for ˙QOOD (2ν OD ) extends prior rate measurements for ˙QOOH. Partial deuteration results in a small increase in the TS barrier predicted by high level electronic structure calculations due to changes in zero-point energies; the imaginary frequency is unchanged. Comparison of the unimolecular decay rates obtained experimentally with those predicted theoretically for both ˙QOOH and ˙QOOD confirm that unimolecular decay is enhanced by heavy-atom tunneling involving simultaneous O–O bond elongation and C–C–O angle contraction along the reaction pathway.

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

Phase-field modeling of stored-energy-driven grain growth with intra-granular variation in dislocation density

Abstract We present a phase-field (PF) model to simulate the microstructure evolution occurring in polycrystalline materials with a variation in the intra-granular dislocation density. The model accounts for two mechanisms that lead to the grain boundary migration: the driving force due to capillarity and that due to the stored energy arising from a spatially varying dislocation density. In addition to the order parameters that distinguish regions occupied by different grains, we introduce dislocation density fields that describe spatial variation of the dislocation density. We assume that the dislocation density decays as a function of the distance the grain boundary has migrated. To demonstrate and parameterize the model, we simulate microstructure evolution in two dimensions, for which the initial microstructure is based on real-time experimental data. Additionally, we applied the model to study the effect of a cyclic heat treatment (CHT) on the microstructure evolution. Specifically, we simulated stored-energy-driven grain growth during three thermal cycles, as well as grain growth without stored energy that serves as a baseline for comparison. We showed that the microstructure evolution proceeded much faster when the stored energy was considered. A non-self-similar evolution was observed in this case, while a nearly self-similar evolution was found when the microstructure evolution is driven solely by capillarity. These results suggest a possible mechanism for the initiation of abnormal grain growth during CHT. Finally, we demonstrate an integrated experimental-computational workflow that utilizes the experimental measurements to inform the PF model and its parameterization, which provides a foundation for the development of future simulation tools capable of quantitative prediction of microstructure evolution during non-isothermal heat treatment.

Materials Science↗
DOE OSTI2021

Neutrino-assisted early dark energy: theory and cosmology

Abstract The tension between measurements of the Hubble constant obtained at different redshifts may provide a hint of new physics active in the relatively early universe, around the epoch of matter-radiation equality. A leading paradigm to resolve the tension is a period of early dark energy, in which a scalar field contributes a subdominant part of the energy budget of the universe at this time. This scenario faces significant fine-tuning problems which can be ameliorated by a non-trivial coupling of the scalar to the standard model neutrinos. These become non-relativistic close to the time of matter-radiation equality, resulting in an energy injection into the scalar that kick-starts the early dark energy phase, explaining its coincidence with this seemingly unrelated epoch. We present a minimal version of this neutrino-assisted early dark energy model, and perform a detailed analysis of its predictions and theoretical constraints. We consider both particle physics constraints — that the model constitute a well-behaved effective field theory for which the quantum corrections are under control, so that the relevant predictions are within its regime of validity — and the constraints provided by requiring a consistent cosmological evolution from early through to late times. Our work paves the way for testing this scenario using cosmological data sets.

Astronomy & Astrophysics↗
DOE OSTI2023

Combining protein sequences and structures with transformers and equivariant graph neural networks to predict protein function

Abstract Motivation Millions of protein sequences have been generated by numerous genome and transcriptome sequencing projects. However, experimentally determining the function of the proteins is still a time consuming, low-throughput, and expensive process, leading to a large protein sequence-function gap. Therefore, it is important to develop computational methods to accurately predict protein function to fill the gap. Even though many methods have been developed to use protein sequences as input to predict function, much fewer methods leverage protein structures in protein function prediction because there was lack of accurate protein structures for most proteins until recently. Results We developed TransFun—a method using a transformer-based protein language model and 3D-equivariant graph neural networks to distill information from both protein sequences and structures to predict protein function. It extracts feature embeddings from protein sequences using a pre-trained protein language model (ESM) via transfer learning and combines them with 3D structures of proteins predicted by AlphaFold2 through equivariant graph neural networks. Benchmarked on the CAFA3 test dataset and a new test dataset, TransFun outperforms several state-of-the-art methods, indicating that the language model and 3D-equivariant graph neural networks are effective methods to leverage protein sequences and structures to improve protein function prediction. Combining TransFun predictions and sequence similarity-based predictions can further increase prediction accuracy. Availability and implementation The source code of TransFun is available at https://github.com/jianlin-cheng/TransFun.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Deep Learning on Operational Facility Data Related to Large-Scale Distributed Area Scientific Workflows

Abstract—Distributed computing platforms provide a robust mechanism to perform large-scale computations by splitting the task and data among multiple locations, possibly located thousands of miles apart geographically. This distribution of resources can lead to benefits such as redundancy of data, engagement with scientific teams that involve a diverse group of domain experts distributed spatially around the globe. It allows scientists to share their expertise and data with everyone and achieve insights by deploying collective intelligence of entire team. However, this distributed computing comes with its associated problems such as rampant duplication of file transfers increasing congestion, long job completion times, unexpected site crashing, suboptimal data transfer rates, unpredictable reliability in a time range, overshooting congestion, suboptimal usage of storage elements. In addition, each sub-system becomes a potential failure node that can trigger system wide disruptions.

Machine Learning, Provenance, Time Series, Semanti↗
DOE OSTI2016

A Slag Management Toolset for Determining Optimal Coal Gasification Temperatures

Abstract Gasifier operation is an intricate process because of the complex relationship between slag chemistry and temperature, limitations of feedstock materials, and operational preference. High gasification temperatures increase refractory degradation, while low gasification temperatures can lead to slag buildup on the gasifier sidewall or exit, either of which are problematic during operation. Maximizing refractory service life and gasifier performance require finding an optimized operating temperature range which is a function of the coal slag chemistry and viscosity. Gasifier operators typically use a slag’s viscosity-temperature relationship and/or ash-fusion fluid temperature to determine the gasification temperature range. NETL has built a slag management toolset to determine the optimal temperature range for gasification of a carbon feedstock. This toolset is based on a viscosity database containing experimental data, and a number of models used to predict slag viscosity as a function of composition and temperature. Gasifier users typically have no scientific basis for selecting an operational temperature range for gasification, instead using experience to select operational conditions. The use of the toolset presented in this paper provides a basis for estimating or modifying carbon feedstock slags generated from ash impurities in carbon feedstock.

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

Observations of wind farm wake recovery at an operating wind farm

Abstract. The interplay of momentum surrounding wind farms significantly influences wake recovery, affecting the speed at which wakes return to their freestream velocities. Under stable atmospheric conditions, wind farm wakes can extend over considerable distances, leading to sustained vertical momentum flux downstream, with variations observed throughout the diurnal cycle. Particularly in regions such as the US Great Plains, stable conditions can induce low-level jets (LLJs), impacting wind farm performance and power output. This study examines the implications of wake recovery using long-term observations of vertical momentum flux profiles across diverse atmospheric conditions. In these observations, several key findings were observed, such as (a) LLJ heights being altered downstream of a wind farm, especially when the LLJs are below 250 m above ground level; (b) a notable impact of LLJ height on wake recovery being observed using momentum flux profiles at upwind and downwind locations, wherein LLJs between 250 and 500 m above ground level resulted in larger momentum transfer within the wake (i.e., smaller velocity deficit) compared to LLJs below 250 m above ground level; (c) the largest momentum flux variability being observed during stable atmospheric conditions, with non-negligible variability observed during neutral and unstable atmospheric conditions; (d) detection of wake effects almost always being observed throughout the atmospheric boundary layer height; and finally (e) enhancement of wake recovery being observed in the presence of propagating gravity waves. These insights deepen our understanding of the intricate dynamics governing wake recovery in wind farms, advancing efforts to model and predict their behavior across varying atmospheric contexts. In addition, the performance of large-eddy-simulation-based semi-empirical internal boundary layer height model estimates incorporating real-world atmospheric and turbine inputs was evaluated using observations during LLJ conditions.

17 WIND ENERGY↗
DOE OSTI2018

Effects of defects in composite wind turbine blades – Part 3: A framework for treating defects as uncertainty variables for blade analysis

Abstract. Given that wind turbine blades are large structures, the use of low-cost composite manufacturing processes and materials has been necessary for the industry to be cost competitive. Since these manufacturing methods can lead to the inclusion of unwanted defects, potentially reducing blade life, the Blade Reliability Collaborative tasked the Montana State University Composites Group with assessing the effects of these defects. Utilizing the results of characterization and mechanical testing studies, probabilistic models were developed to assess the reliability of a wind blade with known defects. As such, defects were found to be best assessed as design parameters in a parametric probabilistic analysis allowing for establishment of a consistent framework to validate categorization and analysis. Monte Carlo simulations were found to adequately describe the probability of failure of composite blades with included defects. By treating defects as random variables, the approaches utilized indicate the level of conservation used in blade design may be reduced when considering fatigue. In turn, safety factors may be reduced as some of the uncertainty surrounding blade failure is reduced when analyzed with application specific data. Overall, the results indicate that characterization of defects and reduction of design uncertainty is possible for wind turbine blades.

Riddle, Trey W.↗
DOE OSTI2023

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads

Abstract. Floating wind turbines must withstand a unique and challenging set of loads from the wind and ocean environment. To de-risk development, accurate predictions of these loads are necessary. Uncertainty in modeling predictions leads to larger required safety factors, increasing project costs and the levelized cost of energy. Complex aero-hydro-elastic modeling tools use many input parameters to represent the wind, waves, current, aerodynamic loads, hydrodynamic loads, and structural properties. It is helpful to understand which of these parameters ultimately drives a design. In this work, an ultimate and fatigue-proxy load sensitivity analysis was performed with 35 different input parameters, using an elementary effects approach to identify the most influential parameters for a case study involving the National Renewable Energy Laboratory (NREL) 5 MW baseline wind turbine atop the OC4-DeepCwind semisubmersible during normal operation. The importance of each parameter was evaluated using 14 response quantities of interest across three operational wind speed conditions. The study concludes that turbulent wind velocity standard deviation is the parameter with the strongest sensitivity; this value is important not just for turbine loads, but also for the global system response. The system center of mass in the wind direction is found to have the highest impact on the system rotation and tower loads. The current velocity is found to be the most dominating parameter for the system global motion and consequently the mooring loads. All tested wind turbulence parameters in addition to the standard deviation are also found to be influential. Wave characteristics are influential for some fatigue-proxy loading but do not significantly impact the extreme ultimate loads in these operational load cases. The required number of random seeds for stochastic environmental conditions is considered to ensure that the sensitivities are due to the input parameters and not due to the seed. The required number of analysis points in the parameter space is identified so that the conclusions represent a global sensitivity. The results are specific to the platform, turbine, and choice of parameter ranges, but the demonstrated approach can be applied widely to guide focus in parameter uncertainty.

17 WIND ENERGY↗
DOE OSTI2016

Energetics of a Li Atom adsorbed on B/N doped graphene with monovacancy

We use density functional theory (DFT) to study the adsorption properties and diffusion of Li atom across B/N-pyridinic graphene. Regardless of the dopant type, B atoms of B-pyridinic graphene lose electron density. On the other hand, N atoms (p-type dopants) have tendency to gain electron density in N-pyridinic graphene. Higher chemical reactivity and electronic conductivity of B/N-pyridinic graphene are responsible for stronger binding of Li with the substrates as compared to pristine graphene. The binding energy of Li with B/N-pyridinic graphene exceeds the cohesive energy of bulk Li, making it energetically unfavourable for Li to form clusters on these substrates. Li atom gets better adsorbed on N-pyridinic graphene due to an additional p-p hybridization of the orbitals while Li on B-pyridinic prefers the ionic bonding. Also, significant distortion of N-pyridinic graphene upon Li adsorption is a consequence of the change in bonding mechanism between Li atom and the substrate. Our results show that bonding character and hence binding energies between Li and graphene can be tuned with the help of B/N doping of monovacancy defects. Further, the sites for most stable adsorption are different for the two types of doped and defective graphene, leading to greater Li uptake capacity of B-pyridinic graphene near the defect. In addition, B-pyridinic graphene offering lower diffusion barrier, ensures better Li kinetics. Thus, B-pyridinic graphene presents itself as a better anode material for LIBs as compared to N-pyridinic graphene. - Graphical abstract: Adsorption and diffusion of Li atom across the B/N doped monovacancy graphene is studied using ab-initio DFT calculations. Our results show that bonding mechanism and binding of Li with graphene can be tuned with the help of N/B doping of defects. Also, B-pyridinic graphene presents itself as a better anode material for lithium ion batteries as compared to N-pyridinic graphene. Display Omitted - Highlights: • Density functional theory (DFT) calculations are employed to study the effect of B/N doping of monovacancy graphene on the adsorption and diffusion of Li atom across the sheet using VASP. • Higher chemical reactivity and electronic conductivity of B/N-pyridinic graphene (p-type semiconductors) as compared to pristine graphene lead to stronger binding of Li. It also exceeds the cohesive energy of bulk Li. Thus, uniform distribution of Li atoms is possible on both substrates. • Li gets adsorbed stably at centre of defect in N-pyridinic graphene. B-pyridinic graphene has stable adsorption of Li at hollow site of hexagon, neighboring the defect, having only one boron atom. It leads to maximum Li uptake capacity of B-pyridinic graphene. • Li gets better adsorbed on N-pyridinic graphene due to an additional p-p hybridization of the orbitals. This change in bonding mechanism causes significant distortion of the substrate. On the other hand, Li on B-pyridinic graphene shows ionic bonding character. • B-pyridinic graphene offers lower energy barrier for Li to diffuse across the substrate in comparison to N-pyridinic graphene. Thus, B-pyridinic graphene presents itself as a better anode material for lithium ion batteries due to optimal Li adsorption and better diffusion kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Effects of carbon nanotubes on twin and texture evolution of magnesium matrix composite during compression process

Highlights: • The CNTs existing at grain boundaries lead to stress concentration, and stimulate the formation of twins. • Crystal rotation and non-basal slip alternately dominate the deformation of the CNTs/Mg composite. • The texture changes from random texture to strong basal texture, strong non-basal texture at the three corresponding stages. • Crystal rotation and non-basal slip system are the main toughening mechanisms of the CNTs/Mg composite. - Abstract: A compression test is performed to investigate the effects of carbon nanotubes (CNTs) on twin and texture evolution of the 1.0 wt.% CNTs reinforced magnesium matrix (CNTs/Mg) composite. The compression process consists of elastic, yield and hardening stages, and the number of twin significantly increases at the yield stage. During the compression process, the crystal rotation and non-basal slip caused by twin shear alternately dominate the deformation of the 1.0 wt.% CNTs/Mg composite. The CNTs existing at grain boundaries lead to stress concentration, and the stress concentration stimulates the formation of twins at the yield stage. The formed twins interact with dislocations, result in crystal rotation and promotion of the non-basal slip system at the hardening stage under the effect of twin shear, thus, improve the toughness of the CNTs/Mg composite.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Multiscale approaches for optimizing the impact of strain on Na-ion battery cycle life

Abstract The high costs and geopolitical challenges inherent to the lithium-ion (Li-ion) battery supply chain have driven a rising interest in the development of sodium-ion (Na-ion) batteries as a potential alternative. Unfortunately, the larger ionic radius of Na limits the reversibility of cycling because of the extensive atomic rearrangements that accompany Na-ion insertion, which in turn limit diffusion and charging speed, and lead to rapid degradation of the electrodes. The Center for Strain Optimization for Renewable Energy (STORE) was established to address these challenges and develop new electrode materials for Na-ion cells. This article discusses the current state-of-the-art materials used in Na-ion cells and several directions that STORE believes are critical to understand and control the structural and volumetric changes during the reversible (de)insertion of large cations. Graphical abstract Highlights Understanding the fundamental way materials respond to localized strains at the atomic length-scale is a critical first step in the development of highly reversible, long cycle life, Na-ion insertion hosts. This perspective explores a variety of methods that can be employed to mitigate the detrimental effects of large strain. The insights gained from these investigations should help lay the foundation for the creation of more economical and sustainable batteries that could have immediate impact on global energy infrastructure. Discussion Although there is near universal agreement that electrochemical energy storage must be an integral part of a green-energy future, there is less agreement about how to reduce the cost of energy storage. Replacing high-cost lithium-ion cells with lower-cost sodium-ion batteries is one option frequently considered in future energy models, but the details of what can be achieve with optimized sodium cell performance remains unclear. Here we posit that developing methods to mitigating strain on the electrode particle length scale is a key factor for achieving long-cycle-life sodium-ion batteries. Mitigating strain on the atomic scale suppress electrode-level volume change. Allowing for fast cycling in materials without the problems of electrode cracking or delamination. We further posit that understanding volume change in sodium-ion electrodes at a fundamental level will lead to the designing new sodium-ion electrode materials that will allow for efficient, stable, lower-cost energy storage.

Brady, Michael J.↗
DOE OSTI2021

Changes in fire weather climatology under 1.5 °C and 2.0 °C warming

Abstract The 2015 Paris Agreement led to a number of studies that assessed the impact of the 1.5 °C and 2.0 °C increases in global temperature over preindustrial levels. However, those assessments have not actively investigated the impact of these levels of warming on fire weather. In view of a recent series of high-profile wildfire events worldwide, we access fire weather sensitivity based on a set of multi-model large ensemble climate simulations for these low-emission scenarios. The results indicate that the half degree difference between these two thresholds may lead to a significantly increased hazard of wildfire in certain parts of the world, particularly the Amazon, African savanna and Mediterranean. Although further experiments focused on human land use are needed to depict future fire activity, considering that rising temperatures are the most influential factor in augmenting the danger of fire weather, limiting global warming to 1.5 °C would alleviate some risk in these parts of the world.

Son, Rackhun (ORCID:000000023366495X)↗
DOE OSTI2024

Heterogeneous Nucleating Agent for High‐Boiling‐Point Nonhalogenated Solvent‐Processed Organic Solar Cells and Modules

Abstract High‐boiling‐point nonhalogenated solvents are superior solvents to produce large‐area organic solar cells (OSCs) in industry because of their wide processing window and low toxicity; while, these solvents with slow evaporation kinetics will lead excessive aggregation of state‐of‐the‐art small molecule acceptors (e.g. L8‐BO), delivering serious efficiency losses. Here, a heterogeneous nucleating agent strategy is developed by grafting oligo (ethylene glycol) side‐chains on L8‐BO (BTO‐BO). The formation energy of the obtained BTO‐BO; while, changing from liquid in a solvent to a crystalline phase, is lower than that of L8‐BO irrespective of the solvent type. When BTO‐BO is added as the third component into the active layer (e.g. PM6:L8‐BO), it easily assembles to form numerous seed crystals, which serve as nucleation sites to trigger heterogeneous nucleation and increase nucleation density of L8‐BO through strong hydrogen bonding interactions even in high‐boiling‐point nonhalogenated solvents. Therefore, it can effectively suppress excessive aggregation during growth, achieving ideal phase‐separation active layer with small domain sizes and high crystallinity. The resultant toluene‐processed OSCs exhibit a record power conversion efficiency (PCE) of 19.42% (certificated 19.12%) with excellent operational stability. The strategy also has superior advantages in large‐scale devices, showing a 15.03‐cm 2 module with a record PCE of 16.35% (certificated 15.97%).

Chemistry↗