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At least 1,477 records · Page 82

Combinatorial optimization and spatial remodeling of CYPs to control product profile

Activating inert substrates is a challenge in nature and synthetic chemistry, but essential for creating functionally active molecules. In this work, we used a combinatorial optimization approach to assemble cytochrome P450 monooxygenases (CYPs) and reductases (CPRs) to achieve a target product profile. By creating 110 CYP-CPR pairs and iteratively screening different pairing libraries, we demonstrated a framework for establishing a CYP network that catalyzes six oxidation reactions at three different positions of a chemical scaffold. Target product titer was improved by remodeling endoplasmic reticulum (ER) size and spatially controlling the CYPs’ configuration on the ER. Out of 47 potential products that could be synthesized, 86% of the products synthesized by the optimized network was our target compound quillaic acid (QA), the aglycone backbone of many pharmaceutically important saponins, and fermentation achieved QA titer 2.23 g/L.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing Correlations of Perovskite Catalytic Performance with Electronic Structure Descriptors

Electronic structure descriptors are computationally efficient quantities used to construct qualitative correlations for a variety of properties. In particular, the oxygen p-band center has been used to guide material discovery and fundamental understanding of an array of perovskite compounds for use in catalyzing the oxygen reduction and evolution reactions. Yet, an assessment of the effectiveness of the oxygen p-band center at predicting key measures of perovskite catalytic activity has not been made and would be highly beneficial to guide future predictions and codify best practices. In this work, we have used density functional theory at the Perdew–Burke–Ernzerhof (PBE), PBEsol, PBE + U, strongly constrained and appropriately normed functional, and Heyd–Scuseria–Ernzerhof (HSE06) levels to assess the correlations of numerous measures of catalytic performance for a series of technologically relevant perovskite oxides, using the bulk oxygen p-band center as an electronic structure descriptor. We have analyzed correlations of the calculated oxygen p-band center for all considered functionals with the experimentally measured X-ray emission spectroscopy oxygen p-band center and multiple measures of catalytic activity, including high-temperature oxygen reduction surface exchange rates, aqueous oxygen evolution current densities, and binding energies of oxygen evolution intermediate species. Our findings show that the best correlations for all measures of catalytic activity considered here are made with PBE-level calculations, with strong observed linear correlations with the bulk oxygen p-band center (R 2 = 0.81–0.87). This study illustrates that strong linear correlations between numerous important measures of catalytic activity and the oxygen p-band bulk descriptor can be obtained under a consistent computational framework, and these correlations can serve as a guide for future experiments and simulations for development of perovskite and related oxide catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solvated Nuclear–Electronic Orbital Structure and Dynamics

Nonadiabatic dynamical processes such as proton-coupled electron transfer and excited state intramolecular proton transfer have been the subject of much research. One of the promising theoretical methods to describe these processes is the nuclear–electronic orbital (NEO) approach. This approach inherently accounts for nuclear quantum effects within quantum chemistry calculations, and it has recently been extended to directly simulate nonadiabatic processes with the development of real-time NEO methods. These processes can also be significantly dependent on the surrounding chemical environment, however, and capturing the effects of the environment is often necessary for analyzing experimentally relevant systems. This work couples the NEO density functional theory and real-time time-dependent density functional theory approaches with solvation through the polarizable continuum model. Here, the effects of this coupling are investigated for ground state properties, solvent-dependent vibrational frequencies, and direct excited state intramolecular proton transfer dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tensor Network Path Integral Study of Dynamics in B850 LH2 Ring with Atomistically Derived Vibrations

The recently introduced multisite tensor network path integral (MS-TNPI) allows simulation of extended quantum systems coupled to dissipative media. We use MS-TNPI to simulate the exciton transport and the absorption spectrum of a B850 bacteriochlorophyll (BChl) ring. The MS-TNPI network is extended to account for the ring topology of the B850 system. Accurate molecular-dynamics-based description of the molecular vibrations and the protein scaffold is incorporated through the framework of Feynman–Vernon influence functional. To relate the present work with the excitonic picture, an exploration of the absorption spectrum is done by simulating it using approximate and topologically consistent transition dipole moment vectors. Comparison of these numerically exact MS-TNPI absorption spectra are shown with second-order cumulant approximations. Finally, the effect of temperature on both the exact and the approximate spectra is also explored.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗

Complex Fluorine Chemical Potential Effects on the Shape and Compositional Heterogeneity of KTa 1– x Nb x O 3 Nanoparticles

When kinetic conditions dominate and dictate the growth in a nanoparticle synthesis, properties of the synthesis environment can have considerable effects on the properties of the products. Such effects were studied here, where the solution environment was changed via the addition of KF to the hydrothermal syntheses of KTa 1– x Nb x O 3 and KTaO 3 . One result demonstrated the straightforward cause-and-effect relationship between the solution and reaction kinetics: KF directly increased the solution stability of the Ta species and therefore decreased its reaction rate, resulting in a change in composition heterogeneity of Ta and Nb in the KTa 1– x Nb x O 3 particles. However, not all effects are so simple; changing the chemical potential of the solution with KF can also promote the formation of particles with anisotropic defect enhanced kinetic Wulff shapes instead of cuboidal shapes. The increased F chemical potential in the solution enabled the formation of planar defects in the bulk, which accelerated growth in-plane to form particles characterized by flat rectangular flake geometries. In this work, thermodynamic modeling with density functional theory calculations confirmed that sufficient KF concentrations can drive the formation of a defect phase K n +1 Ta n O 3 n F.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Roles of Pseudo-Closed s 2 Orbitals for Different Intrinsic Hole Generation between Tl–Bi and In–Bi Bromide Double Perovskites

Although metal halide double perovskites A 2 B(I)B(III)X 6 are expected as nontoxic alternatives for lead halide perovskites, recent studies have shown that only Tl(I)–Bi(III) and In(I)–Bi(III) bromides are thermodynamically stable and possess optoelectronic properties suitable for photovoltaic absorbers. In this work, we show, through density functional theory calculations, that Tl–Bi and In–Bi bromide double perovskites exhibit significantly different semiconducting behaviors due to the different energy levels of the highest-occupied pseudoclosed s 2 orbitals of Tl(I) and In(I). While Tl–Bi double perovskites can exhibit semiconducting $p$-type properties, In–Bi bromide double perovskites exhibit metallic $p$-type ones regardless of the synthesis condition due to the extremely low formation energy of In vacancy. Such difference makes Tl–Bi bromide double perovskites suitable for optoelectronic applications, but not In–Bi bromide double perovskites. Furthermore, there is a high probability for In to substitute a Bi site, forming a local In–In bromide double perovskite structure with a lower local conduction band minimum, detrimentally affecting the open circuit voltage of In–Bi bromide double perovskite-based thin film solar cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of Metal Identity on Light-Induced Switchable Adsorption in Azobenzene-Based Metal–Organic Frameworks

Energy-efficient capture and release of small gas molecules, particularly carbon dioxide (CO 2 ) and methane (CH 4 ), are of significant interest in academia and industry. Porous materials such as metal–organic frameworks (MOFs) have been extensively studied, as their ultrahigh porosities and tunability enable significant amounts of gas to be adsorbed while also allowing specific applications to be targeted. However, because of the microporous nature of MOFs, the gas adsorption performance is dominated by high uptake capacity at low pressures, limiting their application. Hence, methods involving stimuli-responsive materials, particularly light-induced switchable adsorption (LISA), offer a unique alternative to thermal methods. Here, we report the mechanism of a well-known LISA system, the azobenzene-based material PCN-250, for CO 2 and CH 4 adsorption. There is a noticeable difference in the LISA effect dependent on the metal cluster involved, with the most significant being PCN-250-Al, where the adsorption can change by 83.1% CH 4 and 56.1% CO 2 at 298 K and 1 bar and inducing volumetric storage changes of 36.2 and 33.9 cm 3 /cm 3 at 298 K between 5 and 85 bar (CH 4 ) and 2 and 9 bar (CO 2 ), respectively. Using UV light in both single-crystal X-ray diffraction and gas adsorption testing, we show that upon photoirradiation, the framework undergoes a “localized heating” phenomenon comparable to an increase of 130 K for PCN-250-Fe and improves the working capacity. Furthermore, this process functions because of the constrained nature of the ligand, preventing the typical trans-to-cis isomerization observed in free azobenzene. In addition, we observed that the degree of localized heating is highly dependent on the metal cluster involved, with the series of isostructural PCN-250 systems showing variable performance based upon the degree of interaction between the ligand and the metal center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Morphology-Controlled Discharge Profile and Reversible Cu Extrusion and Dissolution in Biomimetic CuS

Metal sulfides, such as CuS, SnS2, Co9S8, MoS2, are high capacity anode materials for Li-ion batteries. However, these materials go through a conversion reaction with Li+, which is accompanied by the phase transformation and inevitably results in a huge volume expansions, therefore causing performance degradation. Here, we report nanoscale engineering route to efficiently control the overall volume expansion for enhanced performance. We engineered CuS with nanoplate assembly on a nanostring, leading to a nanostructure of mimicking the crassula baby necklace (CBN) in the natural plant. Using in-situ transmission electron microscopy (in-situ TEM), we probed the lithiation kinetics and dynamic structural transformations. Due to the linkage of the central nanostring, the CuS CBN exhibited fast Li+ diffusion along the axial direction and high mechanical stability during lithiation. The volume expansion was minimal for the CuS CBN due to the pre-engineered gap between these plates. The CuS followed a two-step lithiation process with Cu2S and Li2S formation as the first step and Cu extrusion from Cu2S in the later stage. Interestingly, during the Cu2S to Cu conversion, there was a incubation period before the metallic Cu extrusion, which is featured by the formation of an amorphous structure due to the large lattice strain and distortion associated with the displacement of Cu by Li ions. In the final stage, the lithiated amorphous phase recrystallized to a composite of Cu nanocrystals dispersed in a polycrystalline Li2S matrix. Associate with the nanoscale size, the Cu nanocrystals can reversibly dissolve into the matrix upon delithiation. The present work demonstrates tailoring of desired functionality through nanoscale engineering of using bionic methods.

Han, Shaobo↗

Accelerated Synthesis of Ordered Mesoporous Carbons Using Plasma

Conventional ordered mesoporous carbon (OMC) production usually requires long processing times in the carbonization step to achieve desired temperatures through controlled ramps. To enable expedited materials discovery, developing advanced manufacturing capability with significantly improved throughput is highly desired. Current approaches for accelerating the synthesis of OMCs include using microwave and Joule heating. However, both methods rely on the introduction of additional components, such as microwave absorbers and electrically conductive agents, within the bulk materials to impart the ability to reach high carbonization temperatures. This work demonstrates accelerated synthesis and functionalization of OMCs through the use of a dielectric barrier discharge plasma, where carbonization can be accomplished within 15 min using 30 W plasma sources, representing more than an order of magnitude increase in polymer-to-carbon conversion kinetics compared to that of a traditionally pyrolyzed analogue. Particularly, the ability of performing rapid carbonization without the use of additional substrates within the OMC precursor systems is advantageous. A systematic investigation of how plasma power, time, and gas atmosphere impact the resulting OMC pore textures and properties is performed, demonstrating the broad applicability of plasma-enabled carbonization methods. Furthermore, we demonstrate that the plasma treatment strategy can be extended to incorporate heteroatoms into the carbon framework by introducing ammonia gas, resulting in OMCs with a nitrogen content up to 4.7 at %, as well as non-Pluronic templating systems for synthesizing OMC with pore sizes larger than 10 nm. As employing a plasma source for materials pyrolysis is an industrially relevant approach, our system can be extended toward scaled synthesis of OMCs with much faster production rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Shape-Shifting Peptide Nanomaterials: Surface Asymmetry Enables pH-Dependent Formation and Interconversion of Collagen Tubes and Sheets

The fabrication of dynamic, transformable biomaterials that respond to environmental cues represents a significant step forward in the development of synthetic materials that rival their highly functional, natural counterparts. In this work, we describe the design and synthesis of crystalline supramolecular architectures from charge-complementary heteromeric pairs of collagen-mimetic peptides (CMPs). Under appropriate conditions, CMP pairs spontaneously assemble into either 1D ultraporous (pore diameter >100 nm) tubes or 2D bilayer nanosheets due to the structural asymmetry that arises from heteromeric self-association. Crystalline collagen tubes represent a heretofore unobserved morphology of this common biomaterial. In-depth structural characterization from a suite of biophysical methods, including TEM, AFM, high-resolution cryo-EM, and SAXS/WAXS measurements, reveals that the sheet and tube assemblies possess a similar underlying lattice structure. The experimental evidence suggests that the tubular structures are a consequence of the self-scrolling of incipient 2D layers of collagen triple helices and that the scrolling direction determines the formation of two distinct structural isoforms. Furthermore, we show that nanosheets and tubes can spontaneously interconvert through manipulation of the assembly pH and systematic adjustment of the CMP sequence. Altogether, we establish initial guidelines for the construction of dynamically responsive 1D and 2D assemblies that undergo a structurally programmed morphological transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Crystallizing Atomic Xenon in a Flexible MOF to Probe and Understand Its Temperature-Dependent Breathing Behavior and Unusual Gas Adsorption Phenomenon

Flexible metal–organic frameworks (MOFs) hold great promise as smart materials for specific applications such as gas separation. These materials undergo interesting structural changes in response to guest molecules, which is often associated with unique adsorption behavior not possible for rigid MOFs. Understanding the dynamic behavior of flexible MOFs is crucial yet challenging as it involves weak host–guest interactions and subtle structural transformation not only at the atomic/molecular level but also in a nonsteady state. Here we report an in-depth study on the adsorbate- and temperature-dependent adsorption in a flexible MOF by crystallizing atomic gases into its pores. Mn(ina)2 shows an interesting temperature-dependent response toward noble gases. Its nonmonotonic, temperature-dependent adsorption profile results in an uptake maximum at a temperature threshold, a phenomenon that is unusual. Full characterization of Xe-loaded MOF structures is performed by in situ single-crystal and synchrotron X-ray diffraction, IR spectroscopy, and molecular modeling. The X-ray diffraction analysis offers a detailed explanation into the dynamic structural transformation and provides a convincing rationalization of the unique adsorption behavior at the molecular scale. The guest and temperature dependence of the structural breathing gives rise to an intriguing reverse of Xe/Kr adsorption selectivity as a function of temperature. The presented work may provide further understanding of the adsorption behavior of noble gases in flexible MOF structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Probe-Enabled Approach for the Selective Isolation and Characterization of Functionally Active Subpopulations in the Gut Microbiome

Increasing evidence has shown that microorganisms present in the mammalian gut have a major impact on the metabolism of xenobiotics – chemicals foreign to the body including drugs and environmental contaminants – either by modulating host metabolism or by transforming xenobiotics or their metabolites directly. Being able to predict these interactions will be critical to develop precision medicine strategies utilizing the gut microbiota. However, current knowledge of which microbes are responsible for a given activity is severely limited and is further complicated by the sheer diversity of gut microbes between individuals. Current approaches including metagenomic and metatranscriptomic analyses can only identify enzymes and organisms that have the potential to catalyze a specific reaction, but cannot determine if an enzyme is truly active within the gut. To identify the microorganisms that are directly responsible for an activity in the gut of an individual, new functional approaches are needed. Here, we present an activity-based probe (ABP) approach to define the microbial populations responsible for a specific xenobiotic metabolizing activity. We developed an ABP for β-glucuronidases, enzymes capable of reversing a major pathway in phase II metabolism that is responsible for xenobiotic elimination. Using this ABP, we covalently labelled active β-glucuronidases both in vitro and in bacterial cells in the mouse gut microbiota. Cells possessing β-glucuronidase activity were then fluorescently labeled, isolated using fluorescence-activated cell sorting (FACS), and identified by sequencing. We found that glucuronidase active bacteria in the murine gut are taxonomically diverse, and even within phyla the taxa displaying function are highly disparate. Perturbation of the gut microbiota with vancomycin decreased but did not eliminate β-glucuronidase activity, which corresponded to a shift in the β-glucuronidase active population. These data demonstrate that the metabolic activity of the gut microbiota can be plastic and that during perturbation, functional capacity may be maintained by phylogenetically disparate populations. This work highlights the utility of ABPs to identify currently unknown functional microbial subpopulations responsible for a specific activity of interest within the gut of an individual.

Whidbey, Christopher↗

Revealing High Na-Content P2-Type Layered Oxides as Advanced Sodium-Ion Cathodes

Layered Na-based oxides with the general composition of Na x TMO 2 (TM: transition metal) have attracted significant attention for their high compositional diversity that provides tunable electrochemical performance for electrodes in sodium-ion batteries. The various compositions bring forward complex structural chemistry that is decisive for the layered stacking structure, Na-ion conductivity, and the redox activity, potentially promising new avenues in functional material properties. In this work, we have explored the maximum Na content in P2-type layered oxides and discovered that the high-content Na in the host enhances the structural stability; moreover, it promotes the oxidation of low-valent cations to their high oxidation states (in this case Ni 2+ ). This can be rationalized by the increased hybridization of the O(2p)-TM(3d-e g *) states, affecting both the local TM environment as well as the interactions between the NaO 2 and TMO 2 layers. These properties are highly beneficial for the Na storage capabilities as required for cathode materials in sodium-ion batteries. It leads to excellent Na-ion mobility, a large storage capacity (>100 mAh g –1 between 2.0-4.0 V), yet preventing the detrimental sliding of the TMO 2 layers (P2–O2 structural transition), as reflected by the ultralong cycle life (3000 (dis)charge cycles demonstrated). These findings expand the horizons of high Na-content P2-type materials, providing new insights of the electronic and structural chemistry for advanced cathode materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Load‐Balancing Intense Physics Calculations to Embed Regionalized High‐Resolution Cloud Resolving Models in the E3SM and CESM Climate Models

Abstract We design a new strategy to load‐balance high‐intensity sub‐grid atmospheric physics calculations restricted to a small fraction of a global climate simulation's domain. We show why the current parallel load balancing infrastructure of Community Earth System Model (CESM) and Energy Exascale Earth Model (E3SM) cannot efficiently handle this scenario at large core counts. As an example, we study an unusual configuration of the E3SM Multiscale Modeling Framework (MMF) that embeds a binary mixture of two separate cloud‐resolving model grid structures that is attractive for low cloud feedback studies. Less than a third of the planet uses high‐resolution (MMF‐HR; sub‐km horizontal grid spacing) relative to standard low‐resolution (MMF‐LR) cloud superparameterization elsewhere. To enable MMF runs with Multi‐Domain cloud resolving models (CRMs), our load balancing theory predicts the most efficient computational scale as a function of the high‐intensity work's relative overhead and its fractional coverage. The scheme successfully maximizes model throughput and minimizes model cost relative to precursor infrastructure, effectively by devoting the vast majority of the processor pool to operate on the few high‐intensity (and rate‐limiting) high‐resolution (HR) grid columns. Two examples prove the concept, showing that minor artifacts can be introduced near the HR/low‐resolution CRM grid transition boundary on idealized aquaplanets, but are minimal in operationally relevant real‐geography settings. As intended, within the high (low) resolution area, our Multi‐Domain CRM simulations exhibit cloud fraction and shortwave reflection convergent to standard baseline tests that use globally homogenous MMF‐LR and MMF‐HR. We suggest this approach can open up a range of creative multi‐resolution climate experiments without requiring unduly large allocations of computational resources.

54 ENVIRONMENTAL SCIENCES↗

Massively parallel reporter assays and mouse transgenic assays provide correlated and complementary information about neuronal enhancer activity

High-throughput massively parallel reporter assays (MPRAs) and phenotype-rich in vivo transgenic mouse assays are two potentially complementary ways to study the impact of noncoding variants associated with psychiatric diseases. Here, we investigate the utility of combining these assays. Specifically, we carry out an MPRA in induced human neurons on over 50,000 sequences derived from fetal neuronal ATAC-seq datasets and enhancers validated in mouse assays. We also test the impact of over 20,000 variants, including synthetic mutations and 167 common variants associated with psychiatric disorders. We find a strong and specific correlation between MPRA and mouse neuronal enhancer activity. Four out of five tested variants with significant MPRA effects affected neuronal enhancer activity in mouse embryos. Mouse assays also reveal pleiotropic variant effects that could not be observed in MPRA. Our work provides a catalog of functional neuronal enhancers and variant effects and highlights the effectiveness of combining MPRAs and mouse transgenic assays.

Kosicki, Michael↗

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of MOFs carried out using multiple density functional approximations. Compared to more accurate hybrid functionals, we find that the widely used PBE generalized gradient approximation (GGA) functional severely underpredicts MOF band gaps in a largely systematic manner for semi-conductors and insulators without magnetic character. However, an even larger and less predictable disparity in the band gap prediction is present for MOFs with open-shell 3 d transition metal cations. With regards to partial atomic charges, we find that different density functional approximations predict similar charges overall, although hybrid functionals tend to shift electron density away from the metal centers and onto the ligand environments compared to the GGA point of reference. Much more significant differences in partial atomic charges are observed when comparing different charge partitioning schemes. We conclude by using the dataset of computed MOF properties to train machine-learning models that can rapidly predict MOF band gaps for all four density functional approximations considered in this work, paving the way for future high-throughput screening studies. To encourage exploration and reuse of the theoretical calculations presented in this work, the curated data is made publicly available via an interactive and user-friendly web application on the Materials Project.

36 MATERIALS SCIENCE↗

Ionic liquids improve the long-term stability of perovskite solar cells

Achieving operational stability in halide perovskite solar cells remains a critical challenge for commercialization. Ionic liquids are promising bulk modifiers, yet their mechanistic role in perovskite crystallization is poorly understood. Here we engineered an ionic liquid, methoxyethoxymethyl-1-methylimidazole chloride (MEM-MIM-Cl), with an ethylene glycol ether side chain that regulates perovskite growth and stabilizes buried interfaces via synergistic interactions with NiO x . MEM-MIM-Cl induces a novel intermediate phase through chelation with undercoordinated Pb(II), suppressing defects and defect-induced degradation. Solar cells incorporating MEM-MIM-Cl achieved a power conversion efficiency of 25.9% and retained 90% of their initial performance after 1,500 h under continuous 1-sun illumination and 90 °C thermal stress—surpassing prior benchmarks under milder ageing conditions. Furthermore, diurnal cyclic ageing revealed unprecedented fatigue resistance, highlighting the dual role of MEM-MIM-Cl in simultaneously enhancing efficiency and operational resilience. In conclusion, this work elucidates design principles for functional ionic liquids while advancing perovskite photovoltaics towards industrial viability.

14 SOLAR ENERGY↗