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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic–inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. Here, to understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31–calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ∼2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31–calcite interactions. While this work provides the first experimental confirmation that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31–calcite interface has advanced our fundamental understanding of the atomic interactions at the organic–inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Close, Emily G. S. [Pacific Northwest National Lab↗
DOE OSTI2025

DataSet for Elucidating molecular level interfacial interactions between a de novo protein and nucleated calcite with solid-state NMR

Biomineralization is the process by which organisms use biomolecules to produce hierarchically structured organic-inorganic composites. Using biology as inspiration, a protein construct (FD31) was previously designed to accelerate formation of nano-calcite with an unconventional {110} face. To understand the molecular interactions essential for protein aided calcite nucleation, solid-state nuclear magnetic resonance (ssNMR) spectroscopy was used in this work to characterize the FD31-calcite interface at the atomic level. Glutamic acid side chains designed to interact directly with calcium ions on the surface were found to have dynamics on the sub-millisecond timescale, indicating possible interactions between the protein and surface waters that were not included in the original model. Dipolar ssNMR recoupling techniques also showed that the protein backbone is ~2 Å closer to the surface than in the original docking model. Refined molecular simulations were done in the presence of explicit waters, which resulted in the protein backbone closer to the surface than in the original docking structure, providing better agreement with experiment and highlighting the important role played by water in FD31-calcite interactions. These studies provide the first experimental evidence to confirm that FD31 interactions with calcite are localized to the surface of the protein designed to serve as a template. However, these studies do indicate a more dynamic binding and closer binding mode between FD31 and the nucleated surface than originally proposed. In all, this enhanced molecular insight into the FD31-calcite interface has advanced our fundamental understanding of the atomic interactions at the organic-inorganic interface and will aid in the design of biological templates for the nucleation of inorganic crystals.

Saccuzzo Close, Emily Grace [Pacific Northwest Nat↗
DOE OSTI2024

Molecular origin of viscoelasticity and influence of methylation in mesophase pitch

The viscoelastic and thermomechanical properties of pitches are responsible for their melt-spinning behavior, which is a critical step for manufacturing high-performance pitch-based carbon fibers. Here, we systematically explore the impact of methyl group modifications on the viscoelastic and thermal properties of mesophase pitches. We employ a range of atomistic modeling approaches, including Density Functional Theory (DFT), Density Functional Tight Binding (DFTB), and Classical Molecular Mechanics (MM), to provide detailed insights into the molecular interactions and structural changes. Further, our results revealed the molecular mechanisms that promote layered structures leading to the anisotropic nature of the viscoelastic behavior of mesophase pitch. Furthermore, we propose a modified molecular representation of naphthalene-based mesophase pitch based on the analysis of x-ray diffraction measurements. This study provides fundamental insights into the molecular structures of mesophase pitch and the role of methyl groups controlling its viscosity, which offer valuable insights into mesophase-based carbon fiber production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Conserving asphalt resources: Rethinking rejuvenator performance evaluation through peptizing efficiency

Timely rejuvenation and restoration of asphalt are essential conservation practices that help preserve and extend the service life of roads, bridges, driveways, and parking lots. The performance of asphalt rejuvenators is often assessed based on their diffusion rates and softening power, yet these metrics alone fail to capture true rejuvenation potential. Here, this study integrates density functional theory (DFT) modeling with experimental analysis to show that rejuvenation effectiveness is primarily governed by molecular interactions with oxidized asphaltene nanoaggregates. DFT results revealed that amide- and unsaturated-chain compounds, such as hexadecanamide, oleic acid, and 9,17-octadecadienal, act cooperatively to disrupt π–π stacking and exfoliate asphaltene layers, reducing binding strength and enhancing dispersion. Unlike bulky, rigid molecules that remain trapped, these components remain mobile and repeatedly interact with multiple aggregation sites. Experimental validation using rheometry and FTIR confirmed that such molecularly compatible rejuvenators restore the binder flexibility and polydispersity, even when diffusion is relatively slow. Building on this mechanistic foundation, six rejuvenators (A2, A5, A7, A8, A9, and A10) were evaluated using a three-metric performance framework encompassing cracking resistance (Glover–Rowe parameter), UV stability, and surface hydrophobicity. Among the six rejuvenators evaluated, A9 exhibited the highest overall performance, reducing the Glover–Rowe cracking parameter by 85% (from 351 kPa to 53 kPa), demonstrating the greatest resistance to UV-induced aging with a stability index of 4.17 h·kPa⁻¹, and increasing surface hydrophobicity to a contact angle of 103.6°. Its superior performance is primarily attributed to its amide- and unsaturated-chain components, which act cooperatively to disrupt π–π stacking interactions and exfoliate asphaltene layers, thereby promoting molecular deagglomeration and enhancing long-term durability. These results shift the criteria for selecting rejuvenators: effective candidates must pair the electronic capability to unlock aged asphaltenes with sufficient structural stability to resist secondary aging and restore hydrophobicity. Restoring hydrophobicity is critical, as aging reduces the asphalt’s water repellency and increases water diffusion, which in turn accelerates moisture-related damage; consequently, a high-performing rejuvenator must effectively restore the binder’s hydrophobic characteristic. Collectively, these findings provide a framework for the rational design of next-generation of bio-based rejuvenators that enhance pavement longevity and promote long-term sustainability.

Aging↗
DOE OSTI2025

Spectral decomposition of human BCL2 bonded to a PROTAC

In this study, we have decomposed the linear infrared spectra and two-dimensional infrared spectroscopy of a VHL-recruiting Proteolysis-targeting chimera (PROTAC) complex with BCL-2 to understand the spectral signatures of this complex. Our findings show that both VHL and BCL-2 units have distinct spectral signatures that contribute to the total spectra in different regions. Furthermore, we observed that the interaction between VHL and BCL-2 within the PROTAC complex leads to unique spectral features, indicating a strong synergistic effect. Through detailed analysis, specific bands were identified that correspond to the vibrational modes of the individual components, as well as their interactive modes within the complex. This study provides valuable insight into the molecular interactions within the PROTAC complex, offering a deeper understanding of its structure and function. These insights could be pivotal in designing more efficient PROTACs for targeted protein degradation in therapeutic applications.

Nauta, Wiestke [University of Groningen]↗
DOE OSTI2024

Investigation of mechanochemical interactions of hydrogen with earth materials in a subsurface gas storage

The goal of this project is to investigate the molecular interactions of H 2 with earth materials (EMs) that may potentially affect economics and safety of H 2 geological storage (HGS). We investigated (1) the H 2 intercalation into interlayers of phyllosilicates, (2) the competitive adsorption of H 2 /CH 4 onto porous materials, and (3) solubility of H 2 in interfacial and confined hydrocarbons. Our results indicate that (i) H 2 intercalation into hydrated interlayers is thermodynamically unfavorable and H 2 solubility in hydrated clay interlayers is in the same order of magnitude as that in bulk water, (ii) CH 4 outcompetes H 2 in adsorption onto kerogen, due to stronger CH 4 -kerogen interactions than H 2 -kerogen interactions, (iii) H 2 tends to dissolve more in oil than in water, and the introduction of CO 2 as a cushion gas reduces H 2 partitioning near the kaolinite surfaces. The outcomes provide foundational knowledge for preparing the USA for future storage site selection and storage system design, supporting DOE missions in clean and secured energy.

08 HYDROGEN↗
DOE OSTI2025

Covalent Drug Binding in Live Cells Monitored by Mid-Infrared Quantum Cascade Laser Spectroscopy: Photoactive Yellow Protein as a Model System

The detection of drug-target interactions in live cells enables analysis of therapeutic compounds in a native cellular environment. Recent advances in spectroscopy and molecular biology have facilitated the development of genetically encoded vibrational probes like nitriles that can sensitively report on molecular interactions. Nitriles are powerful tools for measuring electrostatic environments within condensed media like proteins, but such measurements in live cells have been hindered by low signal-to-noise ratios. In this study, we design a spectrometer based on a double-beam quantum cascade laser (QCL)-based transmission infrared (IR) source with balanced detection that can significantly enhance sensitivity to nitrile vibrational probes embedded in proteins within cells compared to a conventional FTIR spectrometer. Here, using this approach, we detect small-molecule binding in Escherichia coli, with particular focus on the interaction between para-Coumaric acid (pCA) and nitrile-incorporated photoactive yellow protein (PYP). This system effectively serves as a model for investigating covalent drug binding in a cellular environment. Notably, we observe large spectral shifts of up to 15 cm –1 for nitriles embedded in PYP between the unbound and drug-bound states directly within bacteria, in agreement with observations for purified proteins. Such large spectral shifts are ascribed to the changes in the hydrogen-bonding environment around the local environment of nitriles, accurately modeled through high-level molecular dynamics simulations using the AMOEBA force field. Our findings underscore the QCL spectrometer’s ability to enhance sensitivity for monitoring drug–protein interactions, offering new opportunities for advanced methodologies in drug development and biochemical research.

chromophores↗
DOE OSTI2025

Deep potential molecular dynamics simulations of ion-enhanced etching of silicon by atomic chlorine

The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.

Artificial neural networks↗
DOE OSTI2024

Effect of Molecular Conformation on Intermolecular Interactions and Photovoltaic Performances of Giant Molecule Acceptors

The molecular conformation of giant molecule acceptors (GMAs) plays a significant role in regulating the intermolecular interactions and their photovoltaic performances in organic solar cells (OSCs). For the linear GMA GT‐l, the stronger homo‐molecular interaction causes its aggregation being weakly affected by the donor, thus forming an ordered molecular stacking and proper phase separation in its blend film. The star‐shaped GMA GT‐s‐based blend film shows a dominant hetero‐molecular interaction that suppresses the aggregation of the donor and acceptor, resulting in smaller phase separation and more uniform vertical phase distribution. While for another star‐shaped GMA GTs, the weakest hetero‐molecular interaction causes its blend film to form larger phase separation. Therefore, the GT‐l based OSC with PM6 as donor shows the highest charge mobilities, the fastest charge transfer (CT) process, reduced energy loss and less charge recombination, contributing to a higher power conversion efficiency (PCE) of 19.03%. Comparatively, the PCEs of the OSCs based on GTs and GT‐s are 18.05% and 17.58% respectively. Notably, all the three GMAs based OSCs show excellent thermal stability and long‐term storage stability. This study provides a facile strategy by tuning the linking unit and its connecting mode for designing highly efficient and stable organic photovoltaic materials.

Chemistry↗
DOE OSTI2025

Investigating intermolecular interactions among CO 2 , water and PEEK-ionene membrane using cryo ToF-SIMS and isotopic labeling

Cryogenic time-of-flight secondary ion mass spectrometry (cryo ToF-SIMS) has emerged as a powerful tool for investigating molecular interactions, speciation, and dynamics in materials for CO 2 capture. In this study, we apply cryo ToF-SIMS to probe interactions between CO 2 , water, and PEEK-ionene membranes—a promising material for direct CO 2 capture due to its selectivity, durability, and efficiency. Despite this potential, the mechanisms governing CO 2 diffusion and the influence of water vapor on CO 2 behavior remain unclear. To address this, we loaded PEEK-ionene membranes with 13 CO 2 and D 2 O and employed cryo ToF-SIMS to visualize the 3D distribution of CO 2 and water within the membrane. While prior studies suggest that 13 CO 2 is absorbed under ambient conditions, our cryo ToF-SIMS analysis revealed no enhancement of the 13 C/ 12 C ratio, suggesting weak CO 2 -membrane interactions. As a result, CO 2 vaporizes even at low temperatures (−140°C) under vacuum conditions. In contrast, D 2 O displayed a relatively homogeneous distribution in the membrane, suggesting stronger water-membrane interactions via hydrogen bonding (18–20 kJ/mol). Interestingly, CO 2 was not detected in D 2 O-loaded membranes, indicating minimal interference from water vapor on CO 2 diffusion. As a comparison, the cryo ToF-SIMS data show that 13 CO 2 can readily react with a basic Na 2 CO 3 aqueous solution to form NaH 13 CO 3 . These findings demonstrate cryo ToF-SIMS as a critical technique for understanding gas-water-membrane interactions, offering insights for membrane functionalization to improve CO 2 capture efficiency.

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

Anisotropic interactions for continuum modeling of protein–membrane systems

In this work, a model for anisotropic interactions between proteins and cellular membranes is proposed for large-scale continuum simulations. The framework of the model is based on dynamic density functional theory, which provides a formalism to describe the lipid densities within the membrane as continuum fields while still maintaining the fidelity of the underlying molecular interactions. Within this framework, we extend recent results to include the anisotropic effects of protein–lipid interactions. As applications, we consider two membrane proteins of biological interest: a RAS–RAF complex tethered to the membrane and a membrane embedded G protein-coupled receptor. A strong qualitative and quantitative agreement is found between the numerical results and the corresponding molecular dynamics simulations. Combining the scope of continuum level simulations with the details from molecular level particle simulations enables research into protein–membrane behaviors at a more biologically relevant scale, which crucially can also be accessed via experiment.

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

Storage-Induced Collapse of Lignin Macromolecular Structure and Its Impacts on the Biorefinery

Lignin plays a vital role in the economics of biorefineries, serving as a source of process energy and a feedstock for sustainable fuels and chemical production. While understanding lignin’s chemical composition is crucial, emerging evidence suggests that a more comprehensive understanding of its macromolecular structure is critical to explaining its complex behavior in the biorefinery. This study investigated the partial collapse of the lignin network in corn stover feedstock after harvest and storage as a result of the microbial digestion of hemicellulose. Fluorescence microscopy was used to detect the collapse of lignin in terms of lignin’s inter-molecular interaction and the re-orientation of lignin’s chromophores, by the changes in lignin’s fluorescence lifetime, anisotropy, and the number of effective emitters. With minimal sample perturbation, our in-situ microscopic results revealed lignin's coil-globule transition phenomena, which was only previously predicted by molecular dynamics modeling extracted lignin in solvent. This collapse of lignin macromolecular structure was confirmed by results from NMR, IR, Raman, and powder X-ray diffraction. We also investigated the impact of this storage-induced collapse on the downstream biorefinery processes. Our study revealed that the two major approaches for lignin valorization in the lignin-first biorefinery model, namely monomer extraction and milled wood lignin extraction, were negatively impacted by the lignin collapse. As changes during storage are a source of feedstock variability, our study highlights the importance of understanding the effect of feedstock handling on biorefinery operations and economics.

09 BIOMASS FUELS↗
DOE OSTI2024

Inferring effective electrostatic interaction of charge-stabilized colloids from scattering using deep learning

In this article, an innovative strategy is presented that incorporates deep auto-encoder networks into a least-squares fitting framework to address the potential inversion problem in small-angle scattering. To evaluate the performance of the proposed approach, a detailed case study focusing on charged colloidal suspensions was carried out. The results clearly indicate that a deep learning solution offers a reliable and quantitative method for studying molecular interactions. The approach surpasses existing deterministic approaches with respect to both numerical accuracy and computational efficiency. Overall, this work demonstrates the potential of deep learning techniques in tackling complex problems in soft-matter structures and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Strong Effect of Nonpolar Solvent Molecular Structure on CdSe Nanoplatelet Stacking

We report a drastic difference in stacking behavior of oleic acid-stabilized 4-monolayer (4 ML) CdSe nanoplatelets (NPLs) in toluene and methylcyclohexane (MCH), two nonpolar solvents that differ in the conformational flexibility of their molecules. Using liquid cell transmission electron microscopy (TEM) and small angle scattering (SAXS) techniques, we show that NPLs form microns-long ribbons consisting of 4 ML CdSe NPLs in toluene, the solvent widely used to form stable colloidal solutions of a broad range of quasi-spherical nanoparticles. In contrast, 4 ML CdSe NPLs are well dispersed in MCH. The difference in stacking behavior of NPLs in toluene and MCH suggests that the conformational flexibility of the solvent molecules, such as the ability to adopt multiple chair conformations, modulates nanoplatelet interactions. Molecular dynamics (MD) simulations reveal that solvent molecules subtly alter the structure of the organic ligand shell. These solvent-dependent changes propagate to the inorganic core, modulating the degree of CdSe nanoplatelet (NPL) twisting and, consequently, the properties of the nanoparticles. We show that toluene better solvates oleate ligands while MCH induces a bimodal oleate span distribution, which can lead to increased solubility of CdSe NPLs. In addition, the solvent can also influence the inorganic core, which, in turn, can modify the nanoparticle properties. We demonstrate that destabilization of toluene solution containing ribbons of 4 ML CdSe NPLs without CdS shells results in the formation of NPL assemblies with amplified spontaneous emission (ASE) with a low threshold of 14 µJ cm−2 that is comparable with that of CdSe/CdS core/shell NPLs. Our results emphasize that the solvent plays a major role in mediating interactions between NPLs and hence their processability for fabrication of functional structures.

CdSe↗
DOE OSTI2025

Predicting receptor-ligand pairing preferences in plant-microbe interfaces via molecular dynamics and machine learning

Microbiome assembly, structure, and dynamics significantly influence plant health. Secreted microbial signaling molecules initiate and mediate symbiosis by binding to structurally compatible plant receptors. For example, lipo-chitooligosaccharides (LCOs), produced by nitrogen-fixing rhizobial bacteria and various fungi, are recognized by plant lysin motif receptor-like kinases (LysM-RLKs), which activate the common symbiotic pathway. Accurately predicting these molecular interactions could reveal complementary signatures underlying the initial stages of endosymbiosis. Despite the breakthrough in protein-ligand structure prediction with deep learning-based tools, such as AlphaFold3, the large size and highly flexible nature of signaling compounds like LCOs present major challenges for detailed structural characterization and binding-affinity prediction. Typical structure-/physics-based methods of ligand virtual screening are designed for small, drug-like molecules, often rely on high-resolution, experimentally determined structures of the protein receptors, and rarely achieve sufficient sampling to obtain converged thermodynamic quantities with large ligands. In this study, we developed a hybrid molecular dynamics/machine learning (MD/ML) approach capable of predicting binding affinity rankings with high accuracy in systems involving large, flexible ligands, despite limited experimental structural information. Using coarse initial structural models, the predictions using the MD/ML workflow achieved strong alignment with experimental trends, particularly in the top-affinity tier for four legume LysM-RLKs (LYR3) binding to LCOs and a chitooligosaccharide. Furthermore, the MD-based conformation selection protocol provided critical structural insights into substrate specificity and binding mechanisms. This study demonstrates a powerful method to screen for challenging cognate ligand-receptors and advance our understanding of the molecular basis of microbial colonization in plants.

Lipo-chitooligosaccharides↗
DOE OSTI2026

From molecular to macroscopic: predicting liquid–liquid phase equilibria and small-angle scattering of mixtures of organic liquids from atomistic simulation using Kirkwood–Buff theory

Macroscopic phase equilibria between solutions define the functionality of many biological and industrial processes, yet they are challenging to predict due to the inherent complexity of liquids containing large molecules. This work introduces an approach for the purely predictive calculation of such phase equilibria in temperature-composition space from molecular dynamics (MD) simulations at one temperature in the single-phase region. We use an approach developed previously to obtain the entropic and enthalpic contributions to the free energy of mixing from the atomic-scale information given by MD simulations via Kirkwood–Buff theory. This allows us to accurately estimate the free energy of mixing as a function of temperature, and thus obtain liquid–liquid phase equilibria, including liquid–liquid critical points, associated binodal and spinodal lines, and composition fluctuations across a region of temperature and composition. Results for binary malonamide–alkane systems are validated by comparison to a direct experimental probe of the fluctuations: the small angle X-ray scattering intensity near zero wavenumber. The MDKB → Phase method demonstrated here provides a significant improvement in predicting liquid–liquid equilibria and free energy as a function of temperature for our systems of interest compared to conventional thermodynamic models. The accurate performance of this purely predictive approach lies in its preservation of atomistic details when determining thermodynamic properties. Furthermore, its inherent extensibility to multi-component systems will likely make the MDKB → Phase approach a valuable general tool for connecting molecular interactions to macroscopic phase equilibria and for the computational screening of materials for targeted thermodynamic behavior.

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

Structural insights into transcriptional regulation by the helicase RECQL5

Abstract Transcription poses a major challenge for genome stability. The RECQL5 helicase helps safeguard genome integrity and is the only member of the human RecQ helicase family that directly binds to RNA polymerase II (Pol II) and affects its progression. While RECQL5 mitigates transcription stress in cells, the molecular mechanism underlying this phenomenon is unclear. Here, we use cryo-electron microscopy to determine the structures of stalled human Pol II elongation complexes (ECs) bound to RECQL5. Our structures reveal the molecular interactions stabilizing RECQL5 binding to the Pol II EC and highlight its role as a transcriptional roadblock. Additionally, we find that, in its nucleotide-free state, RECQL5 twists the downstream DNA in the EC and, upon nucleotide binding, undergoes a conformational change that allosterically induces Pol II toward a post-translocation state. We propose that this mechanism may help restart Pol II elongation and, therefore, contribute to reducing transcription stress.

Biochemistry & Molecular Biology↗
DOE OSTI2025

Bulky Cation-Modified Interfaces for Thermally Stable Lead Halide Perovskite Solar Cells

Charged conjugated organic molecules offer promising prospects for reducing nonradiative recombination at interfaces in perovskite solar cells, while protecting the active layer from moisture. However, several studies have shown that the heat induced diffusion of these cations leads to irreversible solar cell degradation. Passivation molecules for perovskite can reconstruct the film surface into lower-dimensional phases when exposed to thermal stress, impeding charge extraction and affecting the photoconversion efficiency (PCE) of devices. In this work, we study how molecular interactions between passivation molecules and 3D CsFAPbI 3 perovskite impact stability and charge extraction at the perovskite/hole transport layer interfaces. Two model π- conjugated molecules are studied: 2-([2,2′-bithiophen]-5-yl)ethan-1-aminium iodide (2TI) and 2-(3‴,4′-dimethyl-[2,2′:5′,2″:5″,2‴- quaterthiophen]-5-yl)ethan-1-ammonium iodide (4TmI). We demonstrate that the speed of surface layer reconstruction under thermal stress can be controlled by the cation size and correlate these structural changes with the solar cell performance and stability. Devices treated with 2TI and 4TmI achieve PCEs over 21% and maintain their performance under thermal stress. Our findings demonstrate that thermal stability in PSCs can be achieved via the design engineering of passivation agents, offering a blueprint for developing next-generation passivation molecules.

36 MATERIALS SCIENCE↗