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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Are Deep Energy Retrofits in Commercial Buildings Including Window Upgrades?

U.S. Commercial buildings account for about 20% of total U.S. energy consumption. Because the thermal performance of windows significantly affects building energy efficiency and HVAC system performance, best practice guidance often includes window and envelope improvements in conjunction with HVAC upgrades to optimize energy use and improve occupant comfort. It is an open question, however, regarding how often these best practices are implemented in the field. This paper aims to address that gap by conducting a literature review and a series of interviews with commercial building auditing and management professionals to explore the factors that drive window retrofits in commercial buildings. The paper explores a range of case studies from deep energy retrofits across the globe, comparing projects with and without window retrofits. The primary goals of this review are to: (1) provide data from real-world case studies illustrating the role of windows in deep energy renovations and HVAC upgrades, (2) conduct retrofit cost analyses for windows and high-performance HVAC systems and (3) offer insights into how window upgrade decisions are made and when they are implemented as part of deep energy retrofits. Most of the retrofit studies focused exclusively on high performance HVAC upgrades without considering how window upgrades might further enhance the overall energy efficiency of commercial buildings. Interviews with building industry experts shed light on the key factors influencing deep energy retrofit decisions and what factors tip the scales in favor of including window measures with more comprehensive retrofit projects.

Cort, Katherine↗
DOE OSTI2026

Peptoid-Based Nanosheets Exhibiting Broad Antiviral Activity Against Enveloped RNA Viruses

Enveloped RNA viruses, such as Influenza A (H1N1) and Sindbis virus, pose persistent global health threats due to their high mutation rates, efficient transmission, and frequent drug resistance. By mimicking host cell membrane receptors, multivalent virus inhibitors can block viral attachment, making them promising broad-spectrum antiviral agents. However, most of existing antivirals are often limited by strain specificity, short-lived efficacy, and toxicity. Here, we introduce a broad-spectrum antiviral platform based on highly tunable and biocompatible two-dimensional nanomembranes (2DNMs) self-assembled from amphiphilic peptoids, operating via a non-genomic, mutation-insensitive mechanism. By varying peptoid sequence, we design and synthesize over twenty different 2DNMs with various surface charge and high density of viral-attachment ligands (VALs). The self-assembled architecture of these stable 2DNMs provides cooperative noncovalent multivalent binding to virus particles that result in effective inhibition of viral infection. Screening of variants identified three leads that potently suppressed Influenza A (H1N1) and Sindbis virus infection across median tissue culture infectious dose (TCID50), plaque, RT–qPCR, and immunofluorescence assays, while maintaining >90% cell viability. These nanosheets significantly reduced infectious titers, viral RNA replication, and intracellular viral protein expression, indicating inhibition at early stages of viral entry and propagation. The sequence programmability, chemical robustness, and mutation-insensitive antiviral activity distinguish 2DNMs from traditional antivirals and positions them as a versatile materials platform for antiviral coatings, protective barriers, and prophylactic biomedical applications.

Influenza A virus↗
DOE OSTI2025

Investigating the Combustion Performance of Dual Fuel Combustion with Diesel and Port Injected Hydrogen in a Large Bore Locomotive Engine

The heavy-duty transportation sector has primarily relied on conventional diesel combustion engines given their reliability and high thermal efficiency relative to spark ignition engines, but increased focus on reducing greenhouse gas emissions has led to investigation into alternative fuels. Gaseous hydrogen fuel has garnered a great deal of recent interest in the engine community given it has zero carbon, but hydrogen is not available at the scale and cost that petroleum fuels are currently available, and this is a barrier to adoption for industries that are looking to decarbonize their operations. Because of the fuel flexibility provided, dual fuel technology offers a pathway for some industries to adopt hydrogen as a fuel source while maintaining sufficient flexibility in times and locations where the new fuel is not yet available. This computational study investigates dual fuel combustion in a large bore locomotive engine architecture using direct injected diesel and port injected gaseous hydrogen fuel. With an optimal port fuel injection configuration from previous work, simulations of varying substitution ratio, compression ratio, manifold air temperature, diesel injection timing, and diesel injection pressure were performed to understand their effect on combustion performance. Results indicated that both increased substitution ratio and higher intake air temperature accelerates hydrogen flame propagation and can result in high peak cylinder pressures. Additionally, diesel injection timing and injection pressure were demonstrated as effective methods for controlling dual fuel combustion heat release rates.

ODonnell, Patrick Christopher↗
NASA NTRS2009

General Purpose Data-Driven Monitoring for Space Operations

As modern space propulsion and exploration systems improve in capability and efficiency, their designs are becoming increasingly sophisticated and complex. Determining the health state of these systems, using traditional parameter limit checking, model-based, or rule-based methods, is becoming more difficult as the number of sensors and component interactions grow. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. System health can be monitored by comparing real-time operating data with these nominal characterizations, providing detection of anomalous data signatures indicative of system faults or failures. Data-driven techniques have a number of advantages over other methods for monitoring complex space vehicles. Unlike model-based systems, the developer does not need to understand or encode the internal operation of the system. The knowledge required to monitor the system is automatically derived from archived data from system operation. Unlike rule-based systems, data-driven systems do not require system analysts to define nominal relationships among sensors. Analysts can and often do determine these relationships for a system with few sensors; it is more difficult to analytically determine the nominal relationship among a large number of sensors. Data-driven techniques are not limited to low-dimensional spaces and work as effectively with dozens of parameters as they do with a few. Knowledge bases formed by data-driven techniques are also easy to update. As the operating envelope of the monitored system is expanded, data-driven techniques can be quickly retrained to incorporate the new behavior into the knowledge base. The expertise and time-consuming process of updating a model or rule base to maintain consistency with the new operation is not required. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or analysis of archived events. System data is compared with the nominal IMS model to produce a measure of how well current system behavior matches the normal behavior defined by the training data. Significant deviations from the nominal system model can provide alerts to system malfunctions or precursors of significant failures. The scope of IMS based data-driven monitoring applications continues to expand with current development activities. Successful IMS deployment in the International Space Station (ISS) flight control room to monitor ISS attitude control systems has led to applications in other ISS flight control disciplines, such as thermal control. It has also generated interest in data-driven monitoring capability for Constellation, NASA's program to replace the Space Shuttle with new launch vehicles and spacecraft capable of returning astronauts to the moon, and then on to Mars. Several projects are currently underway to evaluate and mature the IMS technology and complementary tools for use in the Constellation program. These include an experiment on board the Air Force TacSat-3 satellite, and ground systems monitoring for NASA's Ares I-X and Ares I launch vehicles. The TacSat-3 Vehicle System Management (TVSM) project is a software experiment to integrate fault and anomaly detection algorithms and diagnosis tools with executive and adaptive planning functions contained in the flight software on-board the Air Force Research Laboratory TacSat-3 satellite. The TVSM software package will be uploaded after launch to monitor spacecraft subsystems such as power and guidance, navigation, and control (GN&C). It will analyze data in real-time to demonstrate detection of faults and unusual conditions, diagnose problems, and react to threats to spacecraft health and mission goals. The experiment will demonstrate the feasibility and effectiveness of integrated system health management (ISHM) technologies with both ground and on-board experiments. Initially, the TVSM software will run open loop, providing system health information and recommendations to ground operators, without automatically performing fault-mitigating corrective actions. After the end of the satellite's mission, closed loop tests combining TVSM monitoring and diagnosis with reactive capabilities by the flight software will be performed. In addition to monitoring for long periods of actual operation, the experiment will include fault injection into TacSat-3 data as well as commanded operations to test and evaluate automatic ISHM monitoring and recovery under controlled conditions.

Satellites↗
NASA NTRS1989

Up-and-Coming IMCs

While the good oxidation and environmental resistance, high melting points, and comparatively low densities of such ordered intermetallics as Ti 3 Al, NiAl, FeAl, and NbAl 3 render them good candidates for advanced aerospace structures, their poor toughness at low temperatures and low strength at elevated temperatures have prompted the development of fiber-reinforced intermetallic-matrix composites (IMCs) with more balanced characteristics. Fabrication methods for continuous-fiber IMCs under development include the P/M 'powder cloth' method, the foil/fiber method, and thermal spraying. The ultimate success of IMCs depends on fibers truly compatible with the matrix materials.

Randy Bowman↗
DOE OSTI2026

Elucidating the impact of stress states on grain boundary passivation in Ni-5Cr using the Rhines pack method

The oxidation behavior of a Ni–5Cr (at.%) alloy was evaluated at 420 ° C using the Rhines pack method and simultaneous tensile and compressive stress states via a miniature four-point bending fixture. At this moderate temperature, grain boundaries dominate mass transport and the resulting oxidation response. Oxidation produced approximately 1μ⁢m-wide protective Cr 2 O 3 films capping some grain boundaries and penetrative, intergranular Cr-rich oxides at other grain boundaries. Externally applied tensile and compressive stress during oxidation increased the prevalence of Cr 2 O 3 cap formation compared to no applied stress, with tensile stress resulting in more Cr 2 O 3 caps than compressive stress. The observed oxide cap morphology was similar across all test conditions. Regions under compressive stress showed an order of magnitude greater Cr depletion depth along the grain boundary. Chromium nitrides (CrN), likely from N contamination of the Rhines pack cell, were observed both at the oxide–metal interface and intergranularly within the alloy. Collectively these results demonstrate that applied stress promotes localized protective oxide cap formation over grain boundaries, with compressive stress additionally promoting deeper Cr depletion. Furthermore the experimental approach helped separate out the effects of stress on local oxide formation and grain boundary passivation.

4 point bend↗
NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗
DOE OSTI2025

A General Solution Route to Nanoporous Metal Oxide Films

Metal oxide semiconductors are of interest as efficient, stable, and low-cost photoanode materials for photoelectrochemical water splitting, but their characteristically poor charge transport properties remain a fundamental challenge to practical use. Nanoporous metal oxide films that feature open bicontinuous networks of nanocrystals and nanopores can overcome such inefficient charge transport to enable high-performance photoanodes. Here, this paper describes a general method to make high-quality nanoporous films of metal oxides by spin coating and calcining molecular inks that contain a porosity-generating block copolymer. Phase-pure nanoporous films of BiFeO 3 , FeWO 4 , WO 3 , Fe 2 O 3 , and TiO 2 serve to demonstrate the versatility of the approach. It is demonstrated that the crystallite size, film porosity, and film thickness can be independently tuned by adjusting the ink composition and film processing conditions. The method is extended to fabricate core–shell nanoporous films consisting of a nanoporous film coated in a thin shell of a second metal oxide, using WO 3 –BiVO 4 and BiFeO 3 –BiVO 4 as examples. Given its simplicity and flexibility, this solution-phase route should prove useful for making nanoporous films of many different materials for a variety of applications, including energy conversion and storage, catalysis, and chemical sensing.

coating materials↗
DOE OSTI2025

Research and Development on Advanced Electrochemical Energy Storage Devices Enabling a Spectrum of Electrified Vehicles

The USABC Advanced Battery development plan had the following three focus areas: 1. Existing technology validation, implementation, and cost reduction 2. Identification of the next viable technology with emphasis on the potential to meet USABC cost and energy density goals. 3. Support high-risk, high-reward battery technology R&D The primary aim of this project was focused on the barriers that most impede wider public adoption of electrification in vehicles-cost, energy density, low-temp performance, calendar life, and improvements in abuse tolerance. The specific objectives are as follows: Cost Reduction: drive to significantly reduce battery cost to be in-line with the $\$$100/kWh or less (by the end of calendar year 2020) DOE cost goals. Additionally, goals of $\$$75/KWh were set for 2023 aligned with fast charge and some offset of energy density. Energy Density Increase: focus on improving the cell-level specific energy and energy densities to >350 watt hours per kilogram (Wh/kg) and >750Wh/L. Low Temperature Performance Increase: strive toward developments that improve the discharge power and eliminate or dramatically reduce the life limiting lithium plating associated with regenerative braking at low temperatures, during the program. Calendar Life Increase: drive to achieve a 15-year calendar life. Abuse Tolerance Improvement: strive to develop improvements in Li-ion abuse tolerance and/or development of electrochemical energy storage technologies with inherently better response to abuse circumstances. Emerging Areas: initiate new programs that address emerging technologies that arise during the contract period.

25 ENERGY STORAGE↗
DOE OSTI2026

Measuring Climate and Water Risk across the Bulk Power System

As climate impacts increase and power systems transition to renewables, planners and operators need insights into climate risks to power generation and infrastructure to ensure reliable decision-making in the short and long-term. We present a standardized, consistent mechanism for utilities and system operators to evaluate the climate- and water-related risks of their current and future grid assets. Using a risk-based approach on the combined outcomes of high-fidelity climate drivers together with water and power system models, we examine the temperature and water availability impacts within the contiguous United States to power system assets at the water basin level in three different time periods and report resulting outcomes on lost capacity across different expansion scenarios and climate models. The results indicate that air temperature has the highest effect on derating. Changes in streamflow do not have a large impact on generation capacity at the national level. Electric sector buildout scenarios each have a unique regional risk profile, depending on the technology mix and total capacity, although risks from high temperatures are significant for both traditional and renewable energy generation. Stakeholders can use this approach to monitor effects of generation capacity losses and potential impacts as climate, generation mix, and infrastructure change.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Proteome-wide analysis of protein stability in Escherichia coli under acid stress

Knowledge of protein acid sensitivity remains sparse and is largely derived from low-throughput, enzyme-specific assays. We used a scalable framework to map acid stability across the Escherichia coli proteome to assess the acid stability of 1,675 unique proteins, estimating pH 50 values for over 90% of them. The parameter pH50 was defined as the pH value at which only 50% of the initial protein remains in solution following acid treatment. Proteome-wide pH 50 values ranged from 2.28 to 6.33 (median 5.11). Approximately 9% of detected proteins remained stable across all tested pH conditions. Our results align with published data and the assay of citrate synthase (GltA) performed here. Protein acid stability differed significantly by subcellular localization: periplasmic proteins were relatively more abundant in the acid-stable group, cytoplasmic proteins were abundant at pH 50 values 4.5–5.5, and inner membrane proteins at higher pH 50 between 5.5 and 6.0. Outer membrane proteins were too few to draw strong conclusions regarding enrichment within specific pH 50 groups. Notably, the periplasmic binding protein of the molybdate ABC transporter (ModA), was enriched after incubation at low pH. Estimated pH 50 values showed no correlation with protein isoelectric point and molecular weight. Together, this work provides the first proteome-wide map of protein acid stability and establishes a general framework for studying different chemical stressors.

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

Glancing Angle Deposition in Gas Sensing: Bridging Morphological Innovations and Sensor Performances

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO2, CO, H2S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies.

Chemistry↗
DOE OSTI2026

Intrinsically Conductive {pi}‑d Conjugated Layers with Co–N4 Active Sites for Efficient Nitrate Electrocatalysis and Zinc-Nitrate Batteries

Electrochemical synthesis of ammonia from nitrate has been extensively investigated as a potential alternative to the energy-intensive Haber-Bosch process. This approach not only operates under ambient conditions but also simultaneously removes nitrate contaminants while producing ammonia as a value-added product. However, the ongoing quest lies in designing an efficient electrocatalyst that achieves a high ammonia yield rate, high selectivity, and long-term stability. Herein, we report the outstanding performance of a Co–N4 coordinated π-d layered Co3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) in nitrate electrocatalysis. The unique combination of abundant Co–N4 active sites and superior electrical conductivity enables significant electrocatalytic activity, delivering a maximum ammonia yield rate of 56.8 mg cm–2 h–1 at −0.8 V vs RHE and a Faradaic efficiency of ∼91% at −0.4 V vs RHE. Mechanistic analysis reveals that alkaline conditions accelerate water dissociation to generate adsorbed hydrogen intermediates (H*), which are utilized by Co–N4 sites to drive the stepwise hydrogenation of nitrate to ammonia while suppressing competing hydrogen evolution reaction (HER) pathways. Furthermore, integration of this catalyst into a zinc-nitrate battery resulted in a maximum power density of 5.3 mW cm–2 and an open-circuit potential of ∼1.45 V. These results highlight the potential of π-d conjugated Co–N4 materials as an efficient catalyst for both environmental remediation and energy conversion.

Namvar, shahrirar↗
NASA NTRS1958

Turbojet Lift Engine Design for Vtol Transports

The pure hoverjet, utilizing separate turbojet engines for lift and cruise phases of flight, is an interesting high speed VTOL transport airplane configuration. The results of a brief analysis are presented with the intent to: (I) define the effects of some general powerplant installation and operating variables on VTOL transport performance; (2) indicate desirable turbojet lift engine design characteristics with respect to compressor pressure ratio, turbine inlet temperature, component efficiencies and thrust augmentation; and (3) examine the unique lift engine operating requirements for feasible ways of reducing engine specific weight. The figure of merit used to gauge airplane performance is airplane range.

M J Saari↗
NASA NTRS1992

Science questions for the Magellan continuing mission

Magellan has completed two mapping cycles around the planet Venus, returning high resolution synthetic aperture images and altimetry data of over 95 percent of the planet's surface. Venus is dominated by low lying volcanic plains with an impact crater population indicating an average surface age of about 500 million years. Highland regions either tend to be characterized by volcanic shield complexes and rifting or by complex ridged terrain. Successful as the primary mission of Magellan has been, significant scientific questions remain to be addressed with imaging and gravity data that will be collected over the next several years.

Saunders, R. S.↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
DOE OSTI2026

Power and particle exhaust in the ST-E1 fusion power plant

Power exhaust challenges and potential solutions for a 5 m major radius, low-aspect ratio burning tokamak have been explored. 1D edge plasma models have been used to screen for access to detachment using short and long outer divertor legs in double and single null configurations, using Ar as the primary impurity and assuming tungsten plasma-facing components (PFCs). These show that detachment access can be accessed for all but the most conservative assumptions on scrape-off layer (SOL) width and power, but that trade-offs will be required between magnet engineering and the size of the acceptable window of as-yet uncertain plasma parameters. SOLPS-ITER was used to further model selected plasma scenarios, confirming that Ar seeding can be used to achieve dissipative divertor scenarios with peak deposited heat fluxes below 15 MWm -2 . Initial scoping of first wall loads and positioning of limiters has been carried out, showing the feasibility of protecting the breeding blanket wall during steady state without impeding tritium breeding. Initial PFC technology selection is also presented, identifying this as a critical area where further work is needed to find an attractive solution for helium-cooled PFCs that can handle high heat fluxes without excessive power requirements. Key questions and trade-offs for concept development have been identified, including: how to achieve high radiation for reduction of SOL power without core performance degradation; whether power exhaust can be well-controlled in a double null plasma; mechanical design and materials challenges of high-heat flux PFCs; and control of material erosion, redeposition and tritium retention.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]↗