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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

From Ensemble Climate to Ensemble Impacts

Many climate-risk tools rely on ensemble mean projections or endpoint climate snapshots to characterize future hazards. Although convenient for communication, these representations remove the statistical, temporal, and physical information that real infrastructure systems respond to. Infrastructure degradation and failure arise from extremes, sequences, cumulative stress, compound hazards, and nonlinear fragility relationships, none of which survive ensemble averaging or temporal compression. Power-system failure statistics and cascading failure models further show that infrastructure risk is dominated by tail events and path-dependent dynamics rather than by mean conditions. This paper demonstrates why ensemble mean or endpoint-only climate representations are mathematically and physically inconsistent with engineering-grade risk analysis. We outline a model-resolved, time-series-based workflow that preserves extremes, variability, and sequencing by propagating each climate-model realization independently through hazard formation, exposure, fragility, and cascading failure mechanisms. Taking the ensemble of impacts—rather than the ensemble of climate—provides a defensible, physically coherent foundation for infrastructure resilience planning, regulatory compliance, and long-term investment decisions.

54 - ENVIRONMENTAL SCIENCES/GLOBAL CLIMATE CHANGE ↗
DOE OSTI2020

ReaxFF-based molecular dynamics study of bio-derived polycyclic alkanes as potential alternative jet fuels

This work investigates the initial stages of the pyrolysis of HtH-1 (C 18 H 32 ; 2,2,7,7,8a,8b-hexamethyl-dodecahydrobiphenylene) and HtH-2 (C 18 H 34 ; 1,1',3,3,3',3'-hexamethyl-1,1'-bi(cyclohexane)), which are bio-derived polycyclic alkanes and potential jet fuels, using ReaxFF force field based molecular dynamics (MD) simulations. Global Arrhenius parameters, such as activation energies and pre-exponential factors, are calculated and used to analyze the overall decomposition kinetics of the fuels. HtH-1 decomposes faster than HtH-2 at the same temperature and density conditions, and they have a faster decomposition rate compared to some existing jet-fuels, such as JP-10. A systematic reaction analysis framework developed in this work is applied to determine a temperature-dependent decomposition mechanism. At lower temperature, the central C-C bond connecting the two cyclohexane rings is dominantly broken in both HtH-1 and HtH-2. However, C-CH 3 bond breaking becomes dominant with increasing temperature due to the large increase in entropy during this reaction. Major products from HtH-1 are C 5 H 8 and C 4 H 8 , and those from HtH-2 are C 4 H 8 and C 2 H 4 . The major products predict that HtH-1 has a higher sooting tendency than HtH-2, which is consistent with measurements. The impact of HtH-2 on the pyrolysis of HtH-1 is also investigated in their binary mixtures. HtH-1 and HtH-2 decompose by unimolecular reactions, and they rarely interact with each other during the pyrolysis of the mixtures. Furthermore, this work demonstrates that ReaxFF can be used to investigate pyrolysis and combustion chemistry of existing or future fuels and to contribute to the development of their chemical kinetic models without any a priori input and chemical intuition.

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

Operando synchrotron X-ray analysis of melt pool dynamics in an Al-Sn immiscible alloy

The melt flow in an Al-50vol.% Sn immiscible alloy, produced by single-track laser melting of Al and Sn elemental powders, was studied in real time. High-speed synchrotron X-ray imaging was used to track Al and Sn liquids’ movements, and also to examine elemental distributions in the laser tracks, complimented by electron microscopy after solidification. Key aspects, including melt pool geometry, keyhole instability, and flow dynamics (flow pattern and velocity), were examined using digital image analysis. Relatively deeper melt pools formed at 400 W and 300 mm/s exhibited greater stability, with smooth surfaces, consistent outward flow, and minor vortices near the keyhole. In contrast, shallower pools produced at higher scanning speeds (>500 mm/s) demonstrated greater instability with increased surface waviness, and stronger velocity fluctuations, leading to numerous micro-vortices and increased Al-Sn heterogeneity. Velocity scale estimations, supported by experimental observations, examined the roles of vapour pressure, Marangoni effect, buoyancy, inertial, and surface tension forces in the flow. The results revealed that vapour pressure and mechanical waves dominated at high scanning speeds (shallow pools), while Marangoni forces were equally significant in deep pools at lower speeds (300 mm/s). Buoyancy was found to have minimal impact in both cases. Furthermore, the interaction between inertial and surface tension forces played a critical role in determining the degree of waviness of the pools’ surfaces. These findings offer valuable insights into melt pool dynamics during laser processing of immiscible alloys and other metallic systems using elemental powders, and provide guidance for developing high-fidelity computational fluid dynamics models.

immiscible alloys↗
DOE OSTI2020

An ideal MHD δW stability analysis that bypasses the Newcomb equation

In the following work, we demonstrate the efficacy of a Riccati δW ideal MHD stability analysis that bypasses the numerically intractable integration of the Newcomb equation. By transforming the linear Newcomb equation into a quadratic Riccati equation, an accurate and equivalent δW analysis is performed that is shown to enjoy some numerical advantages. Additionally, we demonstrate that the Riccati approach is better conditioned than its Newcomb counterpart at the magnetic axis, and we apply dynamical systems insights to examine its behavior at singular points. We further discuss the constraints involved in solving for the extremal admissible perturbations of a δW analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Effect of surface defects on damage and failure of dynamically driven cylindrical shells

Here, in this work, expanding cylinder experiments are performed using a gas gun on the aluminum 6061 alloy to understand the dynamic deformation and failure behavior of this material in the presence of surface defects in the form of scratches. The experiments are then modeled with the modified Tepla (for tensile plasticity) model, which is equipped with the damage yield function of Gurson [“Continuum theory of ductile rupture by void nucleation and growth: Part I—Yield criteria and flow rules for porous ductile media,” (1977)] and Tvergaard and Needleman [Acta Metall. 32(1), 157–169 (1984)], over-stress viscosity [F. Addessio and J. Johnson, J. Appl. Phys. 74(3), 1640–1648 (1993)], and the underlying viscoplastic model of Preston et al. [J. Appl. Phys. 93(1), 211–220 (2003)] (Preston–Tonks–Wallace model) for the dense material. The Tepla model parameters were calibrated using the Bayesian approach against experimentally measured free-surface velocity data obtained from plate impact experiments on the aluminum 6061 alloy. The evolution of radial expansion and shapes of the deformed cylinder from the simulations on a pristine cylinder wall and a cylinder wall with a longitudinal surface defect shows excellent agreement with the corresponding experimental results. Finally, the role of surface defect size and cylinder wall geometry on the dynamic strength of the cylinder wall was also investigated through a series of simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Integrative investigation of dust emissions by dust storms and dust devils in North Africa

Dust aerosols in North Africa account for >50% of the global total; however dust emission areas are still unclear. Based on the analysis of dust storms simulated with the numerical Weather Research and Forecast (WRF) model, satellite aerosol index (AI), and the dust data observed at 300 meteorological stations over 20 years, the spatio-temporal distribution characteristics of dust storm, dust devil and AI are compared and analyzed. From this study, the results show that: 1) There are two dust emission mechanisms: the dynamically-dominated dust storm and thermally-dominated dust devil; 2) Dust storms occur most frequently in Spring and are concentrated in the areas of Grand Erg Occidental Desert to the Erg Chech-Adrar Desert, the northern part of Grand Erg Oriental, the Atouila Desert to the Ouarane Desert, the Mediterranean coast, the eastern side of Nubian Desert and Bodélé Depression; 3) Dust devils occur most frequently from April to August and are mainly concentrated in the central part of North Africa, especially in the southwest of Hoggar Mountains to the west of Air Mountains, the border area of Egypt - Sudan - Libya and the vicinity of Tibesti Plateau; 4) The spatio-temporal distribution of AI is correlated more with the dust devils emission whereas the annual average contributions by dust storms and dust devils are 61.3% and 38.7%, respectively. This study discovers a new area of dust emissions by dust devils, and provides a better explanation for the spatio-temporal distribution of AI in North Africa.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bipolar Membrane Capacitive Deionization for the Selective Capture of Lithium Ions from Brines and Conversion to Lithium Hydroxide

Meeting the increasing demand for lithium in vehicle electrification and renewable energy storage requires innovations in lithium-ion (Li + ) separations. Traditional solar evaporation methods for lithium recovery are slow and consume tremendous volumes of water and secondary chemicals (acids and bases). This study introduces a bipolar membrane capacitive deionization (BPM-CDI) unit for direct lithium extraction and LiOH production without the external addition of acids and bases. Utilizing de-lithiated lithium-iron-phosphate (LFP) coated carbon cloth electrodes, the BPM-CDI unit demonstrates selective Li + capture over competing ions. Molecular dynamics simulations and H-cell experiments elucidate pH inversion mechanisms during Li + release, yielding LiOH. The BPM-CDI platform efficiently removes Li + from synthetic brines featuring 8x higher Mg 2+ concentrations (200 ppm Mg 2+ ) and 26x higher Na + concentrations (682 ppm Na + ), achieving a LiOH concentration of 124 ppm (36 ppm Li + ) after 8 cycles of recirculation. Post-mortem analysis confirms electrode integrity and stability. BPM-CDI integrated with selective electrodes is a promising electrochemical separation-reactor platform for lithium recovery while producing LiOH.

Kulkarni, Tanmay↗
DOE OSTI2024

Sierra/SD – Verification Test Manual – 5.22

Verification and validation (V&V) of scientific computing programs are important at Sandia National Labs due to the expanding role of computational simulation in managing the United States nuclear stockpile. The complexities of structural response calculations used to analyze physical problems, the varieties of codes applied to the calculations, and the importance of accurate predictions when assessing field conditions demand confidence in the consistency and accuracy of computer codes. Confidence in the accuracy of the predictions arising from computer simulations must ultimately be gained through verification and validation. The Sierra salinas structural dynamics analysis code, Sierra/SD, is used at the DOE Laboratories, and in several DOD projects. The roles of Sierra/SD in the qualification of weapon systems and components for normal and hostile environments throughout the Stockpile-to-Target Sequence include to, • Redesign weapon components. • Certify weapon components and systems for target environments such as hypersonic vehicles. • Certify that components will survive the thermal mechanical shock loads associated with hostile environments. • Evaluate current stockpile issues, including issues associated with uncertainty quantification. • Address many other problems that are encountered in stockpile management. The Sierra/SD verification plan is described, and an evolving set of key verification tests are described in detail. The verification tests ensure the correctness of the mathematics and numerical algorithms associated with functionality describing engineering phenomena. Development is in accordance with a set of tailored Software Quality Engineering (SQE) practices. SQE practices guide the overall verification and validation effort.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity analysis and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE < 0.49 for FBC and <0.36 for BBC and RMSE <0.52 FBC and <0.39 for BBC, while R2 values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R 2 =0.70, P<0.001) and BBC (R 2 =0.26, P<0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows the most critical parameters are turnover rate, carbon-to-nitrogen ratio of fungi and bacteria, and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to the global C cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stabilizing lattice oxygen redox in layered sodium transition metal oxide through spin singlet state

Abstract Reversible lattice oxygen redox reactions offer the potential to enhance energy density and lower battery cathode costs. However, their widespread adoption faces obstacles like substantial voltage hysteresis and poor stability. The current research addresses these challenges by achieving a non-hysteresis, long-term stable oxygen redox reaction in the P3-type Na 2/3 Cu 1/3 Mn 2/3 O 2 . Here we show this is accomplished by forming spin singlet states during charge and discharge. Detailed analysis, including in-situ X-ray diffraction, shows highly reversible structural changes during cycling. In addition, local CuO 6 Jahn-Teller distortions persist throughout, with dynamic Cu-O bond length variations. In-situ hard X-ray absorption and ex-situ soft X-ray absorption study, along with density function theory calculations, reveal two distinct charge compensation mechanisms at approximately 3.66 V and 3.99 V plateaus. Notably, we observe a Zhang-Rice-like singlet state during 3.99 V charging, offering an alternative charge compensation mechanism to stabilize the active oxygen redox reaction.

25 ENERGY STORAGE↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Correlation between Sensor Performance, Autonomy Performance and Fuel-Efficiency in Semi-Truck Platoons

Semi-trucks, specifically class-8 trucks, have recently become a platform of interest for autonomy systems. Platooning involves multiple trucks following each n close proximity, with only the lead truck being manually driven and the rest being controlled autonomously. This approach to semi-truck autonomy is easily integrated on existing platforms, reduces delivery times, and reduces green- house gas emissions via fuel economy benefits. Level 1 SAE fuel studies were performed on class-8 trucks operating with the Auburn Cooperative Adaptive Cruise Control (CACC) system, and fuel savings up to 10-12% were seen. Enabling platooning autonomy required the use of radar, global positioning systems (GPS), and wireless vehicle-to-vehicle (V2V) communication. Poor measurements and state estimates can lead to incorrect or missing positioning data, which can lead to unnecessary dynamics and finally wasted fuel. This is especially an issue if deceleration is applied in response to a bad measurement. In this study, a faulty radar was shown to cause a greater than 5% increase in fuel consumption. The mechanism of this fuel consumption increase is investigated and applied to other types of sensor failures to indicate their potential effects on fuel economy. This analysis indicates that poor GPS signals over short time can be largely filtered out, with no real gain or loss of fuel economy. V2V communications were intentionally limited by causing interference, which resulted in dropped communication packets over a small physical area, but not an appreciable impact on fuel economy.

vehicle platooning, sensor performance, semi-auton↗
DOE OSTI2020

Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging

The universal tendency in scanning probe microscopy (SPM) over the last two decades is to transition from simple 2D imaging to complex detection and spectroscopic imaging modes. The emergence of complex SPM engines brings forth the challenge of reliable data interpretation, i.e., conversion from detected signals to descriptors specific to tip–surface interactions and subsequently to material’s properties. In this work, we implemented a Bayesian inference approach for the analysis of the image formation mechanisms in band excitation SPM. Compared to the point estimates in classical functional fit approaches, Bayesian inference allows for the incorporation of extant knowledge of materials and probe behavior in the form of corresponding prior distribution and return the information on the material functionality in the form of readily interpretable posterior distributions. We explore the nonlinear mechanical behaviors spatially in a classical ferroelectric material, PbTiO 3 . We observe the non-trivial evolution of the Duffing stiffness term and the nonlinearity of the sample surface, determine spatial clustering of the nonlinear response, and perform a Landau analysis on predicting the nonlinear coefficient, which indicates that ferroelectric behavior can be a cause of the observed results. These observations suggest that the spectrum of anomalous behaviors at the ferroelectric domain walls may be broader than previously believed and can extend to non-conventional mechanical properties in addition to static and microwave conductance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The role of deviatoric stress and dislocations on the α to ω phase transformation in Ti

Under extreme conditions, α-Ti becomes unstable and transforms either into β-Ti at high temperature or into ω-Ti at high pressure. In what concerns the α to ω phase transformation (PT), there has been a wide range of experimentally reported transition pressures from approximately 2 to 15 GPa at room temperature. Deviatoric stresses and internal defects are often assumed to be the root cause of this variation. Here, in this study, these postulates are revisited using both continuum mechanics and molecular dynamics (MD) simulations. First, a simple continuum model, assuming linear elasticity and isotropic plasticity, is developed to describe the effects of applied stress and dislocations on the stability of an ω nucleus in an infinite α domain. Second, a new MD simulation method is developed to generate an ω nucleus in the α domain utilizing the displacement field identified from the topological analysis. Results from MD simulations show that despite the fact that phase diagrams typically delineate the limits between two phases in terms of only P and T, deviatoric stress promotes the α to ω phase transformation by reducing the critical radius above which an ω nucleus is stable. Furthermore, the required deviatoric stress to nucleate and stabilize a nanoscale ω nucleus is likely emanating from the internal stress of defects such as dislocations. The MD-informed micromechanics models are used to identify favorable configurations where dislocations help favor the α to ω transformation. These configurations show that the interaction with a basal or prismatic dislocation reduces the critical radius of a ω nucleus by about 10 or 16 %, respectively. In addition, prismatic edge dislocations are found to promote the growth of ω nucleus when interacting with the ($\bar{1}$$\bar{1}$20) α //(0001) ω interface. Importantly, a simple model of the arrival of dislocation at an ω nucleus suggests that PT does not necessarily require a pile-up to be present but could alternatively be mediated by a constant rapid flow of dislocations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A heat flux sensor leveraging the transverse Seebeck effect in elemental antimony

Certain configurations of anisotropic single crystal materials can generate a thermoelectric voltage orthogonal to an induced temperature gradient. This phenomenon is known as the Transverse Seebeck Effect (TSE) and can be leveraged to fabricate simple and robust heat flux sensors. Only a small number of materials have been considered as TSE-based transducers and, among these, few have been developed into sensors with ruggedization against chemical and mechanical degradation. Here, we report on the fabrication and characterization of a rugged TSE-based heat flux sensor using prismatic antimony single crystals. The heat flux sensor was tested under static and dynamic heating scenarios. The sensor has a linear responsivity of 16.8 µV/(W/cm2) to heat fluxes spanning more than two orders of magnitude and a time constant of 4.4 s. The sensor’s response to localized heating, probed with a laser scanning technique, validated that the transduction mechanism is primarily the TSE by ruling out a sizable contribution from the conventional Seebeck effect. Finite element analysis corroborated that components used in the sensor package are the primary determinants of the time constant and the decrement of the responsivity from its theoretical maximum. Design principles that may be applied to elicit a faster transient response or higher responsivity are proposed. Furthermore, the results establish single crystal antimony as a promising transducer material for heat flux measurement systems and demonstrate potential effects of ruggedization on sensor performance.

36 MATERIALS SCIENCE↗
DOE OSTI2022

All-Atom Simulations Uncover Structural and Dynamical Properties of STING Proteins in the Membrane System

Recent studies have shown that the stimulator of interferon gene (STING) protein plays a central role in the immune system by facilitating the production of type I interferons in cells. The STING signaling pathway is also a prominent activator of cancer-killing T cells that initiate a powerful adaptive immune response. Since biomolecular signaling pathways are complicated and not easily identified through traditional experiments, molecular dynamics (MD) has often been used to study structural and dynamical responses of biological pathways. In this work, we carried out MD simulations for full-length chicken and human STING (chSTING and hSTING) proteins. Specifically, we investigated ligand-bound closed (holo) and ligand-unbound open (apo) forms of STING in the membrane system by comparing their conformational and dynamical differences. Our research provides clues for understanding the mechanism of the STING signaling pathway by uncovering detailed insights for the examined systems: the residues from each chain in the binding pocket are strongly correlated to one another in the open STING structure compared with those in the closed STING structure. Ligand-bound closed STING displays ~174° rotation of the ligand-binding domain (LBD) relative to the open STING structure. The dynamical analysis of residue Cys148 located in the linker region of hSTING does not support the earlier hypothesis that Cys148 can form disulfide bonds between adjacent STING dimers. We also demonstrate that using the full-length proteins is critical, since the MD simulations of the LBD portion alone cannot properly describe the global conformational properties of STING.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Molecular Dynamics Investigation of Nanoscale Hydrophobicity of Polymer Surfaces: What Makes Water Wet?

The wettability of a polymer surface–related to its hydrophobicity or tendency to repel water–can be crucial for determining its utility, such as for a coating or a purification membrane. While wettability is commonly associated with the macroscopic measurement of a contact angle between surface, water, and air, the molecular physics that underlie these macroscopic observations are not fully known, and anticipating relative behavior of different polymers is challenging. To address this gap in molecular-level understanding, we use molecular dynamics simulations to investigate and contrast interactions of water with six chemically distinct polymers: polytetrafluoroethylene, polyethylene, polyvinyl chloride, poly(methyl methacrylate), Nylon 66, and polyvinyl alcohol. We show that several prospective quantitative metrics for hydrophobicity agree well with experimental contact angles. Moreover, the behavior of water in proximity to these polymer surfaces can be distinguished with analysis of interfacial water dynamics, extent of hydrogen bonding, and molecular orientation–even when macroscopic measures of hydrophobicity are similar. The predominant factor dictating wettability is found to be the extent of hydrogen bonding between polymer and water, but the precise manifestation of hydrogen bonding and its impact on surface-water structure varies. In the absence of hydrogen bonding, other molecular interactions and polymer mechanics control hydrophobic ordering. Furthermore, these results provide new insights into how polymer chemistry specifically impacts water-polymer interactions and translates to surface hydrophobicity. Such factors may facilitate the design or processing of polymer surfaces to achieve targeted wetting behavior, and presented analyses can be useful in studying the interfacial physics of other systems.

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

Structural determinants for pH-dependent activation of a plant metacaspase

Arabidopsis thaliana metacaspase 9 (AtMC9) plays roles in clearing dead cells, forming xylem vessels, and regulating immunity and programmed cell death in plants. The protease's activation is controlled by pH levels, but the exact structural mechanism behind this has not been elucidated. In this work, high-resolution crystal structures for AtMC9 at active (pH 5.5 and pH 4.2) and inactive (pH 7.5) conditions are reported. The three structures are similar except for local conformations where their hydrogen bonding interactions with solvents are mediated through the protonation of specific titratable amino acid residues' side chains. By combining structural analysis, molecular dynamics simulations under constant pHs, and biochemical assays coupled with site-directed mutagenesis, we show that the regulation of AtMC9 activation involves multiple titratable glutamate and histidine residues across the three domains of p20, linker, and p10. Specifically, deprotonated Glu112, His193, and His208 can suppress AtMC9 proteolytic activity, while protonation of Glu255 and His307 at acidic pH may promote it. This study provides valuable insights into the pH-dependent activation of AtMC9 and could potentially lead to improving crops with enhanced immunity and controlled cell death, ultimately increasing agricultural productivity.

59 BASIC BIOLOGICAL SCIENCES↗