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At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Rapid Electron Transfer Self-Exchange in Conformationally Dynamic Copper Coordination Complexes

Here we report the electron transfer (ET) self-exchange rate constants (k 11 ) for a pair of Cu II/I complexes utilizing dpa R (dpa = dipicolylaniline, R = OMe, SMe) ligands assessed by NMR line-broadening experiments. These ligands afford copper complexes that are conformationally dynamic in one oxidation state. With R = OMe, the Cu I complex is dynamic, while with R= SMe, the Cu II complex is dynamic. Both complexes exhibit unexpectedly large k 11 of 2.48(6) x 10 5 and 2.21(9) × 10 6 M –1 s –1 for [CuCl(dpa OMe )] +/0 and [CuCl(dpa SMe )] +/0 , respectively. Among the fastest reported for molecular copper coordination complexes to date, that of [CuCl(dpa SMe )] +/0 exceeds all others by an order of magnitude and compares only to those observed in type 1 blue copper proteins. The dynamicity of these complexes establish pre-steady-state con-formational equilibria that minimize the inner sphere reorganization energies to 0.71 and 0.62 eV for R = OMe and SMe, respectively. In contrast to the emphasis on rigidity in the formulation of entatic states applied to blue copper proteins, the success of these two systems highlight the relevance of conformational dynamicity in mediating rapid ET.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring a multitude of capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for a particular mission is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) to defining gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities, gaps, and KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed. The paper will contain a summary of the approximately 60 gaps. Gaps are classified as to their type (architecture, knowledge, technology, developmental, or engineering) depending on the magnitude of the gap. The paper will provide brief overviews of a few major technology challenges and the technologies being considered, but will reference detailed papers for a more thorough treatment of the challenges and state of the art. Data analysis of the gaps is in work and results are not currently available for this abstract. It is anticipated the paper will include examples of select KPPs with descriptions as to why these are the relevant measures. Additionally some KPPs will be graphically presented over time to show progress to date and when performance targets need to be achieved to support exploration missions. Graphical summaries of how gaps closures with near term mission elements support follow-on mission elements will be provided.

Life Support↗
NASA NTRSDate not supplied

Utilizing Gaps and Key Performance Parameters to Inform NASA Environmental Control and Life Support and Human Health and Performance Capability Technology Decisions

Human spaceflight is a complex endeavor requiring multiple capabilities for transportation, crew health, scientific goals, and safe return to Earth. The difference between spaceflight proven capabilities and those needed for future exploration architectures is defined as a capability gap. Capability gaps are not technology specific. Each capability gap is approachable with a wide array of technologies that have unique benefits and challenges. Determining what a capability’s relevant and distinguishing key performance parameters (KPPs) are for a mission is critical. Mass, power, and volume are always constrained and important, but defining these in a way normalized by performance is challenging. Additionally, KPP definition for reliability, dormancy, and integration needs are very important and still evolving. This paper provides the approach of the Environmental Control and Life Support – Crew Health and Performance (ECLSS-CHP) System Capability Leadership Team (SCLT) has used to define gaps and KPPs in support of the NASA’s Capabilities Integration Team data call objectives. The nine ECLSS-CHP capability areas are decomposed to capabilities with ~76 gaps and supported with KPPs. Rather than defining very detailed gaps, ECLSS-CHP defines high-level gaps to be technology agnostic. Within a gap, detailed KPPs are defined to both compare technologies and measure progress within a technology over time. Ideally, KPPs are clearly defined, widely communicated both internally and externally, and provide a common nomenclature to describe the state of the art and the degree of improvement required for exploration missions. KPPs help define when the gap is closed, and the core mission objectives can be accomplished. Further technology improvements to enhance the capability, as measured by improved KPPs, must then be weighed against investments in open capability gaps that prevent NASA from achieving its exploration missions. It is uncommon that a technology maturation to improve all the relevant KPPs simultaneously but using KPPs is a critical technology investment decision making component. In addition to traditional technology selections, KPPs are informing how investments in ground testing prior to and in parallel with ISS technology demonstrations are required to improve reliability KPPs. The collection of all major technology activities within a capability area are captured on technology roadmaps to communicate how diverse program activities are coordinated to close gaps and infuse into exploration mission needs. A selection of ECLSS-CHP gaps and KPPs and their formulation, current state, and how they inform capability roadmap planning are discussed.

Life Support↗
DOE OSTI2020

Semiglobal diabatic potential energy matrix for the N–H photodissociation of methylamine

We constructed an analytic diabatic potential energy matrix (DPEM) that describes the N–H photodissociation of methylamine; the electronic state space includes the ground and first excited singlet states. The input for the fit was calculated by extended multi-state complete active space second-order perturbation theory. The data were diabatized using the dipole–quadrupole diabatization method in which we incorporated a coordinate-dependent weighting scheme for the contribution of the quadrupole moments. Therefore, to make the resulting potential energy surfaces semiglobal, we extended the anchor points reactive potential method, a multiscale approach that assigns the internal coordinates to categories with different levels of computational treatment. Key aspects of the adiabatic potential energy surfaces obtained by diagonalizing the DPEM agree with the available experimental and theoretical data at energies relevant for photochemical studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimal Coordination of Distributed Energy Resources Using Deep Deterministic Policy Gradient

Recent studies showed that reinforcement learning (RL) is a promising approach for coordination and control of distributed energy resources (DER) under uncertainties. Many existing RL approaches, including Q-learning and approximate dynamic programming, are based on lookup table methods, which become inefficient when the problem size is large and infeasible when continuous states and actions are involved. In addition, when modeling battery energy storage system (BESS), the loss of life is not reasonably considered into the decision-making process. This paper proposes an innovative deep RL method for DER coordination considering BESS degradation. The proposed deep RL is designed based on an adaptive actor-critic architecture and employs an off-policy deterministic policy gradient method for determining the dispatch operation that minimizes the operation cost and BESS life loss. Case studies were performed to validate the proposed method and demonstrate the effects of incorporating degradation models into control design.

Das, Avijit↗
DOE OSTI2025

Corrosion resistant hot melt adhesive to bind metals

Hot melt adhesives (HMAs) play an important role in many industries, and their demand is expected to grow. HMAs don't require any solvents, and their application results in the formation of strong bonds with the substrate upon cooling within seconds. These properties differentiate them from liquid glues and make them preferable for practical application. Currently, commercial HMAs are used in bonding lightweight materials such as paper, polymers, and cartons, and have limited usage in areas necessitating the bonding of heavier objects like metals. Here, in this study, we report a design and testing of versatile platform comprising an ion-coordinating polymer and ionic fillers for performance optimization and understanding of structure–property relationships, enabling the rational design of HMAs with improved adhesion to metal surfaces. All-atom Molecular dynamics (MD) simulations and various characterization methods are used to elucidate the adhesion mechanism in model composite system containing polyethylene oxide mixed with chemically diverse salt particles. The maximum adhesion strength is found in composites with Al(OH) 3 and FeCl 3 fillers. Interestingly, the presence of Al(OH) 3 also provides a multifunctional anticorrosion property as measured electrochemically using the Tafel method. The discovered path to formulations with improved adhesion to metal surfaces constitutes an important step toward advancing HMAs for use in the structural and semi-structural metal work domain.

Adhesive and cohesive forces↗
DOE OSTI2024

TrustDER: Trusted, Private and Scalable Coordination of Distributed Energy Resources

In this project, the Stanford and SLAC Teams have developed a Trusted, Private and Scalable platform for coordinating Coordination of Distributed Energy Resources (TrustDER). This is a layered system that ensures private, trusted and scalable coordination and monitoring of DERs. It accommodates a variety of resources, such as solar generation, gensets and loads, with a particular focus on battery systems-based resources, as they are a transformational technology experiencing fast growth in adoption by large critical facilities. The platform can be used as standalone or added to existing aggregation systems to enable trust, privacy and resilience. TrustDER consists of layers that address each of the shortcomings of the existing state of the art. Each layer in the platform can operate independently but provides information to the layers above it to enable a novel form of overall coordination architecture. The project consists of several tasks, with each task dedicated to the design of each layer. Task 2 Resource Virtualization defined a software abstraction layer for distributed energy resources (DERs). The goal of this abstraction was to simplify the implementation of algorithms utilizing cooperation of DERs resources in a variety of use cases. Task 3 is on Secure ID for Asset Authentication. Identity Management Systems (IDMS) are a foundational infrastructure for interactions between entities (organizations, users, devices, and services). Secure ID is blockchain-based a distributed identity management system allowing (1) identity provisioning, (2) authentication, (3) authorization, and (4) identity data sharing for IoT-enabled assets on the electricity grid. In this project, the SLAC team focused on designing and testing Keymaker, a protocol for authenticating device identity managed by Secure ID. Task 5 Private and Safe Integration is focused on the design and evaluation of a DER cooperation scheme which allows for the aggregation of DERs without impacting network reliability. The approach is designed based on realistic assumptions regarding data availability, communication infrastructure limitations, and privacy. Task 6 Scalable Distributed Privacy for Information explored how virtualized batteries could be managed privately. Specifically, it examined the case in which a principal provides a partitioned battery to multiple clients. Task 7 Use Cases was to ensure that this technology was applied in relevant situations and scenarios. Primarily, this means that virtualization needed to be employed in a manner that either improved flexibility, bolstered security or privacy, or decreased costs.

25 ENERGY STORAGE↗
DOE OSTI2021

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

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

Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors

Amorphous oxyhalides have attracted significant attention due to their relatively high ionic conductivity (1 mS cm –1 ), excellent chemical stability, mechanical softness, and facile synthesis routes via standard solid‐state reactions. These materials exhibit an ionic conductivity that is almost independent of the underlying chemistry, in stark contrast to what occurs in crystalline conductors. In this work, we employ machine learning interatomic potentials to construct large‐scale molecular dynamics trajectories encompassing hundreds of nanoseconds to obtain statistically converged transport properties. We find that the amorphous state consists of chain fragments of metal‐anion tetrahedra of various lengths. By analyzing the residence time of alkali cations migrating around tetrahedrally‐coordinated metals, we find that oxygen anions limit alkali diffusion. By computing the full Einstein expression of the ionic conductivity, we demonstrate that the alkali transference number of these materials is strongly influenced by distinct‐particles correlations, while alkali transport is dictated by uncorrelated self‐diffusion. By extending this analysis to chemical compositions AMX 2.5 O 0.75 , spanning different alkaline (A = Li, Na, K), metallic (M = Al, Ga, In), and halogen (X = Cl, Br, I) species, we clarify why the diffusion properties of these materials remain largely insensitive to variations in atomic isovalent chemistry.

amorphous materials↗
DOE OSTI2022

Developing Reaction Chemistry Models from Reactive Molecular Dynamics: TATB

Reactive Molecular Dynamic (RMD) are used to simulate the cook-off chemistry of TATB at a variety of fixed density and fixed temperature conditions. The chemical transformations are monitored using a Coordination Geometry Analysis (CGA) approach which tracks which atom types are bonded to each specific atom. This particularly identifies oxidation state changes that occur during the transformations. Correlations between these different chemical changes are identified using a Non-negative Matrix Factorization (NMF) approach. These identify reduced order chemistry models for the TATB system which contains six components whose concentration profiles are a function of both the temperature and density/pressure. The time histories of these transformations appear to show exponential growth/decay properties that could be fit with Arrhenius rates. These components should form the basis of deflagration rate models for these materials which could then be used in mesoscale simulations to analyze accidental initiation, shock-to-detonation and detonation propagation.

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

Incorporation of rare earth elements $\text{Sc}$, $\text{Y}$ and $\text{La}$ into gibbsite

Rare earth elements (REE) are increasingly critical resources in technological applications, but the current understanding of their separation by uptake into minerals remains limited. We examined the adsorption and solubilization of scandium (Sc), yttrium (Y), and lanthanum (La) into aluminum hydroxide (gibbsite, Al(OH) 3 ). Based on spectroscopic investigations such as inductively coupled plasma-optical emission spectroscopy (ICP-OES) and time of flight-secondary ion mass spectrometry (ToF-SIMS), only Sc exhibited favorable incorporation and adsorption (0.66 and 0.06 atom%, respectively). Analysis of solid state 45 Sc magic angle spinning-nuclear magnetic resonance spectroscopy (MAS-NMR) indicated that Sc exhibits an octahedral coordination consistent with isolated substitutions for Al in the gibbsite structure, leading to a increase in lattice constants detectable by X-ray diffraction. Density functional theory (DFT) calculations reinforced this interpretation by reproducing the detected structural distortion as well as demonstrating the relatively favorable energetic basis for Sc incorporation into gibbsite by substitution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Competitive Adsorption of NH 3 and H 2 O in Metal–Organic Framework Materials: MOF-74

Elucidating the interaction between coadsorbed H 2 O and NH 3 in metal–organic frameworks (MOFs) is of paramount importance to uncover mechanistic details of their competitive coadsorption behavior as well as to guide the design of new materials for enhanced NH 3 adsorption in humid environments. Nevertheless, molecular competition between NH 3 and H 2 O within the confined nanopores of MOFs was rarely explored and is poorly understood due to challenges in characterization. Here, we combine in situ infrared spectroscopy with ab initio calculations to unveil the competition of NH 3 and H 2 O for occupying active adsorption sites in the representative MOF-74 material by analyzing the kinetics and energetics of the molecular exchange process. We find that at a high NH 3 /H 2 O ratio, the incoming NH 3 is capable of displacing metal-bound H 2 O and moving it to secondary adsorption sites due to the stronger binding of NH 3 compared with H 2 O. Interestingly, the reverse process of H 2 O displacing metal-bound NH 3 is also possible upon increasing water concentration. Our calculations show that H 2 O exchanging the preabsorbed NH 3 at the metal site is driven not only by a reduced kinetic barrier but also by a favorable energetical state resulting from the formation of water clusters at metal sites and intermolecular H-bonding between the metal-coordinated H 2 O and displaced NH 3 . Our finding emphasizes that the description of molecular occupation in MOFs at equilibrium cannot simply be established by comparing molecules’ binding energies at their strongest binding sites derived by single-component measurements; rather, intermolecular interactions can greatly affect molecular distribution at equilibrium. Furthermore, we show that vibrational modes of adsorbed NH 3 are markedly perturbed upon contact with water molecules, accompanied by a large frequency shift (>30 cm –1 ) and considerable intensity decrease, which arises from the freezing of NH 3 vibrations by coadsorbed H 2 O. As a result, the mechanistic insight obtained through our study sheds light on molecular coadsorption processes in MOFs and helps to assess NH 3 removal efficiency of MOFs containing open-metal sites under realistic conditions, particularly in the presence of humidity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deep Understanding of Strong Metal Interface Confinement: A Journey of Pd/FeO x Catalysts

Tuning the atomic interface configuration of noble metals (NMs) and transition-metal oxides is an effective straightforward yet challenging strategy to modulate the activity and stability of heterogeneous catalysts. Herein, Pd supported on mesoporous Fe 2 O 3 with a high specific surface area was rationally designed and chosen to construct the Pd/iron oxide interface. As a versatile model, the physicochemical environments of Pd nanoparticles (NPs) could be precisely controlled by taming the reduction temperature. The experimental and density functional theory calculation results unveiled that the catalyst in the support–metal interface confinement (SMIC) state showed significantly enhanced catalytic activity and sintering resistance for CO oxidation. The constructed Fe sites at the interfaces between FeO x overlayers and Pd NPs not only provided additional coordinative unsaturated ferrous sites for the adsorption and activation of O 2 , thereby facilitating the activation efficiency of O 2 , but also impressively changed the reaction pathway of CO oxidation. As a result, the catalyst followed the Pd/Fe dual-site mechanism instead of the classical Mars–van Krevelen mechanism. For the catalyst in the strong metal–support interaction (SMSI) state, its catalytic activity was seriously suppressed because of the excessive encapsulation of the active Pd sites by FeO x overlayers. Thus, the present study therefore provides detailed insights into the SMIC and SMSI in ferric oxide-supported Pd catalysts, which could guide the preparation of highly efficient supported catalysts for practical applications.

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

Color center in β -Ga 2 O 3 emitting at the telecom range

Transition metal (TM) ions incorporated into a host from a wide bandgap semiconductor are recognized as a promising system for quantum technologies with enormous potential. In this work, we report on a TM color center in β-Ga 2 O 3 with physical properties attractive for quantum information applications. The center is found to emit at 1.316 μm and exhibits weak coupling to phonons, with optically addressable higher-lying excited states, beneficial for single-photon emission within the telecom range (O-band). Using magneto-photoluminescence (PL) complemented by time-resolved PL measurements, we identify the monitored emission to be internal 1 E→ 3 A 2 spin-forbidden transitions of a 3d 8 TM ion with a spin-triplet ground state—a possible candidate for a spin qubit. We tentatively attribute this color center to a complex involving a sixfold coordinated Cu 3+ ion.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling cross-beam energy transfer with sector ray tracing

Ray-based cross-beam energy transfer (CBET) models are an essential feature of the radiation-hydrodynamic codes used to simulate inertial confinement fusion implosions, but full 3D ray-based CBET calculations can have a prohibitively high computational cost. Sector ray tracing can be used to reduce the cost by orders of magnitude in cases where the coronal plasma and laser drive can be approximated as spherically symmetric. An extension of sector ray tracing (section ray tracing) can be used to relax the assumption of a spherically symmetric drive while still retaining most of the computational savings of a sector ray trace. We discuss the foundations of sector and section ray tracing and compare them to full ray tracing.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Identification of a low-energy metastable 1 T -type phase for monolayer VSe 2

Elucidating the polymorphism of transition metal dichalcogenide layers and the interplay between structure and properties is a key challenge for the application of these materials. We identify a low-energy metastable phase of monolayer VSe 2 and elucidate its magnetic and electronic properties. This structure is distinct from the previously identified charge density wave (CDW) phase. However, while having rather distinct properties it is very close in energy to the CDW phase and is likely to be realized in experiments. Importantly, local bonding instabilities, as characterized by reconstruction of the electronic structure over a wide energy range, are important for this distortion, which includes both V off-centering in the octahedral coordination cages and a partial disproportionation into two distinct types of V. The phase does not have a ferromagnetic ground state. Furthermore, the results show that the physics of 1T–VSe 2 are richer than previously known with an interplay of Fermi surface instabilities and local bonding effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Emergence of Intermediate Range Order in Jammed Packings

We perform a structural analysis of large scale jammed packings of monodisperse, frictionless and frictional spheres to elucidate structural signatures of the static structure factor in the low-to-intermediate wave number region. We employ discrete element method simulations containing up to 8×10^{7} particles, in which the particle friction coefficient(s), including sliding, rolling, and twisting interactions, are varied. At intermediate wave number values, corresponding to length scales that lie between that of the nearest neighbor primary peak and the system size, we find the emergence of a prepeak-a signature of intermediate range order-that grows with increasing friction. We correlate the emergence of this peak to real space fluctuations in the local particle coordination number, which exhibits a grainy fluctuating field throughout the packing process that is retained in the final, mechanically stable state. While the formation of the prepeak shows varying degrees of robustness to packing protocol changes, our results suggest that preparation history may be used to construct packings with variable large length scale structural properties.

Monti, Joseph M↗
DOE OSTI2020

Room-temperature neutron and X-ray data collection of 3CL M pro from SARS-CoV-2

The replication of SARS-CoV-2 produces two large polyproteins, pp1a and pp1ab, that are inactive until cleavage by the viral chymotrypsin-like cysteine protease enzyme (3CL M pro ) into a series of smaller functional proteins. At the heart of 3CL M pro is an unusual catalytic dyad formed by the side chains of His41 and Cys145 and a coordinated water molecule. The catalytic mechanism by which the enzyme operates is still unknown, as crucial information on the protonation states within the active site is unclear. To experimentally determine the protonation states of the catalytic site and of the other residues in the substrate-binding cavity, and to visualize the hydrogen-bonding networks throughout the enzyme, room-temperature neutron and X-ray data were collected from a large H/D-exchanged crystal of ligand-free (apo) 3CL M pro .

3CL Mpro↗