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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Cross-scale Efficient Tensor Contractions for Coupled Cluster Computations Through Multiple Programming Model Backends

Coupled-cluster methods provide highly accurate models of molecular structure by explicit numerical calculation of tensors representing the correlation between electrons. These calculations are dominated by a sequence of tensor contractions, motivating the development of numerical libraries for such operations. While based on matrix-matrix multiplication, these libraries are specialized to exploit symmetries in the molecular structure and in electronic interactions, and thus reduce the size of the tensor representation and the complexity of contractions. The resulting algorithms are irregular and their parallelization has been previously achieved via the use of dynamic scheduling or specialized data decompositions. We introduce our efforts to extend the Libtensor framework to work in the distributed memory environment in a scalable and energy efficient manner. We achieve up to 240 speedup compared with the best optimized shared memory implementation. We attain scalability to hundreds of thousands of compute cores on three distributed-memory architectures, (Cray XC30&XC40, BlueGene/Q), and on a heterogeneous GPU-CPU system (Cray XK7). As the bottlenecks shift from being compute-bound DGEMM's to communication-bound collectives as the size of the molecular system scales, we adopt two radically different parallelization approaches for handling load-imbalance. Nevertheless, we preserve a uni ed interface to both programming models to maintain the productivity of computational quantum chemists.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

A detailed study of CO 2 -brine capillary trapping mechanisms as applied to geologic carbon storage. Final Report

The proposed research focuses on improved fundamental understanding of the efficiency of physical trapping mechanisms, and as such will provide the basis for subsequent upscaling efforts. The overarching hypothesis of the proposed research is that capillary pressure plays a significant role in capillary trapping of CO 2 , especially during the water imbibition stage of the sequestration process. We posit that the relevant physics of the sequestration process is more complex than is currently captured in relative permeability models, which are often based on so-called trapping models to represent relative permeability hysteresis. Our 4 main questions, guiding the 4 main tasks of the proposed research, are as follows: (1) What is the morphology of capillary trapped CO 2 at the pore scale as a function of temperature, pressure, brine concentration, interfacial tension, and pore-space morphology under injection and subsequent imbibition? (2) Is it possible to describe the capillary trapping process using formation-dependent, but otherwise unique continuum-scale functions in permeability-capillary pressure, interfacial area and saturation space, rather than hysteretic functions in permeability-saturation or capillary pressure-saturation space? (3) How do continuum-scale relationships between kr-Pc-S-Anw developed based on pore-scale observations compare with traditional models incorporating relative permeability hysteresis (such as Land’s and other models,) and with observations at the core (5-10cm) scale? (4) How can trapped CO 2 volume be optimized via engineered injection and sweep strategies, and as a function of formation type (incl. heterogeneity)?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SPND Sensitivity Calculations Using MCNP and Experimental Data from ACRR

The use of the Monte Carlo N-Particle Transport Code (MCNP) to calculate detector sensitivity for Self-Powered Neutron Detectors (SPNDs) in the Annular Core Research Reactor (ACRR) could be a vital tool in the effort to optimize the design of next-generation SPNDs. Next-generation SPND designs, which consider specific materials and geometry, may provide experimenters with capabilities for advanced mixed field dosimetry. These detectors will need to be optimized for configuration, materials, and geometries and the ability to model and iterate must be available in order to decide on the ideal. SPND design. SPNDs were modeled in MCNP which closely resembled the dimensions and location of actual detectors used in the ACRR. Tallies were used to calculate detector sensitivity. Using metrics from a previous report, oscilloscope data from pulses were manipulated in a Matrix Laboratory computing environment (MATLAB) script to calculate experimental detector sensitivity. This report outlines the process in which experimental data from ACRR pulses verified results from tallies in an MCNP ACRR model. The sensitivity values from experiments and MCNP calculations agreed within one standard deviation. Parametric studies were also performed with MCNP to investigate the effects of materials and dimensions of different SPNDs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Real-Time Monitoring of Temperature Rises of Energized Transformer Cores With Distributed Optical Fiber Sensors

Real-time temperature mapping that solves local overheating problems is important for obtaining an optimized thermal design for high-efficiency power transformers. Internal temperature monitoring of operating power transformers can also be leveraged for asset monitoring applications targeting at fault detection enabling condition-based maintenance. Transformers present a variety of challenging sensing environments such as high levels of electromagnetic interference and limited space for conventional sensors to operate. Immersion of power transformers in insulation oils for thermal management during operation and the presence of relatively large and time-varying electrical and occasional magnetic fields make sensing technologies requiring electrical wires or active power at sensing locations highly undesirable. In this work, we investigate thermal response of a standard telecom fiber instrumented on compact transformer cores by using an optical frequency-domain reflectometry scheme. As a result, correlation between conventional temperature sensing methods and fiber-optic sensing results as well as tradeoffs between spatial resolution and temperature measurement accuracy is discussed and spatially resolved real-time monitoring of temperatures in energized transformers is experimentally demonstrated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Formation and mechanism of nanocrystalline AZ91 powders during HDDR processing

Grain sizes of AZ91 alloy powders were markedly refined to about 15 nm from 100 to 160 μm by an optimized hydrogenation-disproportionation-desorption-recombination (HDDR) process. The effect of temperature, hydrogen pressure and processing time on phase and microstructure evolution of AZ91 alloy powders during HDDR process was investigated systematically by X-ray diffraction, optical microscopy, scanning electron microscopy and transmission electron microscopy, respectively. The optimal HDDR process for preparing nanocrystalline Mg alloy powders is hydriding at temperature of 350 °C under 4 MPa hydrogen pressure for 12 h and dehydriding at 350 °C for 3 h in vacuum. A modified unreacted core model was introduced to describe the mechanism of grain refinement of during HDDR process. - Highlights: • Grain size of the AZ91 alloy powders was significantly refined from 100 μm to 15 nm. • The optimal HDDR technology for nano Mg alloy powders is obtained. • A modified unreacted core model of grain refinement mechanism was proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Grain engineering: How nanoscale inhomogeneities can control charge collection in solar cells

Statistical and correlative analysis are increasingly important in the design and study of new materials, from semiconductors to metals. Non-destructive measurement techniques, with high spatial resolution, capable of correlating composition and/or structure with device properties, are few and far between. For the case of polycrystalline and inhomogeneous materials, the added challenge is that nanoscale resolution is in general not compatible with the large sampling areas necessary to have a statistical representation of the specimen under study. For the study of grain cores and grain boundaries in polycrystalline solar absorbers this is of particular importance since their dissimilar behavior and variability throughout the samples makes it difficult to draw conclusions and ultimately optimize the material. In this study, we present a nanoscale in-operando approach based on the multimodal utilization of synchrotron nano x-ray fluorescence and x-ray beam induced current collected for grain core and grain boundary areas and correlated pixel-by-pixel in fully operational Cu(In(1-x)Gax)Se2Cu(In(1-x)Gax)Se2 solar cells. We observe that low gallium cells have grain boundaries that over perform compared to the grain cores and high gallium cells have boundaries that under perform. These results demonstrate how nanoscale correlative X-ray microscopy can guide research pathways towards grain engineering low cost, high efficiency solar cells.

14 SOLAR ENERGY↗
DOE OSTI2020

CCM vs. CRM Design Optimization of a Boost-derived Parallel Active Power Decoupler for Microinverter Applications

Single-phase inverter or rectifier systems often make use of an auxiliary active power decoupler (APD) to balance the mismatch between steady DC power and fluctuating AC power. This paper deals with efficiency and size optimization of a parallel boost-type APD circuit for PV microinverter applications. Specifically, design of an eGaNFET-based, 400 W APD circuit, employing planar inductor and operating in either continuous conduction mode (CCM) or critical conduction mode (CRM) is considered. Available design variables including inductance value, inductor core geometry, capacitor voltage, switching frequency, and modulation scheme (CCM vs. CRM) are explored to identify Pareto-optimal configurations, which can achieve low California Energy Commission (CEC) efficiency drop while also reducing the footprint area of the inductor. The theoretical study predicts that the optimal CRM design can achieve 37% reduced inductor size, while operating with similar efficiency drop, compared to the optimal CCM design. Experimental results, obtained using two separate 40 V, 400 W hardware prototypes for CCM and CRM, are presented to verify the analyses.

14 SOLAR ENERGY↗
DOE OSTI2025

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2025

Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference

In this work, we present two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport (COT) problems. Both approaches enable conditional sampling and conditional density estimation, which are core tasks in Bayesian inference—particularly in the simulation-based (“likelihood-free”) setting. Our methods represent the target conditional distribution as a transformation of a tractable reference distribution. Obtaining such a transformation, chosen here to be an approximation of the COT map, is computationally challenging even in moderate dimensions. To improve scalability, our numerical algorithms use neural networks to parameterize candidate maps and further exploit the structure of the COT problem. Our static approach approximates the map as the gradient of a partially input convex neural network. It uses a novel numerical implementation to increase computational efficiency compared to state-of-the-art alternatives. Our dynamic approach approximates the conditional optimal transport via the flow map of a regularized neural ODE; compared to the static approach, it is slower to train but offers more modeling choices and can lead to faster sampling. We demonstrate both algorithms numerically, comparing them with competing state-of-the-art approaches, using benchmark datasets and simulation-based Bayesian inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Heterogeneous data-processing optimization with CLARA’s adaptive workflow orchestrator

The hardware landscape used in HEP and NP is changing from homogeneous multi-core systems towards heterogeneous systems with many different computing units, each with their own characteristics. To achieve maximum performance with data processing, the main challenge is to place the right computing on the right hardware. In this paper, we discuss CLAS12 charge particle tracking workflow orchestration that allows us to utilize both CPU and GPU to improve the performance. The tracking application algorithm was decomposed into micro-services that are deployed on CPU and GPU processing units, where the best features of both are intelligently combined to achieve maximum performance. In this heterogeneous environment, CLARA aims to match the requirements of each micro-service to the strength of a CPU or a GPU architecture. A predefined execution of a micro-service on a CPU or a GPU may not be the most optimal solution due to the streaming data-quantum size and the data-quantum transfer latency between CPU and GPU. So, the CLARA workflow orchestrator is designed to dynamically assign micro-service execution to a CPU or a GPU, based on the online benchmark results analyzed for a period of real-time data-processing.

Gyurjyan, Vardan↗
DOE OSTI2017

Trust-region based return mapping algorithm for implicit integration of elastic-plastic constitutive models

A new method for the solution of the non-linear equations forming the core of constitutive model integration is proposed. Specifically, the trust-region method that has been developed in the numerical optimization community is successfully modified for use in implicit integration of elastic-plastic models. Although attention here is restricted to these rate-independent formulations, the proposed approach holds substantial promise for adoption with models incorporating complex physics, multiple inelastic mechanisms, and/or multiphysics. As a first step, the non-quadratic Hosford yield surface is used as a representative case to investigate computationally challenging constitutive models. The theory and implementation are presented, discussed, and compared to other common integration schemes. Multiple boundary value problems are studied and used to verify the proposed algorithm and demonstrate the capabilities of this approach over more common methodologies. Robustness and speed are then investigated and compared to existing algorithms. As a result through these efforts, it is shown that the utilization of a trust-region approach leads to superior performance versus a traditional closest-point projection Newton-Raphson method and comparable speed and robustness to a line search augmented scheme.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tuning Excited-State Charge Transfer Character in Cofacial Core-Substituted Perylenediimide Dimers

Understanding the interplay between excimer formation and symmetry-breaking charge separation is important for optimizing charge separation in organic photovoltaic materials. To explore this connection, we synthesized four 1,6,7,12-tetrakis( p -X-phenoxy)perylene-(3,4:9,10)-bisdicarboximide cofacially stacked dimers, where X = MeO, tert -butyl, Br, and CF 3 . Steady-state spectroscopy reveals H-type aggregation and excimer formation in all four dimers, while transient absorption spectroscopy shows relatively small changes in their excited-state absorptions. However, time-resolved fluorescence (TRF) spectroscopy shows that relaxation occurs from an initial Frenkel exciton-dominated excimer state to one in which charge transfer (CT) character contributes. Relaxation to the lower-lying state with CT character is attributed to a combination of structural and charge distribution changes elicited by varying the substituents. Finally, this study illustrates how subtle changes in charge distribution and structure can combine to influence the excited state dynamics that influence charge separation in molecular dimers.

fluorescence↗
DOE OSTI2016

Chemistry in CESM-SE: Evaluation, Performance and Optimization

The purpose of the proposed work focused on development of chemistry representation within the Spectral Element (SE) dynamical core as implemented in the Community Earth System Model (CESM). More specifically, a main focus was on the ability of SE to accurately represent tracer transport. The proposed approach was to incrementally increase the complexity of the problem, starting from specified two-dimensional flow and tracers to simulations using specified dynamics and full chemistry. As demonstrated below, we have successfully studied all aspects of the proposed work, although only part of the work has been published in the refereed literature so far. Furthermore, because the SE dynamical core has been found to have several deficiencies that are still being investigated for solution, not all proposed tasks were finalized. In addition to the tests for SE performance, in an effort to decrease the computational burden of interactive chemistry, especially in the case of a large number of chemical species and chemical reactions, development on a faster chemical solver and implementation on GPUs has been implemented in CESM under the leadership of John Drake (U. Tennessee).

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

Development of Low-Cost, High-Performance, Easy-To-Apply, Non-Flammable, Inorganic Phase Change Material (PCM) Technology (Project Final Report)

This report describes a 45-months long research program focused on the development of novel, easy-to-apply, non-flammable, and high-performance inorganic phase change materials (PCMs) for building and industrial applications. The University of Massachusetts Lowell (UML) formed a world-class team consisting of researchers form InsolCorp (only N. American manufacturer of inorganic PCM systems for building applications), and a group of industrial advisors, to develop a universal/multipurpose, simple-to-manufacture and cost-effective PCM technology. The project team expects that the results of this work will spur in the future the adoption of thermal storage materials – a key building energy saving technology as identified by DOE BTO – for a variety of building envelope applications. The main goal of this project was to demonstrate a suite of low-cost, multipurpose, and durable inorganic PCM formulations with phase transition temperatures encompassing typical building applications (between +5 o C and +55 o C). The first objective was to design, fabricate, and experimentally validate a performance of inexpensive, durable, highly efficient, non-flammable, and easy to manufacture PCMs. To allow a variety of building applications, the project team focused on formulations that exhibit repeatable phase transitions between +5 o C and +55 o C. To follow the DOE BTO cost efficiency target without compromising thermal performance, our work was based on inorganic compounds (mostly salt hydrates) and their blends, which represent a fraction of the cost of most of organic PCMs with about twice as high density as well as significantly higher thermal conductivity and phase change enthalpy. The second objective was to develop easy-to-manufacture and -install packaging/encapsulation designs that are 1) a superior barrier to current state-of-the-art macro-packaging, which significantly reduces the risk of loss of hydration water and PCM leak, and 2) optimal in enhancing the heat exchange rates with the surroundings and within the PCM core to ensure complete charging/discharging of the entire PCM within the product. Finally, the project’s intend was to scale-up the fabrication process to demonstrate installation on system-scale applications, and to validate the performance under field conditions. This work aimed at developing low-cost, high-energy storage, and reliable latent heat storage technology for building applications. This development was realized by formulating and integrating the following two technology components: 1) inorganic salt hydrate based PCMs that have high latent enthalpies and are low-cost and durable, and 2) PCM encapsulation (packaging) technology that maximizes PCM concentration and enhances heat transport characteristics in the product and with the external environment/materials. High thermal storage capacity, low cost and fire resistance are key to the building market entry for PCM technology. Therefore, the project’s focus was on salt-hydrate-based formulations which satisfy all these criteria. Packaging and/or encapsulation of PCM is a key processing step. The project team recognized that a low-cost and simple-to-manufacture salt hydrate-based PCM technology holds the best chance to be successful in the building construction market, a market which is traditionally extremely sensitive to cost and where commodity thermal insulations are the benchmark for envelope-related energy saving measures. That is why, in this project, the main intention was to minimize the production cost and maximize the product energy storage density without sacrificing the PCM performance. It was achieved through: 1. Minimizing the non-PCM components (plastics, additives, packaging/encapsulation materials, etc.) because they are significantly more expensive than salt hydrates, 2. Using highly thermally conductive and lightweight PCM carrier (packaging material) to facilitate more complete phase cycling, and 3. Optimizing the thickness and minimizing air spaces in product design (such as in pouched PCM). For this purpose, our approach was to enable an easy system design, including selection of the PCM operating temperatures, optimizing the necessary heat storage capacity (by stacking together several layers of PCM products), and if needed, a synchronized usage of PCM products of different temperatures. A specially designed, robust, highly thermally conducting and highly impermeable packaging (to retain salt hydrate water during phase transition cycles) was designed and tested to increase the overall system thermal performance and durability. All PCM products developed during this project were tested in both lab scale and in full scale field conditions. It is expected that, after further developments and commercialization, the developed PCM technologies may be also applied in space conditioning, energy storage technologies, and heat transfer applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Theoretical Correlation of Elemental Distribution of Nd and Pr in Ce-Fe-B Microstructure With Hard Magnetic Properties

Relatively resource-rich but property inferior-Ce-Fe-B magnet can be improved by partial replacement of Ce by Nd and/or Pr. In addition to the amount of Nd/Pr, their distribution profile in microstructure plays an important role. From our first principles density functional theory (DFT) calculation, the substitution energy of Ce by Pr/Nd is negative in Ce 2 Fe 14 B (2:14:1) while that for laves phase, CeFe 2 is positive, implying that Nd/Pr stabilize 2:14:1 and suppress the formation of the CeFe 2 phase. Further, micromagnetic simulation indicates that homogenized distribution of Nd/Pr improves squareness of demagnetization curve, while core (Ce-rich)-shell (Nd/Pr-rich) 2:14:1 grain structure enhances coercivity. Magnetic properties of Ce-Fe-B can be optimized by manipulating distribution profile of chemical element in microstructure based on their subtle difference in thermodynamic property, which is an effective pathway to design optimized chemical composition and processing route for high-performance magnet.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tailoring tokamak error fields to control plasma instabilities and transport

A tokamak relies on the axisymmetric magnetic fields to confine fusion plasmas and aims to deliver sustainable and clean energy. However, misalignments arise inevitably in the tokamak construction, leading to small asymmetries in the magnetic field known as error fields (EFs). The EFs have been a major concern in the tokamak approaches because small EFs, even less than 0.1%, can drive a plasma disruption. Meanwhile, the EFs in the tokamak can be favorably used for controlling plasma instabilities, such as edge-localized modes (ELMs). Here we show an optimization that tailors the EFs to maintain an edge 3D response for ELM control with a minimized core 3D response to avoid plasma disruption and unnecessary confinement degradation. We design and demonstrate such an edge-localized 3D response in the KSTAR facility, benefiting from its unique flexibility to change many degrees of freedom in the 3D coil space for the various fusion plasma regimes. This favorable control of the tokamak EF represents a notable advance for designing intrinsically 3D tokamaks to optimize stability and confinement for next-step fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗
DOE OSTI2023

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗