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Machine learning enabled autonomous microstructural characterization in 3D samples

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npj Computational Materials 2020年第1期6卷 1654-1662页

作者： Henry Chan Mathew Cherukara Troy D.Loeffler Badri Narayanan subramanian k.r.s.sankaranarayanan Center for Nanoscale Materials Argonne National LaboratoryArgonneILUSA Department of Mechanical Engineering University of LouisvilleLouisvilleKYUSA Department of Mechanical and Industrial Engineering University of Illinois at ChicagoChicagoILUSA

We introduce an unsupervised machine learning(ML)based technique for the identification and characterization of microstructures in three-dimensional(3D)samples obtained from molecular dynamics simulations,particle tracking data,or *** technique combines topology classification,image processing,and clustering algorithms,and can handle a wide range of microstructure types including grains in polycrystalline materials,voids in porous systems,and structures from self/directed assembly in soft-matter complex *** technique does not require a priori microstructure description of the target system and is insensitive to disorder such as extended defects in polycrystals arising from line and plane *** demonstrate quantitively that our technique provides unbiased microstructural information such as precise quantification of grains and their size distributions in 3D polycrystalline samples,characterizes features such as voids and porosity in 3D polymeric samples and micellar size distribution in 3D complex *** demonstrate the efficacy of our ML approach,we benchmark it against a diverse set of synthetic data samples representing nanocrystalline metals,polymers and complex fluids as well as experimentally published characterization *** technique is computationally efficient and provides a way to quickly identify,track,and quantify complex microstructural features that impact the observed material behavior.

关键词： microstructure polycrystalline porosity

A Continuous Action space Tree search for INverse desiGn (CAsTING) framework for materials discovery

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npj Computational Materials 2023年第1期9卷 500-515页

作者： suvo Banik Troy Loefller sukriti Manna Henry Chan srilok srinivasan Pierre Darancet Alexander Hexemer subramanian k.r.s.sankaranarayanan Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Advanced Light source(ALs)Division Lawrence Berkeley National LaboratoryBerkeleyCA 94720USA

Material properties share an intrinsic relationship with their structural attributes,making inverse design approaches crucial for discovering new materials with desired *** Learning(rL)approaches are emerging as powerful inverse design tools,often functioning in discrete action *** constrains their application in materials design problems,which involve continuous search ***,we introduce an rL-based framework CAsTING(Continuous Action space Tree search for inverse design),that employs a decision tree-based Monte Carlo Tree search(MCTs)algorithm with continuous space adaptation through modified policies and *** representative examples like silver(Ag)for metals,Carbon(C)for covalent systems,and multicomponent systems such as graphane,boron nitride,and complex correlated oxides,we showcase its accuracy,convergence speed,and scalability in materials discovery and ***,with the inverse design of super-hard Carbon phases,we demonstrate CAsTING’s utility in discovering metastable phases tailored to user-defined target properties and preferences.

关键词： Action framework Tree

Multi-reward reinforcement learning based development of inter-atomic potential models for silica

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npj Computational Materials 2023年第1期9卷 1059-1071页

作者： Aditya koneru Henry Chan sukriti Manna Troy D.Loeffler Debdas Dhabal Andressa A.Bertolazzo Valeria Molinero subramanian k.r.s.sankaranarayanan Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Department of Chemistry The University of UtahSalt Lake CityUT 84112USA

silica is an abundant and technologically attractive *** to the structural complexities of silica polymorphs coupled with subtle differences in si–O bonding characteristics,the development of accurate models to predict the structure,energetics and properties of silica polymorphs remain *** models for silica range from computationally efficient Buckingham formalisms(Bks,CHIk,soules)to reactive(reaxFF)and more recent machine-learned potentials that are flexible but computationally ***,we introduce an improved formalism and parameterization of Bks model via a multireward reinforcement learning(rL)using an experimental training *** model concurrently captures the structure,energetics,density,equation of state,and elastic constants of quartz(equilibrium)as well as 20 other metastable silica *** also assess its ability in capturing amorphous properties and highlight the limitations of the Bks-type functional forms in simultaneously capturing crystal and amorphous *** demonstrate ways to improve model flexibility and introduce a flexible formalism,machine-learned ML-Bks,that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential(GAP)in capturing the experimental structure and properties of silica polymorphs and amorphous silica.

关键词： amorphous potential attractive

Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

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npj Computational Materials 2021年第1期7卷 1042-1052页

作者： Xu Zhang Hoang Nguyen Jeffrey T.Paci subramanian k.r.s.sankaranarayanan Jose L.Mendoza-Cortes Horacio D.Espinosa Theoretical and Applied Mechanics Program Northwestern UniversityEvanstonILUSA Department of Chemistry University of VictoriaVictoriaBCCanada Center for Nanoscale Materials Argonne National LaboratoryLemontILUSA Department of Chemical Engineering&Materials science Michigan State UniversityEast LansingMIUSA Department of Mechanical Engineering Northwestern UniversityEvanstonILUSA

This investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation *** incorporates a multi-objective genetic algorithm,training and screening property sets,and correlation and principal component *** framework enables iterative definition of properties in the training and screening sets,guided by correlation relationships between properties,aiming to achieve optimal parametrizations for properties of ***,the performance of increasingly complex potentials,Buckingham,stillinger-Weber,Tersoff,and modified reactive empirical bond-order potentials are *** Mose_(2)as a case study,we demonstrate good reproducibility of training/screening properties and superior *** Mose_(2),the best performance is achieved using the Tersoff potential,which is ascribed to its apparent higher flexibility embedded in its functional *** results should facilitate the selection and parametrization of interatomic potentials for exploring mechanical and phononic properties of a large library of two-dimensional and bulk materials.

关键词： materials apparent enable

Inverse design of metasurfaces with non-local interactions

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npj Computational Materials 2020年第1期6卷 669-676页

作者： Haogang Cai srilok srinivasan David A.Czaplewski Alex B.F.Martinson David J.Gosztola Liliana stan Troy Loeffler subramanian k.r.s.sankaranarayanan Daniel López Center for Nanoscale Materials Argonne National LaboratoryLemontIL 60439USA Materials science Division Argonne National LaboratoryLemontIL 60439USA Department of Mechanical and Industrial Engineering University of IllinoisChicagoIL 60607USA Tech4Health Institute and Department of radiology NYU Langone HealthNew YorkNY 10016USA

Conventional metasurfaces have demonstrated efficient wavefront manipulation by using thick and high-aspect-ratio nanostructures in order to eliminate interactions between adjacent phase-shifter ***-than-wavelength dielectric metasurfaces are highly desirable because they can facilitate fabrication and integration with both electronics and mechanically tunable ***,because their constitutive phase-shifter elements exhibit strong electromagnetic coupling between neighbors,the design requires a global optimization methodology that considers the non-local ***,we propose a global evolutionary optimization approach to inverse design non-local *** optimal designs are experimentally validated,demonstrating the highest efficiencies for the thinnest transmissive metalenses reported to-date for visible *** a departure from conventional design methods based on the search of a library of pre-determined and independent meta-atoms,we take full advantage of the strong interactions among nanoresonators to improve the focusing efficiency of metalenses and demonstrate that efficiency improvements can be obtained by lowering the metasurface filling factors.

关键词： local surfaces eliminate

stigma receptivity Is Controlled by Functionally redundant MAPk Pathway Components in Arabidopsis

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Molecular Plant 2020年第11期13卷 1582-1593页

作者： Muhammad Jamshed subramanian sankaranarayanan kumar Abhinandan Marcus A.samuel University of Calgary BI 392Department of Biological Sciences2500 University Dr.NWCalgaryAB T2N 1N4Canada senior scientist Frontier Agri-Science Inc98 Ontario StreetPort HopeON L1A2V2Canada Department of Botany and Plant Pathology Purdue UniversityWest LafayetteIN 47907USA

In angiosperms,the process of pollination relies on species-specific interaction and signaling between the male(pollen)and female(pistil)counterparts where the interplay between several pollen and stigma proteins decides the fate of the *** Brassicaceae,the dry stigmatic papillary cells control pollen germination by releasing resources only to compatible pollen thereby allowing pollen to hydrate and *** the identification of a number of stigmatic proteins that facilitate pollination responses,the signaling mechanisms that regulate functions of these proteins have remained ***,we show that,in Arabidopsis,an extremely functionally redundant mitogen-activated protein kinase(MAPk)cascade is required for maintaining stigma receptivity to accept compatible *** genetic analyses demonstrate that in stigmas,five MAPk kinases(Mkks),Mkk1/2/3/7/9 are required to transmit upstream signals to two MPks,MPk3/4,to mediate compatible *** functions of these five Mkks in the quintuple mutant(mkk1/2/3rNAi/mkk7/9)phenocopied pollination defects observed in the m pk4rNAi/m pk3 double *** further show that this MAPk nexus converges on Exo70A1,a previously identified stigma receptivity factor essential for *** that pollination is the crucial initial step during plant reproduction,understanding the mechanisms that govern successful pollination could lead to development of strategies to improve crop yield.

关键词： reproduction pollination stigma receptivity compatibility MAPk redundancy Exo70A1 exocytosis phosphorylation

AutoPhaseNN:unsupervised physics-aware deep learning of 3D nanoscale Bragg coherent diffraction imaging

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npj Computational Materials 2022年第1期8卷 1146-1153页

作者： Yudong Yao Henry Chan subramanian sankaranarayanan Prasanna Balaprakash ross J.Harder Mathew J.Cherukara Advanced Photon source Argonne National LaboratoryLemontIL60439USA Center for Nanoscale Materials Argonne National LaboratoryLemontIL60439USA Mathematics and Computer science Argonne National LaboratoryLemontIL60439USA

The problem of phase retrieval underlies various imaging methods from astronomy to nanoscale *** phase retrieval methods are iterative and are therefore computationally *** learning(DL)models have been developed to either provide learned priors or completely replace phase ***,such models require vast amounts of labeled data,which can only be obtained through simulation or performing computationally prohibitive phase retrieval on experimental *** 3D X-ray Bragg coherent diffraction imaging(BCDI)as a representative technique,we demonstrate AutoPhaseNN,a DL-based approach which learns to solve the phase problem without labeled *** incorporating the imaging physics into the DL model during training,AutoPhaseNN learns to invert 3D BCDI data in a single shot without ever being shown real space *** trained,AutoPhaseNN can be effectively used in the 3D BCDI data inversion about 100×faster than iterative phase retrieval methods while providing comparable image quality.

关键词： coherent iterative replace

Intelligent Deployment Model for Target Coverage in Wireless sensor Network

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Intelligent Automation & soft Computing 2023年第1期35卷 739-754页

作者： k.subramanian s.shanmugavel Department of ECE National Engineering CollegeKovilpattiTamilnaduIndia

Target coverage and continuous connection are the major recital factors for Wireless sensor Network(WsN).several previous research works studied various algorithms for target coverage difficulties;however they lacked to focus on improving the network’s life time in terms of *** research work mainly focuses on target coverage and area coverage problem in a heterogeneous WsN with increased network *** dynamic behavior of the target nodes is unpredictable,because the target nodes may move at any time in any direction of the ***,target coverage becomes a major problem in WsN and its *** solve the issue,this research work is motivated to design and develop an intelligent model named Distributed Flexible Wheel Chain(DFWC)model for efficient target coverage and area coverage in WsN *** number of target nodes is covered by minimum number of sensor nodes that can improve energy *** be specific,DFWC motivated at obtaining lesser connected target coverage,where every target is available in the monitoring area is covered by a smaller number of sensor *** simulation results show that the proposed DFWC model outperforms the existing models with improved performance.

关键词： WsN target coverage DF WC network coverage

Experimental Investigation for NO_x Emission reduction in Hydrogen Fueled spark Ignition Engine Using spark Timing retardation, Exhaust Gas recirculation and Water Injection Techniques

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Journal of Thermal science 2019年第4期28卷 789-800页

作者： JEErAGAL ramesh k.A.subramanian Engines and Unconventional Fuels Laboratory Centre for Energy Studies IIT Delhi

The experimental tests were carried out on a single cylinder hydrogen fueled spark ignition(sI)generator set with different spark timings(4-20℃A bTDC),exhaust gas recirculation(EGr)up to 28% by volume and water injection up to 1.95 kg/h(maximum water to fuel mass ratio of 8:1).The engine speed was kept constant of 3000 r/*** NOx emission and thermal efficiency of engine with gasoline and hydrogen fuel operation at 1.4 kW power output are 5 g/kWh and 12.1 g/kWh,and 15% and 20.9% *** order to reduce the NOx emission at source level,retarding spark timing,exhaust gas recirculation(EGr),and water injection techniques were *** emission decreased with spark timing retardation,EGr,and water *** emission with hydrogen at 1.4 kW power output decreased from 12.1 g/kWh with maximum brake torque(MBT)spark timing(10℃A bTDC)to 8.1 g/kWh with retarded spark timing(4℃A bTDC)due to decrease in the in-cylinder peak pressure and *** Nox emission decreased to 6.1 g/kWh with 20% EGr due to thermal and chemical dilution ***,thermal efficiency decreased about 33% and 17% with spark timing retardation and 20EGr respectively as compared to that of MBT spark ***,in the case of water injection,the NOx emission decreased significantly without affecting the thermal efficiency of the engine and it is 5.6 g/kWh with water-hydrogen ratio of 4:1(water flow rate of 0.92 kg/h).Water injection is the best suitable method to reduce the NOx emission in a hydrogen fueled engine compared with the spark timing retardation and EGr technique.

关键词： hydrogen spark ignition engine spark timing exhaust gas recirculation NOx emission water injection