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Designing architected materials for mechanical compression via simulation, deep learning, and experimentation

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npj Computational Materials 2023年第1期9卷 1534-1542页

作者： Andrew J.Lew Kai Jin Markus J.Buehler Laboratory for Atomistic and Molecular Mechanics(LAMM) Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA department of Chemistry Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA Center for Computational Science and engineering Schwarzman College of ComputingMassachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA

Architected materials can achieve enhanced properties compared to their plain *** architecting serves as a powerful design lever to achieve targeted behavior without changing the base ***,the connection between architected structure and resultant properties remains an open field of great interest to many fields,from aerospace to civil to automotive ***,we focus on properties related to mechanical compression,and design hierarchical honeycomb structures to meet specific values of stiffness and compressive *** do so,we employ a combination of techniques in a singular workflow,starting with molecular dynamics simulation of the forward design problem,augmenting with data-driven artificial intelligence models to address the inverse design problem,and verifying the behavior of de novo structures with experimentation of additively manufactured *** thereby demonstrate an approach for architected design that is generalizable to multiple material properties and agnostic to the identity of the base material.

关键词： thereby additive starting

DEEP-squared:deep learning powered De-scattering with Excitation Patterning

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Light(Science & Applications) 2023年第10期12卷 2199-2214页

作者： Navodini Wijethilake Mithunjha Anandakumar Cheng Zheng Peter T.C.So Murat Yildirim Dushan N.Wadduwage Center for Advanced Imaging Faculty of Arts and SciencesHarvard UniversityCambridgeMAUSA department of Electronic and Telecommunication engineering University of MoratuwaMoratuwaSri Lanka department of mechanical engineering Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA Laser Biomedical Research Center Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA department of Biological engineering Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA Picower Institute for Learning and Memory Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA department of Neuroscience Cleveland Clinic Lerner Research InstituteClevelandOH 44195USA

Limited throughput is a key challenge in in vivo deep tissue imaging using nonlinear optical *** scanning multiphoton microscopy,the current gold standard,is slow especially compared to the widefield imaging modalities used for optically cleared or thin *** recently introduced“De-scattering with Excitation Patterning”or“DEEP”as a widefield alternative to point-scanning *** patterned multiphoton excitation,DEEP encodes spatial information inside tissue before ***,to de-scatter at typical depths,hundreds of such patterned excitations were *** this work,we present DEEP2,a deep learning-based model that can de-scatter images from just tens of patterned excitations instead of ***,we improve DEEP’s throughput by almost an order of *** demonstrate our method in multiple numerical and experimental imaging studies,including in vivo cortical vasculature imaging up to 4 scattering lengths deep in live mice.

关键词： scattering excitation scatter

Effect of ammonia gas etching on growth of vertically aligned carbon nanotubes/nanofibers

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Transactions of Nonferrous Metals Society of China 2011年第A1期21卷 130-134页

作者： Sang-Gook KIM Sooh-Yung KIM Hyung-Woo LEE department of mechanical engineering Massachusetts Institute of Technology 77 Massachusetts Ave Cambridge MA 02139 USA National Core Research Center for Hybrid Materials Solution Pusan National University

The etching effect of ammonia （NH3） on the growth of vertically aligned nanotubes/nanofibers （CNTs） was investigated by direct-current plasma enhanced chemical vapor deposition （DC-PECVD）. NH3 gas etches Ni catalyst layer to form nanoscale islands while NH3 plasma etches the deposited amorphous carbon. Based on the etching effect of NH3 gas on Ni catalyst, the differences of growing bundles of CNTs and single strand CNTs were discussed; specifically, the amount of optimal NH3 gas etching is different between bundles of CNTs and single strand CNTs. In contrast to the CNT carpet growth, the single strand CNT growth requires shorter etching time （5 min） than large catalytic patterns （10 rain） since nano dots already form catalyst islands for CNT growth. Through removing the plasma pretreatment process, the damage from being exposed at high temperature substrate occurring during the plasma generation time is minimized. High resolution transmission electron microscopy （HTEM） shows fishbone structure of CNTs grown by PECVD.

关键词： carbon nanotube ammonia etching nickel catalyst plasma enhanced chemical vapor deposition (PECVD)

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Full noncontact laser ultrasound:first human data

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Light(Science & Applications) 2019年第1期8卷 11-21页

作者： Xiang Zhang Jonathan R.Fincke Charles M.Wynn Matt R.Johnson Robert W.Haupt Brian W.Anthony department of mechanical engineering Massachusetts Institute of Technology77 Massachusetts Ave.CambridgeMA 02139USA Institute for Medical engineering&Science Massachusetts Institute of Technology45 Carleton St.CambridgeMA 02142USA Lincoln Laboratory Massachusetts Institute of Technology244 Wood StreetLexingtonMA 02421USA

Full noncontact laser ultrasound(LUS)imaging has several distinct advantages over current medical ultrasound(US)technologies:elimination of the coupling mediums(gel/water),operator-independent image quality,improved repeatability,and volumetric *** light-based ultrasound utilizing tissue-penetrating photoacoustics(PA)generally uses traditional piezoelectric transducers in contact with the imaged tissue or carries an optical fiber detector close to the imaging *** PA,the LUS design presented here minimizes the optical penetration and specifically restricts optical-to-acoustic energy transduction at the tissue surface,maximizing the generated acoustic source *** an appropriate optical design and interferometry,any exposed tissue surfaces can become viable acoustic sources and *** operates analogously to conventional ultrasound but uses light instead of piezoelectric ***,we present full noncontact LUS results,imaging targets at~5 cm depths and at a meterscale standoff from the target *** results demonstrating volumetric imaging and the first LUS images on humans are presented,all at eye-and skin-safe optical exposure *** progression of LUS imaging from tissue-mimicking phantoms,to excised animal tissue,to humans in vivo is shown,with validation from conventional ultrasound *** LUS system design insights and results presented here inspire further LUS development and are a significant step toward the clinical implementation of LUS.

关键词： laser piezoelectric image

Dynamical machine learning volumetric reconstruction of objects’ interiors from limited angular views

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Light(Science & Applications) 2021年第5期10卷 824-844页

作者： Iksung Kang Alexandre Goy George Barbastathis department of Electrical engineering and Computer Science Massachusetts Institute of Technology77 Massachusetts AveCambridgeMAUSA department of mechanical engineering Massachusetts Institute of TechnologyCambridgeMA 02139USA Singapore-MIT Alliance for Research and technology(SMART)Centre 1 Create WaySingapore 117543Singapore Omnisens SA Morges 1110Switzerland

Limited-angle tomography of an interior volume is a challenging, highly ill-posed problem with practical implications in medical and biological imaging, manufacturing, automation, and environmental and food security. Regularizing priors are necessary to reduce artifacts by improving the condition of such problems. Recently, it was shown that one effective way to learn the priors for strongly scattering yet highly structured 3D objects, e.g. layered and Manhattan, is by a static neural network [Goy et al. Proc. Natl. Acad. Sci. 116, 19848–19856 (2019)]. Here, we present a radically different approach where the collection of raw images from multiple angles is viewed analogously to a dynamical system driven by the object-dependent forward scattering operator. The sequence index in the angle of illumination plays the role of discrete time in the dynamical system analogy. Thus, the imaging problem turns into a problem of nonlinear system identification, which also suggests dynamical learning as a better fit to regularize the reconstructions. We devised a Recurrent Neural Network (RNN) architecture with a novel Separable-Convolution Gated Recurrent Unit (SC-GRU) as the fundamental building block. Through a comprehensive comparison of several quantitative metrics, we show that the dynamic method is suitable for a generic interior-volumetric reconstruction under a limited-angle scheme. We show that this approach accurately reconstructs volume interiors under two conditions: weak scattering, when the Radon transform approximation is applicable and the forward operator well defined;and strong scattering, which is nonlinear with respect to the 3D refractive index distribution and includes uncertainty in the forward operator.

关键词： interior dynamical angular

Computational and theoretical modeling of intermediate filament networks:Structure,mechanics and disease

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Acta Mechanica Sinica 2012年第4期28卷 941-950页

作者： Zhao Qin Markus J. Buehler Laboratory for Atomistic and Molecular Mechanics (LAMM) Department of Civil and Environmental Engineering 77 Massachusetts Ave. Massachusetts Institute of Technology Room 1-235 A&B Cambridge 02139 MA USA Center for Computational Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. Cambridge MA 02139 USA Center for Materials Science and engineering Massachusetts Institute of Technology77 Massachusetts Ave. Cambridge MA 02139 USA

Intermediate filaments, in addition to microtubules and actin microfilaments, are one of the three major components of the cytoskeleton in eukaryotic cells. It was discovered during the recent decades that in most cells, intermediate filament proteins play key roles to reinforce cells subjected to large-deformation, and that they participate in signal transduction, and it was proposed that their nanome- chanical properties are critical to perform those functions. However, it is still poorly understood how the nanoscopic structure, as well as the combination of chemical composition, molecular structure and interfacial properties of these protein molecules contribute to the biomechanical properties of filaments and filament networks. Here we review recent progress in computational and theoretical studies of the intermediate filaments network at various levels in the protein＇s structure. A multiple scale method is discussed, used to couple molecular modeling with atomistic detail to larger-scale material properties of the networked material. It is shown that a finer-trains-coarser method- ology as discussed here provides a useful tool in understanding the biomechanical property and disease mechanism of intermediate filaments, coupling experiment and simulation. It further allows us to improve the understanding of associated disease mechanisms and lays the foundation for engineering the mechanical properties of biomaterials.

关键词： Intermediate filament network - Multiple scale method Nanoscopic structure Mechanics Disease mechanism Molecular mechanics

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mechanical properties of crosslinks controls failure mechanism of hierarchical intermediate filament networks

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Theoretical & Applied Mechanics Letters 2012年第1期2卷 27-31页

作者： Zhao Qin Markus J. Buehler Laboratory for Atomistic and Molecular Mechanics （LAMM） Department of Civil and Environmental Engineering Massachusetts Institute of Technology 77 Massachusetts Ave. Room 1-235 A＆B Cambridge MA 02139 USA Center for Computational engineering Massachusetts Institute of Technology 77 Massachusetts Ave. Cambridge MA 02139 USA Center for Materials Science and engineering Massachusetts Institute of Technology 77 Massachusetts Ave. Cambridge MA 02139 USA

Intermediate filaments are one of the key components of the cytoskeleton in eukaryotic cells, and their mechanical properties are found to be equally important for physiological function and disease. While the mechanical properties of single full length filaments have been studied, how the mechanical properties of crosslinks affect the mechanical property of the intermediate filament network is not well understood. This paper applies a mesoscopic model of the intermediate network with varied crosslink strengths to investigate its failure mechanism under the extreme mechanical loading. It finds that relatively weaker crosslinks lead to a more flaw tolerant intermediate filament network that is also 23% stronger than the one with strong crosslinks. These findings suggest that the mechanical properties of interfacial components are critical for bioinspired designs which provide intriguing mechanical properties.

关键词： failure mechanism flow tolerance intermediate filament protein network soft material,rupture crosslink strength bioinspired design

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Elasticity,Strength and Resilience:A Comparative Study on mechanical Signatures ofα-Helix,β-Sheet and Tropocollagen Domains

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Nano Research 2008年第1期1卷 63-71页

作者： Markus J.Buehler Sinan Keten Laboratory for Atomistic and Molecular Mechanics Department of Civil and Environmental EngineeringMassachusetts Institute of Technology77 Massachusetts Ave.Room 1-235 A&BCambridgeMA02139-4307USA

In biology,structural design and materials engineering is unified through formation of hierarchical features with atomic resolution,from nano to *** molecular building blocks are particularly prevalent in all structural protein materials:alpha helices(AHs),beta-sheets(BSs)and tropocollagen(TC).In this article we present a comparative study of these three key building blocks by focusing on their mechanical signatures,based on results from full-atomistic simulation *** fi nd that each of the basic structures is associated with a characteristic material behavior:AH protein domains provide resilience at large deformation through energy dissipation at low force levels,BS protein domains provide great strength under shear loading,and tropocollagen molecules provide large elasticity for deformation *** suggests that AHs,BSs,and TC molecules have mutually exclusive mechanical *** correlate each of these basic properties with the molecule’s structure and the associated fundamental rupture *** study may enable the use of abundant protein building blocks in nanoengineered materials,and may provide critical insight into basic biological mechanisms for bio-inspired *** transfer towards the design of novel nanostructures could lead to new multifunctional and mechanically active,tunable,and changeable materials.

关键词： Fracture biology hierarchical materials materiomics proteins self-assembly mechanical properties theory strength

神经性厌食症的女性:应用平板容积CT的有限元及小梁结构分析

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国际医学放射学杂志 2010年第6期 575-576页

作者： C.J.Walsh C.M.Phan M.Misra M.A.Bredella K.K.Miller P.K.Fazeli 刘彬 department of mechanical engineering Massachusetts Institute of Technology77 Massachusetts AveRoom 3-470CambridgeMA 02139

目的使用基于平板容积CT的有限元模型和双能X线吸收骨密度仪提供的骨矿物质密度,将神经性厌食症女性与同龄、正常体质量对照组的骨衰竭载荷、硬度及小梁结

关键词：神经性厌食症正常体病人小梁质量神经官能症骨小梁参数容积梁结构 CT 女性