Craig Hamel - Academia.edu (original) (raw)

Papers by Craig Hamel

Research paper thumbnail of Data Stewardship and Validation Methods for Mechanics of Materials at Sandia

Proposed for presentation at the Society of Engineering Science Annual Technical Meeting (SES 2022) in ,

Research paper thumbnail of Modeling Influences of Printing Defects on Mechanical Properties of Additively Manufactured Silicone Structures

Proposed for presentation at the The 8th European Congress on Computational Methods in Applied Sciences and Engineering held June 5-9, 2022 in Oslo, Norway

Research paper thumbnail of Modular machine learning-based elastoplasticity: Generalization in the context of limited data

Computer Methods in Applied Mechanics and Engineering

Research paper thumbnail of Calibrating constitutive models with full‐field data via physics informed neural networks

Strain

The calibration of solid constitutive models with full‐field experimental data is a long‐standing... more The calibration of solid constitutive models with full‐field experimental data is a long‐standing challenge, especially in materials that undergo large deformations. In this paper, we propose a physics‐informed deep‐learning framework for the discovery of hyperelastic constitutive model parameterizations given full‐field surface displacement data and global force‐displacement data. Contrary to the majority of recent literature in this field, we work with the weak form of the governing equations rather than the strong form to impose physical constraints upon the neural network predictions. The approach presented in this paper is computationally efficient, suitable for irregular geometric domains, and readily ingests displacement data without the need for interpolation onto a computational grid. A selection of canonical hyperelastic material models suitable for different material classes is considered including the Neo–Hookean, Gent, and Blatz–Ko constitutive models as exemplars for g...

Research paper thumbnail of Stabilized Hyperfoam Modeling of the General Plastics EF4003 (3 PCF) Flexible Foam

Research paper thumbnail of Mechanics of Materials Utilizing Machine Learning: Examples at Sandia National Laboratories

Proposed for presentation at the Society of Experimental Mechanics Annual Conference 2021 - Virtual held June 14-17, 2021 in Bethel, CT, United States.

Research paper thumbnail of Developing Intelligent Structures and Devices Using Novel Smart Materials and Multi-Material Multi-Method (m4) 3D Printing

Structural Health Monitoring 2019

The advent of additive manufacturing (AM), commonly known as 3D printing, has enabled the rapid f... more The advent of additive manufacturing (AM), commonly known as 3D printing, has enabled the rapid fabrication of complex structures previously unrealizable with traditional manufacturing techniques. Current approaches, however, are limited to single materials or single methodologies greatly limiting the potential scope of manufacturable products and components. Recently, our group has developed a novel multi-material multi-method (m4) 3D printer which integrates four AM technologies and two complementary technologies into one single platform. This allows for the fabrication of complex devices able to provide a wide range of functionalities ranging from stretchable electronics to self-sensing devices. To demonstrate these functionalities in the realm of printable electronics, multiple proof of concept printed circuit boards (PCBs) were fabricated which solve issues commonly encountered in 3D printed electronics such as high resolution or vertically integrated access (VIA) circuits. In addition, 3D printed smart structures able to respond to external stimulus, such as light or heat, have become highly desirable for applications ranging from soft robotics to implantable medical devices. Recently, our group has turned to liquid crystal elastomers (LCE), a class of active material able to generate large, rapid, and reversible actuations. Therefore, using the m4 3D printer, LCE-based smart structures requiring complex electronics were fabricated which can change their shape in response to an applied current. To demonstrate this, a smart, reconfigurable radio frequency (RF) antenna was 3D printed which can change its shape and operating frequency as a function of the applied current. These examples demonstrate the vast potential of m4 3D printing for creating smart, reconfigurable, and multi-functional structures.

Research paper thumbnail of Machine learning constitutive models of elastomeric foams

Computer Methods in Applied Mechanics and Engineering

Research paper thumbnail of Constitutive Modeling of Anisotropic Flexible Foams

Research paper thumbnail of An Isotropic Large Deformation Viscoplastic-Damage Model for Flexible Foams Across a Range of Relative Densities

Research paper thumbnail of The 3D printing and modeling of functionally graded Kelvin foams for controlling crushing performance

Extreme Mechanics Letters, 2021

Abstract Mechanical impact protection is an important consideration in many applications, ranging... more Abstract Mechanical impact protection is an important consideration in many applications, ranging from product transportation to sports. Cellular materials are typically used due to their desirable energy absorption properties and light weight. However, their large deformation and rate dependent responses (especially of polymer foams) are challenging to consider in design. Additionally, the use of foams with uniform properties, such as uniform density and uniform stiffness, often restricts the designed foams to only be suitable for a narrow range of mechanical impact conditions whereas real applications commonly face unpredictable situations. 3D printing offers fabrication flexibility and thus opens the door to create foams with tailored properties. In this work, we investigate the feasibility of using 3D printing for functionally graded foams (FGFs) that are optimal over a broad range of mechanical environments. The foams are fabricated by the recently developed grayscale digital light processing (g-DLP) method which can print parts with locally designed properties. These foams are tested under both drop test conditions and with slower displacement control. We also model the large deformation behavior of FGFs using finite element analysis in which we account for the different viscoelastic behaviors of the distinct grayscale regions. We then use the model to examine the impact mitigation capabilities of FGFs in different loading scenarios. Finally, we show how FGFs can be used to satisfy real-world design goals using the case study of a motorcycle helmet. In contrast to prior work, we investigate continuous, functionally graded foams of a single density that differ in their viscoelastic responses. This work provides further insight into the benefits of viscoelastic properties and modulus graded foams and presents a manufacturing approach that can be used to produce the next generation of flexible lattice foams as mechanical absorbers.

Research paper thumbnail of Thermomechanical behaviors of polyether ether ketone (PEEK) with stretch-induced anisotropy

Journal of the Mechanics and Physics of Solids, 2021

Abstract Polyether ether ketone (PEEK) is a semi-crystalline thermoplastic polymer with excellent... more Abstract Polyether ether ketone (PEEK) is a semi-crystalline thermoplastic polymer with excellent thermo-mechanical properties, bio-compatibility, corrosion resistance, and 3D printability. Due to these merits, it has wide applications in aeronautics and biomedical devices. However, PEEK's excellent thermo-mechanical properties come from its complicated crystalline domains, making it hard to predict and to design PEEK structures under complex service conditions. In this paper, we studied the thermomechanical behaviors of PEEK with stretch-induced anisotropy and developed a constitutive model to incorporate the influence of the complex loading history along different loading axes. From the experiments, it was found that when it is stretched, PEEK demonstrates viscoplastic behaviors with reduced transversal modulus and yield stress in the subsequent loading, due to the initiation and growth of voids during stretching. The tensile sample also shows a necking behavior at relatively low temperature. To capture these behaviors, the constitutive model consists of two main parts. The undamaged part has three branches, one hyperelastic branch for the nonlinear elastic behavior, one viscoelastic branch for glass transition and relaxation in the amorphous domains, and one plastic branch for yielding and hardening in the crystalline domains. The damaged loose-chain part with history-dependent reduced relaxation time is used to capture the microscopic interface debonding between the crystallites and the amorphous domains. Compared with the experimental results, this model captures the stretch-induced volume expansion and the anisotropic evolution of material properties. This developed model is also able to capture the temperature-dependent necking phenomenon and the corresponding nominal stress-strain behaviors in the uniaxial tensile tests at different strain rates and temperatures. The developed model can be used to facilitate the design of PEEK-based structures under complicated loading conditions.

Research paper thumbnail of Development of a finite element method for light activated polymers

DEVELOPMENT OF A FINITE ELEMENT METHOD FOR LIGHT ACTIVATED POLYMERS by Craig Hamel Traditional Sh... more DEVELOPMENT OF A FINITE ELEMENT METHOD FOR LIGHT ACTIVATED POLYMERS by Craig Hamel Traditional Shape Memory Polymers (SMPs) belong to a class of smart materials which have shown promise for a wide range of applications. They are characterized by their ability to maintain a temporary deformed shape and return to an original parent permanent shape. The first SMPs developed responded to changes in temperature by exploiting the difference in modulus and chain mobility through the glass transition temperature. However, in recent years, new SMPs have been developed that respond to other stimuli besides temperature; these can include electricity, magnetism, changes in chemical concentration, and even light. In this thesis, we consider the photo-mechanical behavior of Light Activated Shape Memory Polymers (LASMPs), focusing on the numerical aspects. The mechanics behind LASMPS is rather abstract and cumbersome, even for simple geometries. In order to move these materials out of the lab and ...

Research paper thumbnail of Materials, design, and fabrication of shape programmable polymers

Multifunctional Materials, 2020

Programmable matter is a class of materials whose properties can be programmed to achieve a speci... more Programmable matter is a class of materials whose properties can be programmed to achieve a specific state upon a stimulus. Among them, shape programmable materials can change their shape, topographical architecture, or dimension triggered by external stimuli after material fabrication, finding broad applications in smart devices, soft robotics, actuators, reconfigurable metamaterials, and biomedical devices. Shape programmable polymers (SPPs) possess the advantages of low cost, the ability to achieve widely tunable stimuli response, and synthetic flexibility. Recent development has resulted in various new materials and fabrication techniques for SPPs. However, to better design and fabricate SPPs to satisfy specific applications, a more comprehensive understanding of SPPs is required. In this review, we provide state-of-the-art advances in materials, design methods, and fabrication techniques for SPPs. Based on different shape-shifting mechanisms, four most widely studied shape-shif...

Research paper thumbnail of The modelling and 3D printing of functionally graded foams for tunable crushing performance

Proposed for presentation at the Society of Engineering Sciences held September 28 - October 1, 2020 in Virtual., 2020

Research paper thumbnail of Evolutionary Algorithm‐Guided Voxel‐Encoding Printing of Functional Hard‐Magnetic Soft Active Materials

Advanced Intelligent Systems, 2020

Hard‐magnetic soft active materials (hmSAMs), embedding hard‐magnetic particles in soft polymeric... more Hard‐magnetic soft active materials (hmSAMs), embedding hard‐magnetic particles in soft polymeric matrices, have attracted a great number of research interests due to their fast‐transforming, untethered control, as well as excellent programmability. However, the current direct‐ink‐write (DIW) printing‐based fabrication of hmSAM parts and structures only permits programmable magnetic direction with a constant magnetic density. Also, the existing designs rely on the brute‐force approach to generate the assignment of magnetization direction distribution, which can only produce intuitional deformations. These two factors greatly limit the design space and the application potentials of hmSAMs. Herein, a “voxel‐encoding DIW printing” method to program both the magnetic density and direction distributions during hmSAM printing is introduced. The voxel‐encoding DIW printing is then integrated with an evolutionary algorithm (EA)‐based design strategy to achieve the desired magnetic actuation...

Research paper thumbnail of Integrating digital light processing with direct ink writing for hybrid 3D printing of functional structures and devices

Additive Manufacturing, 2021

Abstract As an emerging branch of additive manufacturing, multi-material 3D printing has drawn tr... more Abstract As an emerging branch of additive manufacturing, multi-material 3D printing has drawn tremendous attention as it offers more design flexibility that can combine materials with various mechanical, chemical, thermal-mechanical or electrical properties. However, low cost, high-speed, high-resolution, and versatile multi-material 3D printing methods are still lacking. In this paper, we present a new hybrid multi-material 3D printing system that consists of a top-down digital light processing (DLP) printing and a direct ink writing (DIW) printing to fabricate composite structures and unique devices in a single printing job. The vat photopolymerization-based DLP printing allows for high-speed and high-resolution printing of a material matrix with complex geometry. The material extrusion-based DIW printing enables the printing of functional material, including liquid crystal elastomers (LCEs) and conductive silver inks. With this hybrid 3D printing system, a wide choice of inks and resins can be used to print functional composites with tunable mechanical properties, enhanced interfacial bonding, and multifunctionality. We demonstrate that composites prototype, active soft robots, circuit-embedding architectures, and strain sensors can be successfully printed. This work provides a new and robust approach for 3D printing of multi-functional devices for broad applications in soft robotics, electronics, active metamaterials, and biomedical devices.

Research paper thumbnail of 4D Printing of Glass Fiber-Regulated Shape Shifting Structures with High Stiffness

ACS Applied Materials & Interfaces, 2020

Research paper thumbnail of Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing, 2021

Abstract Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently becam... more Abstract Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. Therefore, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

Research paper thumbnail of Room Temperature Quasi-static Characterization and Constitutive Model Parametrization of Flexible Polyurethane Foams of Different Densities Loaded in Different Orientations

Research paper thumbnail of Data Stewardship and Validation Methods for Mechanics of Materials at Sandia

Proposed for presentation at the Society of Engineering Science Annual Technical Meeting (SES 2022) in ,

Research paper thumbnail of Modeling Influences of Printing Defects on Mechanical Properties of Additively Manufactured Silicone Structures

Proposed for presentation at the The 8th European Congress on Computational Methods in Applied Sciences and Engineering held June 5-9, 2022 in Oslo, Norway

Research paper thumbnail of Modular machine learning-based elastoplasticity: Generalization in the context of limited data

Computer Methods in Applied Mechanics and Engineering

Research paper thumbnail of Calibrating constitutive models with full‐field data via physics informed neural networks

Strain

The calibration of solid constitutive models with full‐field experimental data is a long‐standing... more The calibration of solid constitutive models with full‐field experimental data is a long‐standing challenge, especially in materials that undergo large deformations. In this paper, we propose a physics‐informed deep‐learning framework for the discovery of hyperelastic constitutive model parameterizations given full‐field surface displacement data and global force‐displacement data. Contrary to the majority of recent literature in this field, we work with the weak form of the governing equations rather than the strong form to impose physical constraints upon the neural network predictions. The approach presented in this paper is computationally efficient, suitable for irregular geometric domains, and readily ingests displacement data without the need for interpolation onto a computational grid. A selection of canonical hyperelastic material models suitable for different material classes is considered including the Neo–Hookean, Gent, and Blatz–Ko constitutive models as exemplars for g...

Research paper thumbnail of Stabilized Hyperfoam Modeling of the General Plastics EF4003 (3 PCF) Flexible Foam

Research paper thumbnail of Mechanics of Materials Utilizing Machine Learning: Examples at Sandia National Laboratories

Proposed for presentation at the Society of Experimental Mechanics Annual Conference 2021 - Virtual held June 14-17, 2021 in Bethel, CT, United States.

Research paper thumbnail of Developing Intelligent Structures and Devices Using Novel Smart Materials and Multi-Material Multi-Method (m4) 3D Printing

Structural Health Monitoring 2019

The advent of additive manufacturing (AM), commonly known as 3D printing, has enabled the rapid f... more The advent of additive manufacturing (AM), commonly known as 3D printing, has enabled the rapid fabrication of complex structures previously unrealizable with traditional manufacturing techniques. Current approaches, however, are limited to single materials or single methodologies greatly limiting the potential scope of manufacturable products and components. Recently, our group has developed a novel multi-material multi-method (m4) 3D printer which integrates four AM technologies and two complementary technologies into one single platform. This allows for the fabrication of complex devices able to provide a wide range of functionalities ranging from stretchable electronics to self-sensing devices. To demonstrate these functionalities in the realm of printable electronics, multiple proof of concept printed circuit boards (PCBs) were fabricated which solve issues commonly encountered in 3D printed electronics such as high resolution or vertically integrated access (VIA) circuits. In addition, 3D printed smart structures able to respond to external stimulus, such as light or heat, have become highly desirable for applications ranging from soft robotics to implantable medical devices. Recently, our group has turned to liquid crystal elastomers (LCE), a class of active material able to generate large, rapid, and reversible actuations. Therefore, using the m4 3D printer, LCE-based smart structures requiring complex electronics were fabricated which can change their shape in response to an applied current. To demonstrate this, a smart, reconfigurable radio frequency (RF) antenna was 3D printed which can change its shape and operating frequency as a function of the applied current. These examples demonstrate the vast potential of m4 3D printing for creating smart, reconfigurable, and multi-functional structures.

Research paper thumbnail of Machine learning constitutive models of elastomeric foams

Computer Methods in Applied Mechanics and Engineering

Research paper thumbnail of Constitutive Modeling of Anisotropic Flexible Foams

Research paper thumbnail of An Isotropic Large Deformation Viscoplastic-Damage Model for Flexible Foams Across a Range of Relative Densities

Research paper thumbnail of The 3D printing and modeling of functionally graded Kelvin foams for controlling crushing performance

Extreme Mechanics Letters, 2021

Abstract Mechanical impact protection is an important consideration in many applications, ranging... more Abstract Mechanical impact protection is an important consideration in many applications, ranging from product transportation to sports. Cellular materials are typically used due to their desirable energy absorption properties and light weight. However, their large deformation and rate dependent responses (especially of polymer foams) are challenging to consider in design. Additionally, the use of foams with uniform properties, such as uniform density and uniform stiffness, often restricts the designed foams to only be suitable for a narrow range of mechanical impact conditions whereas real applications commonly face unpredictable situations. 3D printing offers fabrication flexibility and thus opens the door to create foams with tailored properties. In this work, we investigate the feasibility of using 3D printing for functionally graded foams (FGFs) that are optimal over a broad range of mechanical environments. The foams are fabricated by the recently developed grayscale digital light processing (g-DLP) method which can print parts with locally designed properties. These foams are tested under both drop test conditions and with slower displacement control. We also model the large deformation behavior of FGFs using finite element analysis in which we account for the different viscoelastic behaviors of the distinct grayscale regions. We then use the model to examine the impact mitigation capabilities of FGFs in different loading scenarios. Finally, we show how FGFs can be used to satisfy real-world design goals using the case study of a motorcycle helmet. In contrast to prior work, we investigate continuous, functionally graded foams of a single density that differ in their viscoelastic responses. This work provides further insight into the benefits of viscoelastic properties and modulus graded foams and presents a manufacturing approach that can be used to produce the next generation of flexible lattice foams as mechanical absorbers.

Research paper thumbnail of Thermomechanical behaviors of polyether ether ketone (PEEK) with stretch-induced anisotropy

Journal of the Mechanics and Physics of Solids, 2021

Abstract Polyether ether ketone (PEEK) is a semi-crystalline thermoplastic polymer with excellent... more Abstract Polyether ether ketone (PEEK) is a semi-crystalline thermoplastic polymer with excellent thermo-mechanical properties, bio-compatibility, corrosion resistance, and 3D printability. Due to these merits, it has wide applications in aeronautics and biomedical devices. However, PEEK's excellent thermo-mechanical properties come from its complicated crystalline domains, making it hard to predict and to design PEEK structures under complex service conditions. In this paper, we studied the thermomechanical behaviors of PEEK with stretch-induced anisotropy and developed a constitutive model to incorporate the influence of the complex loading history along different loading axes. From the experiments, it was found that when it is stretched, PEEK demonstrates viscoplastic behaviors with reduced transversal modulus and yield stress in the subsequent loading, due to the initiation and growth of voids during stretching. The tensile sample also shows a necking behavior at relatively low temperature. To capture these behaviors, the constitutive model consists of two main parts. The undamaged part has three branches, one hyperelastic branch for the nonlinear elastic behavior, one viscoelastic branch for glass transition and relaxation in the amorphous domains, and one plastic branch for yielding and hardening in the crystalline domains. The damaged loose-chain part with history-dependent reduced relaxation time is used to capture the microscopic interface debonding between the crystallites and the amorphous domains. Compared with the experimental results, this model captures the stretch-induced volume expansion and the anisotropic evolution of material properties. This developed model is also able to capture the temperature-dependent necking phenomenon and the corresponding nominal stress-strain behaviors in the uniaxial tensile tests at different strain rates and temperatures. The developed model can be used to facilitate the design of PEEK-based structures under complicated loading conditions.

Research paper thumbnail of Development of a finite element method for light activated polymers

DEVELOPMENT OF A FINITE ELEMENT METHOD FOR LIGHT ACTIVATED POLYMERS by Craig Hamel Traditional Sh... more DEVELOPMENT OF A FINITE ELEMENT METHOD FOR LIGHT ACTIVATED POLYMERS by Craig Hamel Traditional Shape Memory Polymers (SMPs) belong to a class of smart materials which have shown promise for a wide range of applications. They are characterized by their ability to maintain a temporary deformed shape and return to an original parent permanent shape. The first SMPs developed responded to changes in temperature by exploiting the difference in modulus and chain mobility through the glass transition temperature. However, in recent years, new SMPs have been developed that respond to other stimuli besides temperature; these can include electricity, magnetism, changes in chemical concentration, and even light. In this thesis, we consider the photo-mechanical behavior of Light Activated Shape Memory Polymers (LASMPs), focusing on the numerical aspects. The mechanics behind LASMPS is rather abstract and cumbersome, even for simple geometries. In order to move these materials out of the lab and ...

Research paper thumbnail of Materials, design, and fabrication of shape programmable polymers

Multifunctional Materials, 2020

Programmable matter is a class of materials whose properties can be programmed to achieve a speci... more Programmable matter is a class of materials whose properties can be programmed to achieve a specific state upon a stimulus. Among them, shape programmable materials can change their shape, topographical architecture, or dimension triggered by external stimuli after material fabrication, finding broad applications in smart devices, soft robotics, actuators, reconfigurable metamaterials, and biomedical devices. Shape programmable polymers (SPPs) possess the advantages of low cost, the ability to achieve widely tunable stimuli response, and synthetic flexibility. Recent development has resulted in various new materials and fabrication techniques for SPPs. However, to better design and fabricate SPPs to satisfy specific applications, a more comprehensive understanding of SPPs is required. In this review, we provide state-of-the-art advances in materials, design methods, and fabrication techniques for SPPs. Based on different shape-shifting mechanisms, four most widely studied shape-shif...

Research paper thumbnail of The modelling and 3D printing of functionally graded foams for tunable crushing performance

Proposed for presentation at the Society of Engineering Sciences held September 28 - October 1, 2020 in Virtual., 2020

Research paper thumbnail of Evolutionary Algorithm‐Guided Voxel‐Encoding Printing of Functional Hard‐Magnetic Soft Active Materials

Advanced Intelligent Systems, 2020

Hard‐magnetic soft active materials (hmSAMs), embedding hard‐magnetic particles in soft polymeric... more Hard‐magnetic soft active materials (hmSAMs), embedding hard‐magnetic particles in soft polymeric matrices, have attracted a great number of research interests due to their fast‐transforming, untethered control, as well as excellent programmability. However, the current direct‐ink‐write (DIW) printing‐based fabrication of hmSAM parts and structures only permits programmable magnetic direction with a constant magnetic density. Also, the existing designs rely on the brute‐force approach to generate the assignment of magnetization direction distribution, which can only produce intuitional deformations. These two factors greatly limit the design space and the application potentials of hmSAMs. Herein, a “voxel‐encoding DIW printing” method to program both the magnetic density and direction distributions during hmSAM printing is introduced. The voxel‐encoding DIW printing is then integrated with an evolutionary algorithm (EA)‐based design strategy to achieve the desired magnetic actuation...

Research paper thumbnail of Integrating digital light processing with direct ink writing for hybrid 3D printing of functional structures and devices

Additive Manufacturing, 2021

Abstract As an emerging branch of additive manufacturing, multi-material 3D printing has drawn tr... more Abstract As an emerging branch of additive manufacturing, multi-material 3D printing has drawn tremendous attention as it offers more design flexibility that can combine materials with various mechanical, chemical, thermal-mechanical or electrical properties. However, low cost, high-speed, high-resolution, and versatile multi-material 3D printing methods are still lacking. In this paper, we present a new hybrid multi-material 3D printing system that consists of a top-down digital light processing (DLP) printing and a direct ink writing (DIW) printing to fabricate composite structures and unique devices in a single printing job. The vat photopolymerization-based DLP printing allows for high-speed and high-resolution printing of a material matrix with complex geometry. The material extrusion-based DIW printing enables the printing of functional material, including liquid crystal elastomers (LCEs) and conductive silver inks. With this hybrid 3D printing system, a wide choice of inks and resins can be used to print functional composites with tunable mechanical properties, enhanced interfacial bonding, and multifunctionality. We demonstrate that composites prototype, active soft robots, circuit-embedding architectures, and strain sensors can be successfully printed. This work provides a new and robust approach for 3D printing of multi-functional devices for broad applications in soft robotics, electronics, active metamaterials, and biomedical devices.

Research paper thumbnail of 4D Printing of Glass Fiber-Regulated Shape Shifting Structures with High Stiffness

ACS Applied Materials & Interfaces, 2020

Research paper thumbnail of Utilizing computer vision and artificial intelligence algorithms to predict and design the mechanical compression response of direct ink write 3D printed foam replacement structures

Additive Manufacturing, 2021

Abstract Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently becam... more Abstract Additive Manufacturing (AM) of porous polymeric materials, such as foams, recently became a topic of intensive research due their unique combination of low density, impressive mechanical properties, and stress dissipation capabilities. Conventional methods for fabricating foams rely on complex and stochastic processes, making it challenging to achieve precise architectural control of structured porosity. In contrast, AM provides access to a wide range of printable materials, where precise spatial control over structured porosity can be modulated during the fabrication process enabling the production of foam replacement structures (FRS). Current approaches for designing FRS are based on intuitive understanding of their properties or an extensive number of finite element method (FEM) simulations. These approaches, however, are computationally expensive and time consuming. Therefore, in this work, we present a novel methodology for determining the mechanical compression response of direct ink write (DIW) 3D printed FRS using a simple cross-sectional image. By obtaining measurement data for a relatively small number of samples, an artificial neural network (ANN) was trained, and a computer vision algorithm was used to make inferences about foam compression characteristics from a single cross-sectional image. Finally, a genetic algorithm (GA) was used to solve the inverse design problem, generating the AM printing parameters that an engineer should use to achieve a desired compression response from a DIW printed FRS. The methods developed herein present an avenue for entirely autonomous design and analysis of additively manufactured structures using artificial intelligence.

Research paper thumbnail of Room Temperature Quasi-static Characterization and Constitutive Model Parametrization of Flexible Polyurethane Foams of Different Densities Loaded in Different Orientations