Projects

Mentor:  Dr. Ibrahim Karaman

Background: 
Additive manufacturing (AM), or 3D Printing, has achieved significant advancements since its inception in 1980s and led to a revolution in the manufacture of parts in traditional 3D space. Now it is witnessing further evolution through the introduction of 4D printing. The fourth "D" refers to the dimension of time, where the 3D printed part undergoes a controlled change in shape or properties in response to an external stimulus over time such as heat, stress, light, and moisture, among others. This approach is used most often in polymers, while 4-D printing of metallic materials is lagging behind. Now a few recent works, mostly from the Pl's group, have begun to explore 4-D printing of active metallic systems, in particular shape memory alloys (SMAs). In this project, we take advantage of the fact that the physical and functional responses of SMAs depend greatly on the processing schemes employed during AM (such as selection of energy source power and scan speed, layer density, and scan line spacing). By controlling the processing parameters, AM-fabricated SMAs can be tailored to achieve spatial and time­ dependent functional responses through the control of the local composition and microstructure.

Research Plan: 
The REU students will participate in the various stages of the research, including systematic studies of the effects of laser power, scan speed, and scan line spacing on the local composition and microstructure of various nickel-titanium SMAs and new NiCoMnln magnetic SMAs using two different AM techniques: laser powder bed fusion and direct laser energy deposition. The REU students will also be involved in conducting parametric post-AM heat treatment studies, determining magnetic and mechanical properties using various characterization instruments, determining local compositions using simple spectroscopy techniques, and identification of microstructures using optical and electron microscopy with the help of graduate students. Students will have the opportunity to conduct magneto-thermo-mechanical characterization of samples that another REU student fabricated to analyze the effect of AM parameters on the physical and mechanical properties under multiple fields (mechanical load, magnetic field, and temperature) using the state-of-the-art experimental systems available at Texas A&M.

Mentor: Dr. Raymundo Arroyave

Background:
Most significant advances in energy technologies have been enabled by the discovery of new materials, which have increased the overall efficiency of energy usage (e.g., new high-temperature alloys ^{39, 40}), expanded the renewable energy inventory (e.g., more efficient photovoltaic materials), facilitated the storage of energy (e.g., battery materials^{41, 42}), and allowed the recovery of energy that otherwise would be wasted (e.g. thermoelectric materials^{43, 44}). Novel multifunctional materials enable the conversion of various energy forms (magnetic, mechanical, thermal, and electrical) through couplings between different kinds of energy forms and have the potential to significantly outperform conventional conversion technologies and facilitate technological breakthroughs that will contribute to our energy independence. However, the multi-functional materials space is highly complex, and the discovery of novel materials needs to be accelerated in order to facilitate the development of transformative technologies. Fortunately, recent advances in materials genomics⁴⁵, Artificial Intelligence^{46, 47} (AI) and data science^{48, 49} make possible the discovery of relationships between materials features and materials performance through data-enabled approaches that can be leveraged to accelerate the discovery of materials with optimal functionality. In this REU, the student will learn and acquire the fundamental skills necessary to carry out AI-enabled materials discovery and will apply such skills to the investigation of novel functional materials.

Research Plan:
REU students will be involved in the development of machine learning (ML) approaches to build predictive models connecting materials features and performance. They will be trained in the basic aspects of the physics of multi-functional materials (weeks 1,2). They will also be trained in data visualization, data analysis and ML workflows through the Orange platform⁵⁰ (week 2,3). Students will be capturing data sets of the relevant materials to be investigated and mentored by the graduate student in the curation of materials data, which will be stored in the Materials Data Curation System⁵¹ (weeks 4,5). At the same time, they will be trained in the use of scripting programming languages (such as Python⁵²) to automate many of the pre- and post-processing of files necessary to run calculations. Using Orange, the REU students will explore the use of different supervised and unsupervised ML models and evaluate the models through rigorous informatics evaluation techniques (weeks 6-10). The students will gain a deep understanding of material science and proficiency in data analysis, ML, and Python programming, backed by consistent mentorship and valuable networking opportunities.

Mentor: Dr. Yuxuan Cosmi Lin

Background:
Next generation computing and artificial intelligent technologies calls for out-of-box design of semiconductor materials and device architectures with non-traditional device characteristics that can bring computing and signal processing to the analog domain, closer to the sensor level. Such a new computing scheme, called near-sensor computing or in-sensor computing, is fundamentally advantageous over the traditional hierarchical von Neumann computing architecture in terms of novel functionality, energy efficiency and scalability. Two-dimensional (2D) functional materials have emerged recently, offering novel multi-functionalities in different physical domains. Samples include semi metallic graphene, insulating, hBN, semiconducting MoS₂, and WSe₂, as well as ferroelectric CuInP₂S_6. Because of their atomically thin nature, it is possible to engineer 2D material heterostructures, with extra degree of freedom and exceptional controllability at the limit of atomic scale for the functionalities that are required in the application of in-sensor computing. In particular, Lin has proposed and implemented two kinds of 2D material heterostructures with tunable optoelectronic properties for spectral and imaging sensing and processing: (1) 2D semiconductors with wide-range bandgap tuning induced by electrochemical gating; (2) graphene/hBN/graphene heterostructures with electrically tunable photo-assisted tunneling. Based on the proposed structures, the spectral photocurrent response can be widely tuned simply by electrical signals, and signal processing functionalities both in the 2D imaging domain and in the spectral domain can be programmed directly onto these tunable photodetectors (Figure).

Research Plan:
This project will focus on the design of vertical heterostructures based on functional 2D materials for advanced optoelectronic functionalities that can enable in-sensor computing technologies. The students will work on the theoretical design and experimental verification of the in-sensor computing devices. Students will get exposed to both fundamental knowledge and the cutting-edge research activities in emerging semiconductor technologies. The proposed in-sensor computing scheme will transform the future computing and intelligent sensing systems in very different form factors and enable more powerful hardware of artificial intelligence with energy consumption, orders of magnitude smaller than the existing computing architecture. The expected tasks for the REU students will be: (1) Design the 2D semiconductor heterostructures with desired optoelectronic functionalities. (2) Use computer-aided design tool to simulate the proposed device characteristics. (3) Based on the simulated device characteristics, design the image and spectral processing algorithms that can harness the unique performance of the 2D semiconductor heterostructures. (4) Verify the design and theoretical findings experimentally.

Mentor: Dr. Patrick Shamberger

Background:
Thermal energy storage (TES) materials offer a compact solution to absorb heat during periods of high heat generation, increasing efficiency and minimizing temperature rise of transient pulsed power systems.  However, these systems are limited by their inflexibility, in that they only absorb heat over a narrow temperature range.  Tunable TES materials introduce an additional vector (e.g., pressure) to control the temperature at which thermal energy is stored.

Research Plan:
The overarching objective of this project is to develop reversible endothermic condensed phase transitions (solid/solid or solid/liquid) that have dynamically tunable critical transition temperatures, as the basis for responsive and tunable thermal energy storage media. This task will focus primarily on understanding intrinsic chemical degrees of control on the kinetics of the reversible phase transformation and the dynamic tuning of the material. We will focus on plastic crystals that are known to have relatively large DH and dT_cr/dP as model systems and will focus on the effect of: 1) molecular structure, 2) crystal structures of parent and daughter phases, 3) molecule size, shape, and symmetry, and 4) intramolecular bonding. The anticipated outcome of these tasks is an approach to design tunable thermal energy storage materials at the molecular level, as well as a validation of their utility as energy storage media. These materials have the potential to improve efficiency of a variety of transient systems from electric cars and airplanes to HVAC and building climate control systems.  Students will measure the phase transformation kinetics of different plastic crystal molecules using calorimetry, polarized optical light microscopy, and custom thermal cycling apparatuses.  These data will be fit to kinetic models, which will be interpreted using crystallographic information (and specifically, the transformation strain between the parent and daughter phase), and molecular structural information. This information will be correlated with kinetic parameters and used to develop techniques to increase the reversibility of the plastic crystal transformations.

Mentors: Dr. D.C. Lagoudas, Dr. J. Lutkenhaus, T. Zhou

Background:
Structural energy and power systems offer both mechanical and electrochemical performance in a single multifunctional platform. They potentially offer a reduction in mass and/or volume for aircraft, satellites, and ground transportation. However, there is a natural tradeoff between mechanical and energy storage properties, making it difficult to synergistically optimize both. Common approaches center on modifying battery electrodes or electrolytes with stiff fillers such as carbon or glass fibers. This type of reinforcement leads to lower energy and power density. Here, we explore a different battery mechanism with redox-active polymers in a dual-ion battery to increase the electrochemical performance of carbon fiber-based batteries. A polymer-based dual-ion battery shortens the diffusion path, which leads to a higher power density. Our earlier work has shown excellent results for power density increase⁵³. This faster energy transport is crucial for space applications where the temperature is low, and diffusion is slow. Degradation due to electrochemical degradation, internal stress development, and external mechanical loading remain unexplored.

Research Plan:
The students’ summer activities will center on electrode fabrication, pouch cell assembly, and mechanical and electrochemical characterization. The mentoring team will consist of a graduate student, a post-doc, and the PIs. At the beginning of the summer, students will synthesize carbon fiber-reinforced polymer-based batteries. Each of these fabrications are performed in the Lutkenhaus lab on a regular basis. In early to mid-summer, students will perform separate electrochemical (capacity, energy, power) and mechanical (three-point bending) characterization on these materials (fi. They will then perform in-situ energy density and power density characterization at different deflections. In mid- to late-summer, students will develop a micromechanics model to capture the experimental observation and explain the mechanism of the electro-chemo-mechanical coupling on structural battery degradation. The students will develop a test matrix to answer the following questions: How do mechanical deformation and degradation change electrochemical performances? How do these behaviors change at lower temperatures? How can we predict and improve the lifetime of a structural battery for low-temperature applications?

Mentor: Dr. Kaiwen Hsiao

Background:
There is a critical need to develop sustainable separation methods to meet the global stress for freshwater supplies. Membrane-based water purification methods are desirable separation technologies due to their higher energy efficiency compared to thermal approaches. However, current membrane fabrication methods are largely based on empirical processes such as phase-inversion technologies that inevitably introduce pore sizes polydispersity and suboptimal performances, such as selectivity-permeability trade-offs, high fouling potential, and poor mechanical properties. It is therefore highly desirable to develop a scalable and novel membrane fabrication method that can form multiscale pore sizes ranging from micrometer to nanometer length scales with high-uniformity and free-form membrane surface pattern designs to minimize biofouling.

Research Plan:
The students’ summer research will center on polymer materials preparations, high-resolution and high-speed additive manufacturing of these membranes, study the material morphology and mechanical properties, and visualize molecular transport of fluorescence biomolecules through the membrane. The mentoring team will consist of a graduate student and Hsiao. The students will learn how to prepare polymer electrolytes, learn how to vary the photopolymerization processes to control the nanostructure formation, and explore visualization of labeled biomolecules transporting through nano- and micron- scale pores. Key research questions the students will probe include: 1) How do photopolymerization kinetics affect the assembly and formation of nano-transport pathways? 2) How are the mechanical properties related to membranes with different nanoscale morphology? 3) How do size and distribution of the pores affect transport of biomolecules?

Mentor:  Dr. Emily Pentzer

Background:
The Pentzer lab develops new particle surfactants for the stabilization of various liquid-liquid interfaces, driving forward the ability to stabilize, e.g., water-in-oil, oil-in-water, oil-in-oil, ionic liquid-in-oil, salt hydrate-in-oil emulsions⁵⁷. These phases separated systems are then used to make a variety of composite materials with multifunctional properties. To date, applications have included carbon capture^{58, 59}, electrochemical energy storage⁶⁰, thermal energy management^{61, 62}, and imaging. The development of new particle surfactants gives access to different compositions but has thus far relied on a guess-and-check approach. The proposed research aims to overcome this current limitation by establishing relationships between particle wettability, liquid-liquid interfacial tension, physicochemical properties of the liquids, and energy input on the formation and stability of the emulsions. Students in this research project will gain skills in colloidal synthesis, interfacial characterization, emulsification, and the collection, organization, and dissemination of data and research results. Emulsions are a critical component of multiple facets of modern life- from food to cosmetics to drilling oil. They are used to template the formation of composite and multi-functional materials, but can only be used as such provided, they can be readily accessed and are stable. This work will address the fundamental question of what factors dictate emulsion formation and stability. 

Research Plan:
The REU student in the Pentzer lab will first functionalize silica particles by silanization following a well-established procedure. Different pendant functional groups will be appended to the same sided silica particles, and the composition of the particles will be characterized, as well as wettability and what solvents the modified particles are dispersible in. Then, the student will identify potential emulsion systems of interest, with the solvents the modified particles are dispersible in dictating the expected continuous phase of an emulsion that could be formed. The wettability of the particles will be established by water contact angle, then the interfacial tension of two liquids will be measured by pendant drop tensiometery, both in the presence and absence of the particles. Finally, the student will prepare a matrix of emulsion systems and monitor formation and stability using optical microscopy techniques. The student will then identify any relationship between the physical properties of the system and its components and the ability to form stable emulsions. Tasks for the REU student are: (1) Modifying silica particles for varied wettability, (2) Measuring physical properties of particles and liquid-liquid combinations. (3)  Creating an emulsion matrix to determine conditions for stability.

Mentor: Dr. Svetlana Sukhishvili

Background: 
This project will focus on achieving multiple and controlled shape reconfiguration in dynamic covalent polymer networks based on furan-maleimide Diels-Alder (DA) reactions. DA polymer (DAP) networks are re-processable due to the presence of dynamic, temperature-activated bonds and have the potential of replacing traditional thermosets. DAP-based materials have widely tunable mechanical properties (Young’s modulus E from several MPa to several GPa) and exhibit a novel route of materials’ shape morphing above the materials’ glass transitions temperature via the mechanism of network plasticity with no creep, all in the solid state (see the figure)^54-56. The propensity of DAP materials to solid state reconfiguration is strongly determined by the conversion degree and stereochemistry of DA bonds formed during network synthesis. Thus, it is essential to establish the impact of polymer chain rigidity and network processing conditions (temperature, time, solvent-free vs. solution processing) on the DA bond formation and material reconfigurability that are essential for future applications of these materials as shape-adaptable, re-processable materials for consumer market and defense sectors, including soft robotics.

Research Plan: 
The REU students will work with a graduate student to develop, construct, and characterize novel DAP networks constructed using epoxy monomers that were previously studied in our group, as well as other monomers yielding polymers with different chain rigidity. By strategically varying the network processing temperature, time, and solvent conditions, the REU student will (a) construct several networks using modifications of the synthesis technique available in the Sukhishvili lab (Task 1); (b) study degree of DA conversion using FTIR and ¹H NMR techniques (Task 2); (c) correlate the data with the fraction of endo DA attachments (determined by differential scanning calorimetry) and material’s shape (Task 3).

Mentor: Dr. Miladin Radovic

Background:
MXenes are a versatile class of multifunctional two-dimensional (2D) ceramic nanosheets with diverse compositions, and tailorability for different applications including energy storage, catalysis, electromagnetic interference shielding, sensors, composites, and batteries ^{66, 73}. However, large-scale production faces challenges due to synthesis difficulties and MXene's chemical instability. Recently, we have demonstrated that challenges in achieving a scalable synthesis of high-quality MXenes stem from the intricate process of selectively etching the A layer and the subsequent overarching of MX layers, as illustrated by our core-shell model in Figure 5.

Research Plan:
Our core-shell model highlights the critical role of specific etching parameters, including the choice of etchants, their concentrations, etching temperature, particle sizes of the parent MAX phase, and the amount of etchants applied ⁷⁴. These factors significantly influence the rates of A-layer etching and over-etching of MX layers, ultimately impacting the yield of MXenes. Furthermore, our recent findings have introduced safer alternatives to traditional etchants, such as (i) a mixture of organic quaternary fluoride salts with milder acids ⁷⁴ and (ii) molten fluoride salts ^{75, 76}. These discoveries open up new possibilities for the scalable production of high-quality multifunctional MXenes using safer etching methods. The UG student will work closely with graduate students and our industrial partner engaged on the recently awarded NSF grant #2240554 entitled “GOALI: Manufacturing of Two-Dimensional MXene Nanosheets by Salt Solution Etching and Their Solution-based Layer-by-Layer Assembly into Heterostructures”. REU student’s major research tasks will include conduct XPS analysis of MXenes prepared using different etching conditions and correlate distribution on terminal groups (such as –O, -OH, -F, -Cl) to the etching conditions; conduct AFM, DLS and XRD measurements on MXenes prepared using different etching conditions to establish relationship between size, thickens and  interlaminar spacing of MXenes and etching conditions; Carry out SEM and EDS to characterize morphology and composition of different MXenes.