Scholarly Works, Mechanical Engineering

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Research articles, presentations, and other scholarship

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Analytical Investigation of Electromechanical Hierarchical Metamaterials for Vibration Attenuation and Energy Harvesting
Mebrat, Ashenafi Abebe; LeGrande, Joshua; Barry, Oumar (MDPI, 2025-03-21)
This work presents a theoretical study of outward and inward hierarchical metamaterials. Hierarchically configured multiple electromechanical resonators with shunt circuits are implemented, maintaining the same overall mass as that of a comparable single resonator metamaterial. The governing equations of motion for the outward and inward hierarchical configurations are derived. Dispersion relations are determined for each configuration with varying system parameters to identify key design parameters and assess their impact on the system’s dynamic behavior. Furthermore, outer mass displacement transmissibility and normalized total power output of finite chain hierarchical metamaterials are compared to observe vibration attenuation and energy harvesting capacity. The results reveal that the band structure of the hierarchical electromechanical metamaterials depends on the configuration type, the resonator masses, the electromechanical coupling coefficient, and the resistance of the shunt circuit. The first-order hierarchy offers a greater total band gap width, increased bandwidth, and greater flexibility in tuning the band structure. Finite chain transmissibility analysis demonstrates that, compared to the baseline performance of the zero-order hierarchy, the first-order hierarchy exhibits superior abilities in vibration attenuation and energy harvesting for the same total mass. The ideal design requires careful consideration of the resonator masses and their configuration, electromechanical coupling coefficient, and resistance of the shunt circuits. This theoretical work provides a foundation for designing lightweight hierarchical metamaterials for simultaneous vibration attenuation and energy harvesting.
Investigating the effect of heterogeneities across the electrode|multiphase polymer electrolyte interfaces in high-potential lithium batteries
Min, Jungki; Bak, Seong-Min; Zhang, Yuxin; Yuan, Mingyu; Pietra, Nicholas F.; Russell, Joshua A.; Deng, Zhifei; Xia, Dawei; Tao, Lei; Du, Yonghua; Xiong, Hui; Li, Ling; Madsen, Louis A.; Lin, Feng (Nature Portfolio, 2025-04-01)
Polymer electrolytes hold great promise for safe and high-energy batteries comprising solid or semi-solid electrolytes. Multiphase polymer electrolytes, consisting of mobile and rigid phases, exhibit fast ion conduction and desired mechanical properties. However, fundamental challenges exist in understanding and regulating interactions at the electrode|electrolyte interface, especially when using high-potential layered oxide active materials at the positive electrode. Here we demonstrate that depletion of the mobile conductive phase at the interface contributes to battery performance degradation. Molecular ionic composite electrolytes, composed of a rigid-rod ionic polymer with nanometric mobile cations and anions, serve as a multiphase platform to investigate the evolution of ion conductive domains at the interface. Chemical and structural characterizations enable the visualization of concentration heterogeneity and spatially resolve the interfacial chemical states over a statistically significant field of view for buried interfaces. We report that concentration and chemical heterogeneities prevail at electrode|electrolyte interfaces, leading to phase separation in polymer electrolytes. Understanding the hidden roles of interfacial chemomechanics in polymer electrolytes enables us to design an interphase tailoring strategy based on electrolyte additives to mitigate the interfacial heterogeneity and improve battery performance.
Physical stimuli-responsive DNA hydrogels: design, fabrication strategies, and biomedical applications
Acharya, Rumi; Dutta, Sayan D.; Mallik, Hemadri; Patil, Tejal V.; Ganguly, Keya; Randhawa, Aayushi; Kim, Hojin; Lee, Jieun; Park, Hyeonseo; Mo, Changyeun; Lim, Ki-Taek (2025-03-22)
Physical stimuli-responsive DNA hydrogels hold immense potential for tissue engineering due to their inherent biocompatibility, tunable properties, and capacity to replicate the mechanical environment of natural tissue, making physical stimuli-responsive DNA hydrogels a promising candidate for tissue engineering. These hydrogels can be tailored to respond to specific physical triggers such as temperature, light, magnetic fields, ultrasound, mechanical force, and electrical stimuli, allowing precise control over their behavior. By mimicking the extracellular matrix (ECM), DNA hydrogels provide structural support, biomechanical cues, and cell signaling essential for tissue regeneration. This article explores various physical stimuli and their incorporation into DNA hydrogels, including DNA self-assembly and hybrid DNA hydrogel methods. The aim is to demonstrate how DNA hydrogels, in conjunction with other biomolecules and the ECM environment, generate dynamic scaffolds that respond to physical stimuli to facilitate tissue regeneration. We investigate the most recent developments in cancer therapies, including injectable DNA hydrogel for bone regeneration, personalized scaffolds, and dynamic culture models for drug discovery. The study concludes by delineating the remaining obstacles and potential future orientations in the optimization of DNA hydrogel design for the regeneration and reconstruction of tissue. It also addresses strategies for surmounting current challenges and incorporating more sophisticated technologies, thereby facilitating the clinical translation of these innovative hydrogels.
Effect of processing parameters and thermal history on microstructure evolution and functional properties in laser powder bed fusion of 316L
Deshmukh, Kaustubh; Riensche, Alex; Bevans, Ben; Lane, Ryan J.; Snyder, Kyle; Halliday, Harold (Scott); Williams, Christopher B.; Mirzaeifar, Reza; Rao, Prahalada (Elsevier, 2024-07-03)
In this paper, we explain and quantify the causal effect of processing parameters and part-scale thermal history on the evolution of microstructure and mechanical properties in the laser powder bed fusion additive manufacturing of Stainless Steel 316L components. While previous works have correlated the processing parameters to flaw formation, microstructures evolved, and properties, a missing link is the understanding of the effect of thermal history. Accordingly, tensile test coupons were manufactured under varying processing conditions, and their microstructure-related attributes, e.g., grain morphology, size and texture; porosity; and microhardness were characterized. Additionally, the yield and tensile strengths of the samples were measured using digital image correlation. An experimentally validated computational model was used to predict the thermal history of each sample. The temperature gradients and sub-surface cooling rates ascertained from the model predictions were correlated with the experimentally characterized microstructure and mechanical properties. By elucidating the fundamental process-thermal-structure–property relationship, this work establishes the foundation for future physics-based prediction of microstructure and functional properties in laser powder bed fusion.
DC vs AC Electrokinetics-Driven Nanoplasmonic Raman Monitoring of Charged Analyte Molecules in Ionic Solutions
Xiao, Chuan; Wang, Xin; Zhao, Yuming; Zhang, Hongwei; Song, Junyeob; Vikesland, Peter J.; Qiao, Rui; Zhou, Wei (American Chemical Society, 2024-08-31)
Electrokinetic surface-enhanced Raman spectroscopy (EK-SERS) is an emerging high-order analytical technique that combines the plasmonic sensitivity of SERS with the electrode interfacial molecular control of electrokinetics. However, previous EK-SERS works primarily focused on non-Faradaic direct current (DC) operation, limiting the understanding of the underlying mechanisms. Additionally, developing reliable EK-SERS devices with electrically connected plasmonic hotspots remains challenging for achieving high sensitivity and reproducibility in EK-SERS measurements. In this study, we investigated the use of two-tier nanolaminate nano-optoelectrode arrays (NL-NOEAs) for DC and alternating current (AC) EK-SERS measurements of charged analyte molecules in ionic solutions. The NL-NOEAs consist of Au/Ag/Au multilayered plasmonic nanostructures on conductive nanocomposite nanopillar arrays (NC-NPAs). We demonstrate that the NL-NOEAs exhibit high SERS enhancement factors (EFs) of ∼106 and can be used to modulate the concentration and orientation of Rhodamine 6G (R6G) molecules at the electrode surface by applying DC and AC voltages. We also performed numerical simulations to investigate the ion and R6G dynamics near the electrode surface under DC and AC voltage modulation. Our results show that AC EK-SERS can provide additional insights into the dynamics of molecular transport and adsorption processes compared to DC EK-SERS. This study demonstrates the potential of NL-NOEAs for developing high-performance EK-SERS sensors for a wide range of applications.
A Novel Fission-Matrix Based Radial Boundary Correction Methodology and its Implementation into the RAPID Code System
Al Hajj, Walid; Haghighat, Alireza (EDP Sciences, 2024-10-15)
The RAPID code system utilizes a novel combined fission matrix methodology to rapidly solve the whole-core eigenvalue problem. To represent axial and radial reflector regions, the fission density distribution in the boundary assemblies, a fission density correction factor methodology was devised and demonstrated. Although, accurate results were achieved, because of the need for a full core Monte Carlo calculation, this technique requires significant computing resources. To address this issue, this paper introduces a novel FM based methodology, which achieves accurate results, however at very small computing expense. The methodology has been implemented into the RAPID code system, and successfully demonstrated for the Watts Bar whole core OECD/NEA
Whole Core Reactor High Fidelity Calculations using the RAPID Code System
Stroh, Brian; Haghighat, Alireza (2025-07-22)
Nuclear reactors require routine modeling for determining safety margins, core configurations, and other optimizations. These models are typically simulated with a Monte Carlo based code, or a deterministic code based on the Linear Boltzmann Equation (LBE) or transport equation. The problem with these solutions arises when high-fidelity results are necessary. Monte Carlo based codes are able to obtain high fidelity results, but they require a significant amount of computational resources (e.g., processors, memory) and time. The deterministic codes can also produce high fidelity results, but due to the discretization of variables the resources required can exceed that of Monte Carlo based codes. The RAPID code has been developed based on the Multistage Response function Transport (MRT) methodology. In this methodology, a problem is partitioned into stages or sub-problems that can be simulated using response functions or coefficients. By pre-calculating these functions/coefficients as a function of different parameters using a Monte Carlo code, then solutions are obtained using a liner system of equations in seconds or minutes on one computer core. The RAPID code system has been verified computationally and validated using benchmark problems, and experimentally using the Jo˘zef Stefan Institute (JSI) TRIGA reactor in Slovenia.
Fuel Resistance of Firefighting Surfactant Foam Formulations
Ateş, Ayşenur; Qiao, Rui; Lattimer, Brian Y. (MDPI, 2025-01-25)
Aqueous film-forming foam (AFFF) is widely recognized for its excellent fire-extinguishing capabilities, yet the specific roles of its components remain insufficiently understood. AFFF typically consists of fluorocarbon and hydrocarbon surfactants, as well as organic solvents such as diethylene glycol butyl ether (DGBE), which can significantly influence foam performance. This study investigates the effects of surfactant mixtures and the DGBE additive on foam stability and fuel resistance at room temperature and ambient humidity. Static foam ignition experiments were conducted to assess fuel transport through foams using various hydrocarbon fuels, including n-octane, iso-octane, n-heptane, methylcyclohexane, methylcyclopentane, and a mixture of 25% trimethylbenzene with 75% n-heptane. Methylcyclopentane, with its higher vapor pressure and solubility, led to the shortest ignition times, indicating faster fuel transport. The addition of DGBE increased ignition times by a factor of 1.2 to 3.7 for individual surfactants, while the Capstone+Glucopon mixture improved ignition times by a factor of 2.4 to 5.5 compared to the individual surfactants. Further enhancement was observed with Capstone+Glucopon+DGBE, increasing ignition times by a factor of 3 to 7.3 compared to the individual surfactants. Additionally, combining DGBE with surfactant mixtures reduced fuel concentration in the bulk solution by over 60% compared to individual surfactants, significantly enhancing fuel resistance. Interface experiments showed that fuel presence, particularly methylcyclopentane and n-octane, altered the foam structure and accelerated drainage at the foam/fuel interface, impacting foam stability and fuel transport. These findings demonstrate that surfactant mixtures and DGBE-enhanced formulations substantially improve foam stability and fuel resistance.
Limits of dropwise condensation heat transfer on dry nonwetting surfaces
Hatte, Sandeep; Pitchumani, Ranga (Cell Press, 2024-09-27)
Surface condensation is ubiquitous in applications such as power generation and water harvesting. Nonwetting surfaces have been studied extensively for their dropwise condensation potential with reports of dramatic improvements relative to the classical Nusselt equation for film-wise condensation that has long served as a reference theoretical lower bound on the condensation heat transfer coefficient. However, a theoretical upper bound on the maximum possible condensation heat transfer over a given surface is not available. Considering actual surface topographies as fractal surfaces, we present theoretical upper bounds for gravity-driven and jumping droplet condensation modes in a unified manner. Experimental data on steam condensation from this study as well as the literature on dry nonwetting surfaces are compared to the bounds to identify the opportunity gap to the theoretical maximum. Solid-infused surfaces, introduced recently by the authors, is shown to fall in this opportunity space, closer to the upper bound.
Microfluidic-based systems for the management of diabetes
Staples, Anne E.; Zhang, Shuyu (Springer, 2024-03-20)
Diabetes currently affects approximately 500 million people worldwide and is one of the most common causes of mortality in the United States. To diagnose and monitor diabetes, finger-prick blood glucose testing has long been used as the clinical gold standard. For diabetes treatment, insulin is typically delivered subcutaneously through cannula-based syringes, pens, or pumps in almost all type 1 diabetic (T1D) patients and some type 2 diabetic (T2D) patients. These painful, invasive approaches can cause non-adherence to glucose testing and insulin therapy. To address these problems, researchers have developed miniaturized blood glucose testing devices as well as microfluidic platforms for non-invasive glucose testing through other body fluids. In addition, glycated hemoglobin (HbA1c), insulin levels, and cellular biomechanics-related metrics have also been considered for microfluidic-based diabetes diagnosis. For the treatment of diabetes, insulin has been delivered transdermally through microdevices, mostly through microneedle array-based, minimally invasive injections. Researchers have also developed microfluidic platforms for oral, intraperitoneal, and inhalation-based delivery of insulin. For T2D patients, metformin, glucagon-like peptide 1 (GLP-1), and GLP-1 receptor agonists have also been delivered using microfluidic technologies. Thus far, clinical studies have been widely performed on microfluidic-based diabetes monitoring, especially glucose sensing, yet technologies for the delivery of insulin and other drugs to diabetic patients with microfluidics are still mostly in the preclinical stage. This article provides a concise review of the role of microfluidic devices in the diagnosis and monitoring of diabetes, as well as the delivery of pharmaceuticals to treat diabetes using microfluidic technologies in the recent literature. Graphical abstract: (Figure presented.)
Left-right tympanal size asymmetry in the parasitoid fly Ormia ochracea
Mikel-Stites, Max R.; Marek, Paul E.; Hellier, Madeleine E.; Staples, Anne E. (2024-08-02)
Ormia ochracea is a parasitoid fly notable for its impressive hearing abilities relative to its small size. Here, we use it as a model organism to investigate if minor size differences in paired sensory organs may be beneficial or neutral to an organism's perception abilities. We took high-resolution images of tympanal organs from 21 O. ochracea specimens and found a statistically significant surface area asymmetry (up to 6.88%) between the left and right membranes. Numerical experiments indicated that peak values of key sound localization variables increased with increasing tympanal asymmetry, which may explain features of the limited available physiological data.
Computing the multimodal stochastic dynamics of a nanobeam in a viscous fluid
Barbish, John; Paul, Mark R. (AIP Publishing, 2024-12-16)
The stochastic dynamics of small elastic objects in fluid are central to many important and emerging technologies. It is now possible to measure and use the higher modes of motion of elastic structures when driven by Brownian motion alone. Although theoretical descriptions exist for idealized conditions, computing the stochastic multimodal dynamics for the complex conditions of an experiment is very challenging. We show that this is possible using deterministic finite-element calculations with the fluctuation dissipation theorem by exploring the multimodal stochastic dynamics of a doubly clamped nanobeam. We use a very general, and flexible, finite-element computational approach to quantify the stochastic dynamics of multiple modes simultaneously using only a single deterministic simulation. We include the experimentally relevant features of an intrinsic tension in the beam and the influence of a nearby rigid boundary on the dynamics through viscous fluid interactions. We quantify the stochastic dynamics of the first 11 flexural modes of the beam when immersed in air or water. We compare the numerical results with theory, where possible, and find excellent agreement. We quantify the limitations of the computational approach and describe its range of applicability. These results pave the way for computational studies of the stochastic dynamics of complex 3D elastic structures in a viscous fluid where theoretical descriptions are not available.
A Novel Telelocomotion Framework with CoM Estimation for Scalable Locomotion on Humanoid Robots
Chi, An-Chi; Li, Junheng; Park, Jungsoo; Kolt, Omar; Beiter, Ben; Leonessa, Alexander; Nguyen, Quan; Akbari Hamed, Kaveh (2024-09-01)
Teleoperated humanoid robot systems have made substantial advancements in recent years, offering a physical avatar that harnesses human skills and decision-making while safeguarding users from hazardous environments. However, current telelocomotion interfaces often fail to accurately represent the robot’s environment, limiting the user’s ability to effectively navigate the robot through unstructured terrain. This paper presents an initial telelocomotion framework that integrates the ForceBot locomotion interface with the smallsized humanoid robot, HECTOR V2. The framework utilizes ForceBot to simulate walking motion and estimate the user’s Center of Mass (CoM) trajectory, which serves as a tracking reference for the robot. On the robot side, a model predictive control (MPC) approach, based on a reduced-order single rigid body model, is employed to track the user’s scaled trajectory. We present experimental results on ForceBot’s CoM estimation and the robot’s tracking performance, demonstrating the feasibility of this approach.
H₂- and H_∞-Optimal Model Predictive Controllers for Robust Legged Locomotion
Pandala, Abhishek; Ames, Aaron D.; Hamed, Kaveh Akbari (IEEE, 2024-05-31)
This paper formally develops robust optimal predictive control solutions that can accommodate disturbances and stabilize periodic legged locomotion. To this end, we build upon existing optimization-based control paradigms, particularly quadratic programming (QP)-based model predictive controllers (MPCs). We present conditions under which the closed-loop reduced-order systems (i.e., template models) with MPC have the continuous differentiability property on an open neighborhood of gaits. We then linearize the resulting discrete-time, closed-loop nonlinear template system around the gait to obtain a linear time-varying (LTV) system. This periodic LTV system is further transformed into a linear system with a constant state-transition matrix using discrete-time Floquet transform. The system is then analyzed to accommodate parametric uncertainties and to synthesize robust optimal H2 and H∞ feedback controllers via linear matrix inequalities (LMIs). The paper then extends the theoretical results to the single rigid body (SRB) template dynamics and numerically verifies them. The proposed robust optimal predictive controllers are used in a layered control structure, where the optimal reduced-order trajectories are provided to a full-order nonlinear whole-body controller (WBC) for tracking at the low level. The developed layered controllers are numerically and experimentally validated for the robust locomotion of the A1 quadrupedal robot subject to various disturbances and uneven terrains. Our numerical results suggest that the H2-and H∞-optimal MPC controllers significantly improve the robust stability of the gaits compared to the normal MPC.
DynamicPrint: A physics-guided feedforward model predictive process control approach for defect mitigation in laser powder bed fusion additive manufacturing
Riensche, Alex; Bevans, Benjamin; Carrington Jr, Antonio; Deshmukh, Kaustubh; Shephard, Kamden; Sions, John; Synder, Kyle; Plotnikov, Yuri; Cole, Kevin; Rao, Prahalada (Elsevier, 2025-01-05)
In this work, we developed and applied a physics-guided autonomous feedforward model predictive process control approach called DynamicPrint to mitigate part defects in laser powder bed fusion (LPBF) additive manufacturing. Currently, the processing parameters for LPBF of a specific material are optimized through empirical testing of simple-shaped coupons. These optimized parameters are typically maintained constant when printing complex parts. However, using constant parameters often causes uneven temperature distribution in complex parts, leading to such defects as inhomogeneous microstructure, poor surface finish, thermal-induced distortion, and build failures. By contrast, DynamicPrint autonomously adjusts the processing parameters layer-by-layer before an LPBF part is printed to prevent non-uniform temperature distribution and mitigate thermal-induced defects. The a priori process parameter adjustments in DynamicPrint are guided by rapid physics-based thermal simulations. Through experiments with complex stainless steel 316 L LPBF parts, we demonstrate the following beneficial outcomes of DynamicPrint: (i) homogenous grain sizes and consistent properties (microhardness); (ii) improved geometric accuracy and surface integrity of hard-to-access internal features; and (iii) avoidance of recoater crashes and elimination of supports in parts with prominent overhang features. DynamicPrint can greatly accelerate the time-to-market for LPBF parts by offering a rapid, physics-based method for process qualification, unlike the current cumbersome and expensive empirical build-and-test approach.
A data-driven approach to the “Everesting” cycling challenge
Seo, Junhyeon; Raeymaekers, Bart (Nature Publishing Group, 2023-02-08)
The “Everesting” challenge is a cycling activity in which a cyclist repeats a hill until accumulating an elevation gain equal to the elevation of Mount Everest in a single ride. The challenge experienced a surge in interest during the COVID-19 pandemic and the cancelation of cycling races around the world that prompted cyclists to pursue alternative, individual activities. The time to complete the Everesting challenge depends on the fitness and talent of the cyclist, but also on the length and gradient of the hill, among other parameters. Hence, preparing an Everesting attempt requires understanding the relationship between the Everesting parameters and the time to complete the challenge. We use web-scraping to compile a database of publicly available Everesting attempts, and we quantify and rank the parameters that determine the time to complete the challenge. We also use unsupervised machine learning algorithms to segment cyclists into distinct groups according to their characteristics and performance. We conclude that the power per unit body mass of the cyclist and the tradeoff between the gradient of the hill and the distance are the most important considerations when attempting the Everesting challenge. As such, elite cyclists best select a hill with gradient > 12%, whereas amateur and recreational cyclists best select a hill with gradient < 10% to minimize the time to complete the Everesting challenge.
Guest editorial: Special issue on artificial intelligence and emerging computational approaches for tribology
Zhang, Zhinan; Pan, Shuaihang; Raeymaekers, Bart (2024-04-02)
Measuring and Simulating the Transient Packing Density During Ultrasound Directed Self-Assembly and Vat Polymerization Manufacturing of Engineered Materials
Noparast, Soheyl; Guevara Vasquez, Fernando; Francoeur, Mathieu; Raeymaekers, Bart (Wiley, 2024-04-08)
Ultrasound-directed self-assembly (DSA) uses ultrasound waves to organize and orient particles dispersed in a fluid medium into specific patterns. Combining ultrasound DSA with vat photopolymerization (VP) enables manufacturing materials layer-by-layer, wherein each layer the organization and orientation of particles in the photopolymer is controlled, which enables tailoring the properties of the resulting composite materials. However, the particle packing density changes with time and location as particles organize into specific patterns. Hence, relating the ultrasound DSA process parameters to the transient local particle packing density is important to tailor the properties of the composite material, and to determine the maximum speed of the layer-by-layer VP process. This paper theoretically derives and experimentally validates a 3D ultrasound DSA model and evaluates the local particle packing density at locations where particles assemble as a function of time and ultrasound DSA process parameters. The particle packing density increases with increasing particle volume fraction, decreasing particle size, and decreasing fluid medium viscosity is determined. Increasing the particle size and decreasing the fluid medium viscosity decreases the time to reach steady-state. This work contributes to using ultrasound DSA and VP as a materials manufacturing process.
Learning from Experience: A Faculty-Led Collaborative Inquiry Exploring Embedded Communication Skills Across Engineering Curricula
Biviano, Angelo; Branscome, Caroline; Burgoyne, Christine Bala; Carper, Kathleen; Iorio, Josh; Scarff, Kelly; Taylor, Ashley R.; Arena, Sara (ASEE Conferences, 2024-06-23)
This evidence-based practice paper describes a collaborative inquiry process to explore a critical question for engineering faculty: what are practical strategies for leveraging evidence-based practices to embed communication skills across core engineering curricula? Within engineering education, there is a growing consensus that communication skills are essential for engineering graduates. For example, the Accreditation Board for Engineering and Technology (ABET) distinctly highlights communication skills as a required student learning outcome for accreditation of engineering programs in ABET Criterion 3.3.: an ability to communicate effectively with a range of audiences. Numerous studies exploring engineers’ school-to-work transition suggest that communication is one of the most important skill sets for engineering practice according to both recent graduates (Passow, 2012) and industry (Male et. al, 2010). As the Engineer of 2020 Report concisely noted, “good engineering will require good communication” (National Academy of Engineering, 2004, p. 56). Despite the engineering education community’s shared vision for ensuring engineering graduates can communicate effectively, few practical examples exist to illuminate how faculty can leverage evidence-based practices to integrate communication skills into their existing technical curricula. Therefore, the purpose of this paper is to share seven practical case-based examples of strategies implemented in a spectrum of engineering disciplines and learning environments to support faculty in integrating communication skills into existing engineering curriculum. We first describe our collaborative inquiry process to create a “systematic structure for learning from experience” (Yorks & Kasl, 2002, p. 3). Our learning from experience is rooted in the reflections of faculty representing seven engineering departments who teach communication skills across a diverse range of engineering curricular contexts (e.g., course size, course level, technical subject, etc.) Next, we provide seven case studies of evidence-based strategies-in-action across this range of learning contexts, including both undergraduate and graduate education. For example, one case study discusses the integration of a community-focused debate project in a mining engineering undergraduate course to build students’ communications skills in rhetorical situation analysis while another study in a construction engineering management department attends to aspects of diversity and inclusion by promoting a writing process that begins with visual design. These case studies provide rich context for the learning environment and the implementation of the evidence-based practice, with the ultimate goal of supporting faculty in drawing connections to their own teaching strategies. Finally, we conclude by situating the case studies in the broader engineering education literature and sharing reflections for lessons learned on integration of communication instruction across existing engineering curricula.
Spinel oxide enables high-temperature self-lubrication in superalloys
Zhang, Zhengyu; Hershkovitz, Eitan; An, Qi; Liu, Liping; Wang, Xiaoqing; Deng, Zhifei; Baucom, Garrett; Wang, Wenbo; Zhao, Jing; Xin, Ziming; Moore, Lowell; Yi, Yao; Islam, Md Rezwan Ul; Chen, Xin; Cui, Bai; Li, Ling; Xin, Hongliang; Li, Lin; Kim, Honggyu; Cai, Wenjun (Nature Research, 2024-11-20)
The ability to lubricate and resist wear at temperatures above 600 °C in an oxidative environment remains a significant challenge for metals due to their high-temperature softening, oxidation, and rapid degradation of traditional solid lubricants. Herein, we demonstrate that high-temperature lubricity can be achieved with coefficients of friction (COF) as low as 0.10-0.32 at 600- 900 °C by tailoring surface oxidation in additively-manufactured Inconel superalloy. By integrating high-temperature tribological testing, advanced materials characterization, and computations, we show that the formation of spinel-based oxide layers on superalloy promotes sustained self-lubrication due to their lower shear strength and more negative formation and cohesive energy compared to other surface oxides. A reversible phase transformation between the cubic and tetragonal/monoclinic spinel was driven by stress and temperature during high temperature wear. To span Ni- and Cr-based ternary oxide compositional spaces for which little high-temperature COF data exist, we develop a computational design method to predict the lubricity of oxides, incorporating thermodynamics and density functional theory computations. Our finding demonstrates that spinel oxide can exhibit low COF values at temperatures much higher than conventional solid lubricants with 2D layered or Magnéli structures, suggesting a promising design strategy for selflubricating high-temperature alloys.

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