Open Access Publications - Department of Mechanical Engineering

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Open access publications by faculty, postdocs, and graduate students in the Department of Mechanical Engineering.

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Prognostic assessment of osteolytic lesions and mechanical properties of bones bearing breast cancer using neural network and finite element analysis
(Mechanobiology in Medicine, 2025-04-10) Wang, Shubo; Chu, Tiankuo; Wasi, Murtaza; Guerra, Rosa M.; Yuan, Xu; Wang, Liyun
The management of skeletal-related events (SREs), particularly the prevention of pathological fractures, is crucial for cancer patients. Current clinical assessment of fracture risk is mostly based on medical images, but incorporating sequential images in the assessment remains challenging. This study addressed this issue by leveraging a comprehensive dataset consisting of 260 longitudinal micro-computed tomography (μCT) scans acquired in normal and breast cancer bearing mice. A machine learning (ML) model based on a spatial–temporal neural network was built to forecast bone structures from previous μCT scans, which were found to have an overall similarity coefficient (Dice) of 0.814 with ground truths. Despite the predicted lesion volumes (18.5 % ± 15.3 %) being underestimated by ∼21 % than the ground truths’ (22.1 % ± 14.8 %), the time course of the lesion growth was better represented in the predicted images than the preceding scans (10.8 % ± 6.5 %). Under virtual biomechanical testing using finite element analysis (FEA), the predicted bone structures recapitulated the loading carrying behaviors of the ground truth structures with a positive correlation (y = 0.863x) and a high coefficient of determination (R2 = 0.955). Interestingly, the compliances of the predicted and ground truth structures demonstrated nearly identical linear relationships with the lesion volumes. In summary, we have demonstrated that bone deterioration could be proficiently predicted using machine learning in our preclinical dataset, suggesting the importance of large longitudinal clinical imaging datasets in fracture risk assessment for cancer bone metastasis. Graphical abstract available at: https://doi.org/10.1016/j.mbm.2025.100130 Highlights • Fracture risk assessment is critical in managing bone cancer metastasis. • Utilized 260 longitudinal μCT scans of both normal mice and cancer-bearing mice. • Bone lesion progression predicted from μCT scans using machine learning (ML). • Finite element analysis (FEA) revealed the rigidity of the predicted bone structures. • Predictive modeling of bone deterioration is a valuable tool to assess fracture risk.
Life Cycle Assessment of Thermoelectrics: Ecological Viability in Intermittent Waste Heat Scenarios
(ACS Omega, 2025-04-01) Iyer, Rakesh Krishnamoorthy; Sabet, Morteza; Pilla, Srikanth
This study evaluates the ecological impacts of thermoelectrics (TEs) in stationary applications that periodically generate waste heat using life cycle assessment (LCA) methodology, a first of its kind. Six TE modules are analyzed for a periodic heat-emitting application: a natural gas-based power plant that meets only peak electricity demand. The analysis uses detailed inventories from an earlier study regarding the production and end-of-life stages of the TEs. The results show that while TEs are effective in conserving fossil fuels and lowering greenhouse gas emissions, they do not exhibit significant positive effects on other environmental impacts. These findings persist even when accounting for variations in TE conversion efficiency and lifetime and the implementation of a circular economy approach for recycling and repurposing TE modules. This suggests that the environmental suitability of TEs is predominantly influenced by the type of fossil energy source they replace, making current TEs unsuitable for stationary applications that periodically generate waste heat. The study also highlights the need for further research on the development of new, practical TEs that utilize nontoxic, abundant elements and are produced through less energy-intensive techniques.
Modeling of periodical shearing flow in a fibrous space with applications in shear-induced brain injury
(Physics of Fluids, 2024-06-04) Lang, Ji; Wang, Liyun; Wu, Qianhong
This paper presents a theoretical model examining the interaction between a fibrous network and viscous fluid flow driven by an oscillating boundary. The aim is to understand how oscillating impacts are transmitted from the skull, through the arachnoid trabeculae network filled with cerebrospinal fluid, as observed in shaken baby syndrome. The model uses an effective medium approach to determine the fluid velocity field while each fiber is treated as a soft string undergoing deformation. Results indicate that the frequency of oscillation, fiber stiffness, and porous structure resistance significantly influence the oscillating shearing flow, as indicated by the Womersley (⁠Wo⁠), Brinkman (⁠a⁠), and Bingham (Bm⁠ ⁠) numbers. Application of the model to shaken baby syndrome suggests that oscillations in the cerebrospinal fluid and arachnoid trabeculae can significantly surpass those on the skull, leading to intense shear stress penetration to the brain. This model is the first study to integrate the dynamic response of string-like fibrous networks in fluid flows with oscillating boundaries and offers a quantitative framework for predicting the transmission of shearing forces from the skull to the brain matter.
Quadrupole Magnetic Tweezers for Precise Cell Transportation
(IEEE Transactions on Biomedical Engineering, 2024-12-09) Yang, Yanda; Sokolich, Max; Mallick, Sudipta; Das, Sambeeta
This research introduces a quadrupole magnetic tweezers which can be used for precise cell transportation by actuating magnetic spherical microrobots. The focus of the system is on navigating and manipulating cells within environments characterized by high cellular density. Demonstrating efficacy in moving cells through densely packed cell samples, the system underscores its potential to overcome common obstacles such as inaccurate target delivery and inefficiency. The findings from this study highlight the significant promise that microrobotic technologies hold in advancing medical applications, particularly in precise cell delivery mechanisms, setting a foundation for the future exploration and utilization of medical microrobots.
Electrochemo-Mechanical Degradation and Failure of Active Particles in High Energy Density Batteries: A Review
(Small, 2025-01-07) Li, Dawei; Shen, Chenhao; Zheng, Yuejiu; Xu, Jun
Failure of the active particles is inherently electrochemo-mechanics dominated. This review comprehensively examines the electrochemo-mechanical degradation and failure mechanisms of active particles in high-energy density lithium-ion batteries. The study delves into the growth of passivating layers, such as the solid electrolyte interphase (SEI), and their impact on battery performance. It highlights the role of elevated temperatures in accelerating degradation reactions, such as the dissolution of transition metals and the formation of new SEI layers, leading to capacity fade and increased internal resistance. The review also discusses the mechanical degradation of electrode materials, including the fracture of active particles and the impact of stress on electrode performance. Advanced characterization techniques, such as cryogenic scanning transmission electron microscopy and 3D tomography, are explored to provide insights into the structural and chemical evolution of battery materials. By addressing the interplay between chemical, mechanical, and thermal factors, this review aims to provide guidelines for the chemistry development, material selection, structural design as well as recycling of next-generation batteries with high safety, durability, and high energy density.
Detailed computational modeling of crack patterns of silicon-based anode sheet in lithium-ion batteries upon mechanical stress
(Energy Materials and Devices, 2025-02-17) Kawashima,Yuzuki; Ogata, Kazuma; Shibayama, Yuto; Takagi, Aoi; Yonezu, Akio; Xu, Jun
Silicon (Si)-based anodes, where Si serves as the active material, have garnered significant attention due to their potential to achieve high electric capacity in lithium-ion batteries (LIBs). A key challenge with Si-based anodes is their susceptibility to create in-plane cracks caused by stresses from the manufacturing process and cyclic charging, which ultimately shortens battery life and reduces the overall electrochemical capacity. To address this issue, a refined microstructural design of the active material layer is in pressing need to enhance both the performance and longevity of LIBs. We successfully applied the Oyane failure criterion, which models ductile failure under stress triaxiality, to simulate crack initiation and propagation in the binder matrix containing Si particles in the finite element modeling. Given the non-linear plastic deformation of the binder, this criterion was formulated based on cumulative strain increments. The computational results of microcrack formation within the active material layer under uniaxial tension were then validated by the experimental observations. Furthermore, we developed several models with varied particle arrangements, comparing each simulated crack path to actual microstructural images obtained via scanning electron microscopy. The findings confirm the accuracy of the model, underlying its promising application in optimizing the microstructure of Si-based anodes for enhanced LIB performance and durability. Graphical Abstract available at: https://doi.org/10.26599/EMD.2025.9370054.
Osteocyte Dendrites: How Do They Grow, Mature, and Degenerate in Mineralized Bone?
(Cytoskeleton, 2024-12-09) Guerra, Rosa M.; Fowler, Velia M.; Wang, Liyun
Osteocytes, the most abundant bone cells, form an extensive cellular network via interconnecting dendrites. Like neurons in the brain, the long-lived osteocytes perceive mechanical and biological inputs and signal to other effector cells, leading to the homeostasis and turnover of bone tissues. Despite the appreciation of osteocytes' vital roles in bone biology, the initiation, growth, maintenance, and eventual degradation of osteocyte dendrites are poorly understood due to their full encasement by mineralized matrix. With the advancement of imaging modalities and genetic models, the architectural organization and molecular composition of the osteocyte dendrites, as well as their morphological changes with aging and diseases, have begun to be revealed. However, several long-standing mysteries remain unsolved, including (1) how the dendrites are initiated and elongated when a surface osteoblast becomes embedded as an osteocyte; (2) how the dendrites maintain a relatively stable morphology during their decades-long life span; (3) what biological processes control the dendrite morphology, connectivity, and stability; and (4) if these processes are influenced by age, sex, hormones, and mechanical loading. Our review of long, thin actin filament (F-actin)-containing processes extending from other cells leads to a working model that serves as a starting point to investigate the formation and maintenance of osteocyte dendrites and their degradation with aging and diseases.
Mechanical Properties of the Cortex in Older Adults and Relationships With Personality Traits
(Human Brain Mapping, 2025-02-06) Twohy, Kyra E.; Kramer, Mary K.; Diano, Alexa M.; Bailey, Olivia M.; Delgorio, Peyton L.; McIlvain, Grace; McGarry, Matthew D. J.; Martens, Christopher R.; Schwarb, Hillary; Hiscox, Lucy V.; Johnson, Curtis L.
Aging and neurodegeneration impact structural brain integrity and can result in changes to behavior and cognition. Personality, a relatively stable trait in adults as compared to behavior, in part relies on normative individual differences in cellular organization of the cerebral cortex, but links between brain structure and personality expression have been mixed. One key finding is that personality has been shown to be a risk factor in the development of Alzheimer's disease, highlighting a structure–trait relationship. Magnetic resonance elastography (MRE) has been used to noninvasively study age-related changes in tissue mechanical properties because of its high sensitivity to both the microstructural health and the structure–function relationship of the tissue. Recent advancements in MRE methodology have allowed for reliable property recovery of cortical subregions, which had previously presented challenges due to the complex geometry and overall thin structure. This study aimed to quantify age-related changes in cortical mechanical properties and the relationship of these properties to measures of personality in an older adult population (N = 57; age 60–85 years) for the first time. Mechanical properties including shear stiffness and damping ratio were calculated for 30 bilateral regions of the cortex across all four lobes, and the NEO Personality Inventory (NEO-PI) was used to measure neuroticism and conscientiousness in all participants. Shear stiffness and damping ratio were found to vary widely across regions of the cortex, upward of 1 kPa in stiffness and by 0.3 in damping ratio. Shear stiffness changed regionally with age, with some regions experiencing accelerated degradation compared to neighboring regions. Greater neuroticism (i.e., the tendency to experience negative emotions and vulnerability to stress) was associated with high damping ratio, indicative of poorer tissue integrity, in the rostral middle frontal cortex and the precentral gyrus. This study provides evidence of structure–trait correlates between physical mechanical properties and measures of personality in older adults and adds to the supporting literature that neurotic traits may impact brain health in cognitively normal aging.
Kinematics, kinetics, and muscle activations during human locomotion over compliant terrains
(Scientific Data, 2025-01-16) Angelidou, Charikleia; Chambers, Vaughn; Hobbs, Bradley; Karakasis, Chrysostomos; Artemiadis, Panagiotis
Walking on compliant terrains, like carpets, grass, and soil, presents a unique challenge, especially for individuals with mobility impairments. In contrast to rigid-ground walking, compliant surfaces alter movement dynamics and increase the risk of falls. Understanding and modeling gait control across such soft and deformable surfaces is thus crucial for maintaining daily mobility. However, access to the necessary equipment for modeling compliant surface walking is limited. Therefore, in this paper, we present the first publicly available biomechanics dataset of 20 individuals walking on terrains of varying compliance, using a unique robotic device, the Variable Stiffness Treadmill 2 (VST 2), designed to simulate walking on adjustable compliant terrain. VST 2 provides a consistent and reproducible environment for studying the biomechanics of walking on such surfaces within laboratory settings. The goal of this dataset is to provide insights into the muscular, kinematic, and kinetic adaptations that occur when humans walk on compliant terrain in order to design better controllers for prosthetic limbs, improve rehabilitation protocols, and develop adaptive assistive devices that can enhance mobility on compliant surfaces.
Behavior of chemically powered Janus colloids in lyotropic chromonic liquid crystal
(Physical Review E, 2024-11-21) Sudha, Devika Gireesan; Baza, Hend; Rivas, David P.; Das, Sambeeta; Lavrentovich, Oleg D.; Hirst, Linda S.
Platinum-coated Janus colloids exhibit self-propelled motion in aqueous solution via the catalytic decomposition of hydrogen peroxide. Here, we report their motion in a uniformly aligned nematic phase of lyotropic chromonic liquid crystal, disodium cromoglycate (DSCG). When active Janus colloids are placed in DSCG, we find that the anisotropy of the liquid crystal imposes a strong sense of direction to their motion; the Janus colloids tend to move parallel to the nematic director. Motion analysis over a range of timescales reveals a crossover from ballistic to anomalous diffusive behavior on timescales below the relaxation time for liquid crystal elastic distortions. Surprisingly we observe that smaller particles roll during ballistic motion, whereas larger particles do not. This result highlights the complexity of phoretically-driven particle motion, especially in an anisotropic fluid environment.
Muscular, temporal, and spatial responses to shoulder exosuit assistance during functional tasks
(Journal of Neurophysiology, 2024-11-01) Burch, Kaleb; Higginson, Jill
Shoulder exosuits are a promising new technology that could enable individuals with neuromuscular impairments to independently perform activities of daily living, however, scarce evidence exists to evaluate their ability to support such activities. Consequently, it is not understood how humans adapt motion in response to assistance from a shoulder exosuit. In this study, we developed a cable-driven shoulder exosuit and evaluated its effect on reaching and drinking tasks within a cohort of 18 healthy subjects to quantify changes to muscle activity and kinematics as well as trial-to-trial learning in duration and actuator switch timing. The exosuit successfully reduced mean muscle activity in the middle (reaching: 23.4 ± 26.3%, drinking: 20.0 ± 25.1%) and posterior (reaching: 12.8 ± 10.3%, drinking: 4.0 ± 7.2%) deltoid across both functional tasks. Likewise, the exosuit reduced integrated muscle activity in the middle deltoid (reaching: 22.2 ± 22.7%, drinking: 14.9 ± 27.0%). Exosuit assistance also altered kinematics such that individuals allowed their arms to follow forces applied by the exosuit. In terms of learning, subjects reduced movement duration by 15.6 ± 11.9% as they practiced using the exosuit. Reducing movement duration allowed subjects to reduce integrated muscle activity in the anterior (15.2 ± 10.3%), middle (14.7 ± 9.7%), and posterior (14.8 ± 9.7%) deltoids. Similarly, subjects activated the actuator switch earlier over the course of many assisted trials. The muscle activity reductions during both reaching and drinking demonstrate the promise of shoulder exosuits to enable independent function among individuals with neuromuscular impairments. The kinematic response to assistance and learning features observed in movement duration provide insight into human-exosuit interaction principles that could inform future exosuit development. NEW & NOTEWORTHY Shoulder exosuits assist arm function, but it is not understood how assistance affects motion. We evaluated spatiotemporal movement features and muscle activity during assisted and unassisted arm motions. Introducing the exosuit caused individuals to let their arms follow assistive forces. Furthermore, individuals learned to use the exosuit with practice by moving more quickly to reduce cumulative effort and by activating assistance earlier. These results demonstrate that individuals adapt exosuit-assisted motion to reduce effort.
Individual closed-loop control of micromotors by selective light actuation
(Soft Matter, 2024-11-11) Rivas, David P.; Sokolich, Max; Das, Sambeeta
Control of individual micromotors within a group would allow for improved efficiency, greater ability to accomplish complex tasks, higher throughput, and increased adaptability. However, independent control of micromotors remains a significant challenge. Typical actuation techniques, such as chemical and magnetic, are uniform over the workspace and therefore cannot control one micromotor independently of the others. To address this challenge, we demonstrate a novel control method of applying a localized region of UV light that activates a single light-responsive TiO2 micromotor at a time. To achieve this, a digital micromirror device (DMD) was employed which is capable of highly precise localized illumination. To demonstrate this precise user-defined control, patterns of micromotors were created via selective actuation and magnetic steering. In addition, a closed-loop system was also developed which automates the guidance of individual micromotors to specified locations, illustrating the potential for more efficient and precise control of the micromotors.
Enhancing cathode composites with conductive alignment synergy for solid-state batteries
(Science Advances, 2025-01-03) Cao, Zhang; Yao, Xinxin; Park, Soyeon; Deng, Kaiyue; Zhang, Chunyan; Chen, Lei; Fu, Kelvin
Enhancing transport and chemomechanical properties in cathode composites is crucial for the performance of solid-state batteries. Our study introduces the filler-aligned structured thick (FAST) electrode, which notably improves mechanical strength and ionic/electronic conductivity in solid composite cathodes. The FAST electrode incorporates vertically aligned nanoconducting carbon nanotubes within an ion-conducting polymer electrolyte, creating a low-tortuosity electron/ion transport path while strengthening the electrode’s structure. This design not only mitigates recrystallization of the polymer electrolyte but also establishes a densified local electric field distribution and accelerates the migration of lithium ions. The FAST electrode showcases outstanding electrochemical performance with lithium iron phosphate as the active material, achieving a high capacity of 148.2 milliampere hours per gram at 0.2 C over 100 cycles with substantial material loading (49.3 milligrams per square centimeter). This innovative electrode design marks a remarkable stride in addressing the challenges of solid-state lithium metal batteries.
Transforming CO2 into advanced 3D printed carbon nanocomposites
(Nature Communications, 2024-12-04) Crandall, Bradie S.; Naughton, Matthew; Park, Soyeon; Yu, Jia; Zhang, Chunyan; Mahtabian, Shima; Wang, Kaiying; Liang, Xinhua; Fu, Kelvin; Jiao, Feng
The conversion of CO2 emissions into valuable 3D printed carbon-based materials offers a transformative strategy for climate mitigation and resource utilization. Here, we 3D print carbon nanocomposites from CO2 using an integrated system that electrochemically converts CO2 into CO, followed by a thermocatalytic process that synthesizes carbon nanotubes (CNTs) which are then 3D printed into high-density carbon nanocomposites. A 200 cm2 electrolyzer stack is integrated with a thermochemical reactor for more than 45 h of operation, cumulatively synthesizing 37 grams of CNTs from CO2. A techno-economic analysis indicates a 90% cost reduction in CNT production on an industrial scale compared to current benchmarks, underscoring the commercial viability of the system. A 3D printing process is developed that achieves a high nanocomposite CNT concentration (38 wt%) while enhancing composite structural attributes via CNT alignment. With the rapidly rising demand for carbon nanocomposites, this CO2-to-nanocomposite process can make a substantial impact on global carbon emission reduction efforts.
Visualizing fiber end geometry effects on stress distribution in composites using mechanophores
(Soft Matter, 2024-11-14) Haque, Nazmul; Chang, Hao Chun; Chang, Chia-Chih; Davis, Chelsea S.
Localized stress concentrations at fiber ends in short fiber-reinforced polymer composites (SFRCs) significantly affect their mechanical properties. Our research targets these stress concentrations by embedding nitro-spiropyran (SPN) mechanophores into the polymer matrix. SPN mechanophores change color under mechanical stress, allowing us to visualize and quantify stress distributions at the fiber ends. We utilize glass fibers as the reinforcing material and employ confocal fluorescence microscopy to detect color changes in the SPN mechanophores, providing real-time insights into the stress distribution. By combining this mechanophore-based stress sensing with finite element analysis (FEA), we evaluate localized stresses that develop during a single fiber pull-out test near different fiber end geometries—flat, cone, round, and sharp. This method precisely quantifies stress distributions for each fiber end geometry. The mechanophore activation intensity varies with fiber end geometry and pull-out displacement. Our results indicate that round fiber ends exhibit more gradual stress transfer into the matrix, promoting effective stress distribution. Also, different fiber end geometries lead to distinct failure mechanisms. These findings demonstrate that fiber end geometry plays a crucial role in stress distribution management, critical for optimizing composite design and enhancing the reliability of SFRCs in practical applications. By integrating mechanophores for real-time stress visualization, we can accurately map quantified stress distributions that arise during loading and identify failure mechanisms in polymer composites, offering a comprehensive approach to enhancing their durability and performance.
Mechanical Deformation Behavior of Polymer Blend Thin Films
(Macromolecular Rapid Communications, 2024-12-31) Pokhrel, Geeta; Jo, Hyungyung; Christ, Nicholas M.; Son, Hyeyoung; Howarter, John A.; Davis, Chelsea S.
Examining the mechanical properties of polymer thin films is crucial for high-performance applications such as displays, coatings, sensors, and thermal management. It is important to design thin film microstructures that excel in high-demand situations without compromising mechanical integrity. Here, a polymer blend of polystyrene (PS) and polyisoprene (PI) is used as a model to explore microscale deformation behavior under uniaxial mechanical testing. Six thin film compositions ranging from pure PS to a 4.5:5.5 ratio of PS to PI are fabricated. The thin films are deformed under compression, tension, and cyclic loadings, while monitoring the behavior utilizing a micromechanical stage and optical microscopy. To calculate the plane strain modulus, a strain-induced elastic buckling instability technique is employed. The results show that as the PI concentration increases, the plane strain modulus of the films decreases while the fracture strain increases. For the 4.5:5.5 ratio of PS to PI with a continuous rubbery PI phase, the thin films show major recoverable mechanical performance. This behavior is attributed to the mechanical strength of glassy PS combined with the strain energy absorption capability of rubbery PI, enabling elastic recovery. These fundamental observations provide valuable insights for designing mechanically resilient thin films for coatings and flexible devices.
Mechanical evaluation of mandibular fractures stabilized with absorbable implants or intraoral splints in cats
(Frontiers in Veterinary Science, 2025-01-07) Castejon-Gonzalez, Ana C.; Friday, Chet S.; Hast, Michael W.; Reiter, Alexander M.
Introduction: The goal of this cadaver study in cats was to compare the mechanical properties of intact mandibles (C) with mandibles whose simulated fracture was located between the third and fourth premolar teeth and repaired with four possible treatments: (1) Stout multiple loop interdental wiring plus bis-acryl composite intraoral splint (S); (2) modified Risdon interdental wiring plus bis-acryl composite intraoral splint (R); (3) ultrasound-aided absorbable fixation plate (P); and (4) ultrasound-aided absorbable fixation mesh (M). Materials and methods: Thirty feline mandibles were randomly assigned to the control and treatment groups. Mandibles were loaded by cantilever bending on the canine tooth, first in non-destructive cyclic loading followed by destructive ramp-to-failure loading. Results: Cyclic loading showed no differences between the treatment groups in angular deflection (a measure of sample flexion under non-destructive loads); however, the R group had significantly higher angular deflection than the C group. In destructive testing, no differences in mechanical properties were found between the treatment groups; however, all treatment groups demonstrated significantly lower maximum bending moment, bending stiffness, energy to failure, and maximum force when compared to the control group. The main mode of failure of the intraoral splint groups (S and R) was fracture of the bis-acryl composite (50%), and the main mode of failure of the absorbable fixation groups (P and M) was fracture of the pins (91.7%). Discussion: Intraoral splint and absorbable fixation methods have low strength and stiffness. The four treatments tested provided similar stabilization of mandibular fractures located between the third and fourth premolar teeth.
Model-Driven Manufacturing of High-Energy-Density Batteries: A Review
(Batteries & Supercaps, 2024-10-09) Maksimovna Vakhrusheva, Daria; Xu, Jun
Graphical Abstract This review offers a comprehensive review of recent advancements in model-driven manufacturing approaches for high-energy-density batteries. It highlights the integration of computational models with experimental manufacturing processes to optimize battery performance, reliability, and cost-effectiveness. Additionally, the review addresses the challenges associated with scaling up these model-driven approaches, focusing on critical issues such as model validation, parameter sensitivity, and the incorporation of artificial intelligence. Graphical Abstract available at: https://doi.org/10.1002/batt.202400539 Abstract The rapid advancement in energy storage technologies, particularly high-energy density batteries, is pivotal for diverse applications ranging from portable electronics to electric vehicles and grid storage. This review paper provides a comprehensive analysis of the recent progress in model-driven manufacturing approaches for high-energy-density batteries, highlighting the integration of computational models and simulations with experimental manufacturing processes to optimize performance, reliability, safety, and cost-effectiveness. We systematically examine various modeling techniques, including electrochemical, thermal, and mechanical models, and their roles in elucidating the complex interplay of materials, design, and manufacturing parameters. The review also discusses the challenges and opportunities in scaling up these model-driven approaches, addressing key issues such as model validation, parameter sensitivity, and the integration of machine learning and artificial intelligence for predictive modeling, process optimization, and quality assurance. By synthesizing current research findings and industry practices, this paper aims to outline a roadmap for future developments in model-driven manufacturing of high-energy density batteries, emphasizing the need for interdisciplinary collaboration and innovation to meet the increasing demands for energy storage solutions.
Visualizing separation at composite interfaces via spirolactam mechanophores
(RSC Mechanochemistry, 2024-10-17) Gohl, Jared A.; Roberts, Tyler J.; Freund, Anna C.; Haque, Nazmul; Rueschhoff, Lisa M.; Baldwin, Luke A.; Davis, Chelsea S.
The failure of interfaces between polymers and inorganic substrates often leads to deteriorated performance, as is the case for polymer matrix composites. Interfacial mechanophores (iMPs) have the potential to fluorescently measure interfacial failures. Spirolactam-based mechanophores are of interest due to their readily available synthetic precursors and compatibility with epoxy matrices. In this work, spirolactam is covalently bound at the interface of silica surfaces and epoxy, chosen due to the industrial relevance of glass fiber composites. The iMPs are mechanically activated through uniaxial tension applied to the composite while the resulting fluorescent response is observed in situ with a confocal microscope. Due to their real time sensing capabilities, iMPs are a promising technique to measure interfacial failures in composite materials more easily than with traditional optical microscopy techniques.
Trace inequalities and kinematic metrics
(Robotica, 2024-09-12) Wu, Yuwei; Chirikjian, Gregory S.
Kinematics remains one of the cornerstones of robotics, and over the decade, Robotica has been one of the venues in which groundbreaking work in kinematics has always been welcome. A number of works in the kinematics community have addressed metrics for rigid-body motions in multiple different venues. An essential feature of any distance metric is the triangle inequality. Here, relationships between the triangle inequality for kinematic metrics and so-called trace inequalities are established. In particular, we show that the Golden-Thompson inequality (a particular trace inequality from the field of statistical mechanics) which holds for Hermitian matrices remarkably also holds for restricted classes of real skew-symmetric matrices. We then show that this is related to the triangle inequality for SO(3) and SO(4) metrics.

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