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Macroscale Fabrication of Three-Dimensional Carbon Architectures with Hierarchical Porosity and Tunable Mechanical Properties
No full textThe strength of a material originates from features across multiple length scales, from atomic bonds to macroscale architecture. While high strength is typically associated with dense materials, such as metals, low-density systems, like foams, often lack mechanical robustness. Natural materials—including bone, wood, and enamel—defy this trade-off through hierarchical architectures that span several orders of magnitude. Inspired by these systems, this thesis explores design strategies for synthetic 3D porous carbon structures that challenge long-standing trade-offs between density, strength, toughness, and dimensional stability. The core innovation is a modular template–coating approach that bridges nanoscale strengthening effects with macroscopic utility. By combining sacrificial porous templates with conformal, high–char-yield coatings, this method enables precise control over shrinkage and mass retention during pyrolysis. Using this strategy, I demonstrate macroscale carbon foams with ~80% dimensional retention and specific strengths up to ~0.13 GPa g-1 cm3—among the highest reported for polymer-derived carbons. I further develop a thermally compatible polybenzoxazine system with tunable densities (~0.1–0.7 g cm-3) and ~90% dimensional retention, surpassing conventional approaches in the density–shrinkage landscape. Finally, I demonstrate that partial carbonization of 3D-printed lattices yields hybrid carbon–polymer architectures with specific strengths of ~128 MPa g-1 cm-3 and toughnesses of ~32 J g-1 at only ~20% shrinkage. Together, these results define a new design space for porous carbon materials—one that combines hierarchical architecture with scalable processing to access combinations of materials properties typically considered mutually exclusive. This work lays the foundation for lightweight, strong, and damage-tolerant carbon materials for next-generation applications in construction, packaging, transportation, and beyond
Devil’s Bargain: How Elite Deals Undermined Sudan’s Democratic Transition
Get PDFThis dissertation explores how counter-revolutionary forces utilize a playbook to derail democracy and exploit the ostensibly pro-democratic international community’s efforts to secure a democratic transition. Focusing on Sudan’s attempted democratic transition (2019-2023) it consists of three chapters plus an introduction and conclusion that investigate the actions of civilian, international, and military actors during the transitional period and highlight the incentives that plunged the country into civil war. In 2019, the Sudanese uprising forced out President Omar al-Bashir capturing the world’s attention and providing optimism on the democratic prospects of nonviolent resistance movements in the wake of authoritarian resurgence in Egypt and Tunisia. Yet halfway through a planned 39- month run-up to elections, the Sudanese military carried out a coup against the transitional government. By April 2023, with a deal to return to the transition hanging in the balance, war broke out between factions of the military putting an end to hopes for a democratic Sudan. Chapter 2 (Escaping the Transition Trap) lays out the counter revolutionary playbook that was used against Sudan’s would-be democrats. This chapter argues that counter-revolutionaries worked hard to derail the prospects of democracy in Sudan, thrusting the opposition in a sort of transition trap. Similar to a finger trap, unless both the radical democratic forces and the established opposition parties pushed against the military, they would be unable to free themselves. Chapter 3 (With Friends Like These) examines the international community’s reliance on pacted transitions to “support” Sudan’s democratic transition. While pacted transitions are seen as a relatively safe way to shepherd democratic transitions, the international community in Sudan failed to see the danger of introducing additional division in a country with two militaries. The lack of a security guarantee due to the withdrawal of peacekeepers also gave the military free reign. Ultimately, the international community’s support of the military as a political actor deeply compromised the country’s democratic prospects. Chapter 4 (When Democratization Kills Peace) asks how likely civil war was in Sudan. By examining major correlates of civil war, the chapter makes the argument that though the country was at an elevated risk of civil war, the resulting conflict was not fought along ethnic lines as the literature would predict. Instead, the “war of the generals” was sparked by democratization, a known correlate of civil war that introduced a dangerous bargaining issue the generals chose to resolve with force
Un/Weaving Germany: A Cultural History of Textiles in Literature and Visual Art, 1970 – 90
No full textThis dissertation demonstrates how textile objects and practices played an important but unacknowledged role in art and literature of the Federal Republic of Germany and the German Democratic Republic during the second half of the twentieth century. Positioned against established narratives of the fiber arts revolution in the United States and Great Britain, this project articulates an alternative evolution of textile art in Germany. With a diverse corpus of artists and authors including multimedia artists Annegret Soltau, Gabriele Stötzer, Heike Stephan, and Ellen Thiemann as well as Christa Wolf and concrete poet/mail artist Ruth Wolf-Rehfeldt, I analyze how the development of textile art in East and West Germany navigated the tensions of societies reformulating themselves after World War II. I use unpublished archival material and personal interviews with artists to create a capacious definition of textile art, one that includes both objects made from fiber as well as works that are formed through textile and textile-informed processes, allowing for a textile poetics and woven communities. While German studio textile art is not as radically experimental as that of U.S., U.K., or Polish artists, I use this broader understanding to argue that textile art developed in realms outside established artists’ studios formally innovative and experimental ways. Hence, I argue that textiles were central to the development of art that is radically egalitarian: egalitarian, as it employed techniques and processes which were familiar to individuals in the 1970s and -80s, and radical for its ability to grant an artistic voice to individuals otherwise excluded from professional artistic spheres in East Germany. Through this inclusivity, textile and textile practices demonstrate their potential as an organizing tool for communities and collectives, as I demonstrate with the Erfurter Künstlerinnengruppe (Erfurt Women Artists Group, 1984 – 1994). I also demonstrate the coercive, anti-utopian side of this organizing with Ellen Thiemann and the Kunstgewerbekommando (Arts and Crafts Detail) at Hoheneck Prison. Furthermore, within this egalitarian framework and textiles’ association with domestic spaces and craft, I argue that their migration to literature in Christa Wolf’s poetics of weaving is in part a way of claiming a connection between literary work and the laboring class, thereby obscuring her own privileged position. Along with their ability to facilitate and mediate relationships between individuals, I turn to Soltau’s stitched photographs and Soltau’s photography to argue that textiles act as a surrogate for the body and thereby a means of defining individuals within a society that foregrounds the collective. Ultimately, textile art in Germany both mediates and navigates the spectrum between the binaries of individual and community, artist and amateur, working class and intelligentsia, and craft and art
Exploring the Inclusion of Dynamic Bonds into Adaptive Liquid Crystalline Functional Polymers
Get PDFIn Chapter 1, a review and background of stimuli-responsive materials is provided that identifies dynamic liquid crystal elastomers (LCEs) as a promising class of materials with avenues for potential study. In Chapter 2, a tailorable network design allows for the study of dynamic bond placement within disulfide containing LCEs as it pertains to thermomechanical, morphological, and relaxation properties. In Chapter 3, a linear phase-separated metallosupramolecular liquid crystal polymer (MSLCP) was developed to study the impact that phase separation and metallosupramolecular linkages have on liquid crystallinity as well as how these moieties can be leveraged to synthesize more processable LCP materials. In Chapter 4, disulfide containing LCEs are used as a platform for developing adaptive retrainable adhesive materials whose properties can be synthetically tailored through the bulkiness of the mesogen and the resulting control of the stability of the LC phase. Finally, Chapter 5 provides a summary of the work performed as well as some perspectives and outlooks for future research directions
Prescription Use and Spending After the Introduction of a Real-Time Prescription Benefit Tool
Get PDFImportance: Real-time prescription benefit (RTPB) tools provide point-of-care information for clinicians at the time of prescribing and may reduce prescription costs for patients and payers. Objective: To assess trends in prescription use and spending among Medicare Advantage beneficiaries at a national health insurer during the first year of clinician access to an RTPB tool. Design, Setting, and Participants: This cohort study used 2018 to 2020 administrative data from a national insurer to compare prescription fills for beneficiaries receiving prescriptions from clinicians at practices with an RTPB tool with fills prescribed by clinicians without access to the tool. Trends in prescription spending and fills in the year after practices adopted an RTPB tool (in March 2019) were measured using a difference-in-differences design. Data were analyzed from November 2022 to June 2024. Exposure: Access to an RTPB tool within a national electronic health record software vendor. Main Outcomes and Measures: The main outcomes were total prescription spending, beneficiary out-of-pocket spending, and number of prescription fills. Secondary outcomes included percentage of fills with the insurer-owned mail-order pharmacy, percentage of fills with a 90-day supply, and subgroup analyses in drug classes appearing most frequently in the RTPB tool and high-cost prescription drug classes. Results: The sample included 2 805 060 beneficiaries (mean [SD] age 70.9 [9.2] years; 56.7% female; 14.7% Black individuals; 80.5% White individuals), with mean (SD) monthly out-of-pocket costs of 29.1 dollars (90.4 dollars), total prescription costs of 213.2 dollars (1066.3 dollars), and 2.6 (2.1) prescription fills per month. After introduction of the RTPB tool, there was no change in prescription spending (estimated out-of-pocket spending change, 1.2% [95% CI, −0.7% to 3.0%]; estimated total prescription spending change, 0.5% [95% CI: −0.2% to 1.2%]) or number of prescription fills (estimated change, 0.01 [95% CI, −0.01 to 0.02]) among beneficiaries prescribed medication by clinicians at practices with the RTPB tool. Conclusions and Relevance: In this cohort study of 2.8 million patients, simply providing clinicians access to a RTPB tool was not associated with the anticipated benefits to patients and payers in the first year the tool was released. Further research on how to design and deploy RTPB tools to maximize potential benefits is needed.</p
Wandering the Bilingual Wonderland: Mentally Traveling Through Time in a Foreign Language
No full textPeople spend a significant portion of their daily lives detached from the present, mentally traveling through time to relive past experiences or imagine future scenarios. This ability to project oneself through time serves several crucial adaptive functions, including guiding decision-making, facilitating planning and goal-setting, regulating emotions, and supporting the formation and maintenance of a coherent sense of self. It is, therefore, essential to understand the factors that influence this process. Among these, language plays a particularly significant role. Language is not merely a tool for communicating our mental time travel experiences to others, but it also acts as a vessel through which we travel through time and therefore, it directly affects the experience itself. Yet, the influence of one of the most salient features of language, its nativeness, has not been systematically examined. Given that nearly half of the world’s population speaks more than one language, it is important to understand how using a native versus a foreign language affects the experience of mental time travel. In this dissertation, I investigate how language nativeness influences a key aspect of mental time travel, which is the perceived distance of past and future events, across speakers of English, Chinese, Korean, German, and Italian. In Chapter 1, I report experiments demonstrating that using a foreign language, compared to a native tongue, makes past events feel more temporally distant. In Chapter 2, I present experiments showing that imagining a future scenario in a foreign language increases its perceived distance by making it feel less likely to occur. In both chapters, I also explore two competing accounts of the underlying mechanism. One account proposes that the effect of foreign language use on perceived distance is an indirect consequence of known correlates of foreign language processing, such as reduced emotionality, fluency, and vividness of imagery. The alternative account suggests that language functions as an overarching context that directly influences mental simulations. The findings are consistent with the latter account, and they rule out the account that assumes that the foreign language effect on perceived distance results from reductions in emotionality, fluency, or vividness of imagery. Finally, in Chapter 3, I turn to the real-world implications of these effects. Perceptions of the distance of past and future events are consequential, as they may influence how urgent, relevant, or important those events seem. This, in turn, can affect present-day decisions and behaviors that rely on mental simulations of those events. I test two potential consequences in this chapter: (1) forgiveness motivation, and (2) intention to prepare for environmental threats. The two domains hinge on how people interpret the temporal distance of past events and the likelihood of future events, respectively. For example, perceiving a past transgression as more distant may facilitate forgiveness, while perceiving a future environmental threat as less likely to occur may reduce intention to prepare. Although the distancing effect of foreign language does not replicate in these applied contexts, the findings raise important questions about when language affects perception of distance. Together, this research reveals how language context influences mental time travel by influencing the perceived distance of the past and future, offering new insights into the cognitive processes of the multilingual mind. As people routinely rely on past memories and future simulations to navigate daily life, and increasingly do so in a foreign language, these findings also carry broad implications for an interconnected, multilingual world
Will AI become our Co-PI?
Get PDFRapid advances in large language models (LLMs) are transforming the role of students and principal investigators (PIs) in biomedical research. This perspective examines how LLMs can reshape the laboratory model as de facto “Co-PIs” for tasks ranging from literature triage to hypothesis generation. By clarifying both opportunities and risks, we propose a framework for efficient AI collaboration which aims to guide investigators and trainees in harnessing LLMs responsibly
Lost time undermines return behavior
Get PDFPeople commonly experience long gaps of time between getting to do things they love to do. In principle, the longer it has been since people last enjoyed something, the quicker they should jump at the chance to enjoy it again. In practice, five experiments reveal a case of the opposite: The longer since people's last enjoyable experience, the more they postpone returning—in part because they demand their return be “extra special” to offset the wait. This effect emerged across many controlled parameters. For example, participants chose to avoid contacting close friends after large vs. small gaps in contact, all else equal—a choice that undermined their immediate happiness. This effect further extended to COVID-19 contexts, regarding people's returns from lengthy shutdowns: Somewhat nonobviously, we found that participants delayed returning to everyday activities even longer (as opposed to jumping back at their first sufficiently good chance) if it meant that they could better mark the occasion. Finally, this effect was uniquely attenuated by helping participants reconstrue any chance to return as “extra special.” Together, these findings suggest that time delays create psychological barriers to returning, which people self-impose. People may increasingly avoid contacting loved ones, getting back into rewarding hobbies, and so on, the longer it has been since last time, promoting vicious cycles of deferment. Motivating people to return to experiences that would enhance their immediate happiness—experiences they still want to have and are now theirs to take—may be surprisingly difficult
Investigating Statistical Conditions of Coevolutionary Signals that Enable Algorithmic Predictions of Protein Partners
Get PDFThis study examines the statistical conditions of coevolutionary signals that allow algorithmic predictions of protein partners based on amino acid sequences rather than 3D structures. It introduces a Markov stochastic model that predicts the number of correct protein partners based on coevolutionary information. The model defines state probabilities using a Poisson mixture of normal distributions, with key parameters including the total number of protein sequences M, the coevolutionary information gap α, and variance σ02. The model suggests that algorithmic approaches that maximize coevolutionary information cannot effectively resolve partners in protein families with a large number of sequences M ≥ 100. The model shows that true-positive (TP) rates can be enhanced by disregarding mismatches among similar sequences. This approach allows a distinction, in terms of {α, σ02}, between optimized solutions with trivial errors and other degenerate solutions. Our findings enable the a priori classification of protein families where partners can be reliably predicted by ignoring trivial errors between similar sequences, advancing the understanding of coevolutionary models for large protein data sets