The ability to generate novel utterances compositionally using generative knowledge is a hallmark property of human language. At the same time, languages contain non-compositional or idiosyncratic items, such as irregular verbs, idioms, etc. This dissertation asks how and why language achieves a balance between these two systems—generative and item-specific—from both the synchronic and diachronic perspectives.

Specifically, I focus on the case of binomial expressions of the form “X and Y”, whose word order preferences (e.g. bread and butter/#butter and bread) are

xiipotentially determined by both generative and item-specific knowledge. I show that ordering preferences for these expressions indeed arise in part from violable generative constraints on the phonological, semantic, and lexical properties of the constituent words, but that expressions also have their own idiosyncratic preferences. I argue that both the way these preferences manifest diachronically and the way they are processed synchronically is constrained by the fact that speakers have finite experience with any given expression: in other words, the ability to learn and transmit idiosyncratic preferences for an expression is constrained by how frequently it is used. The finiteness of the input leads to a rational solution in which processing of these expression relies gradiently upon both generative and item-specific knowledge as a function of expression frequency, with lower frequency items primarily recruiting generative knowledge and higher frequency items relying more upon item-specific knowledge. This gradient processing in turn combines with the bottleneck effect of cultural transmission to perpetuate across generations a frequency-dependent balance of compositionality and idiosyncrasy in the language, in which higher frequency expressions are gradiently more idiosyncratic. I provide evidence for this gradient, frequency-dependent trade-off of generativity and item-specificity in both language processing and language structure using behavioral experiments, corpus data, and computational modeling.

What makes some sentences more difficult to process, and why? Memory- and expectation-based theories both attempt to explain sentence processing difficulties, and decades of sentence processing literature have found evidence in support of both theories. This dissertation further investigates these theories of sentence processing by exploring processing of subject- and object-extracted relative clauses (SRCs and ORCs) in Modern Standard Arabic, and how expectations affect the resulting interpretation of low-frequency structures. We investigate this question through various experimental paradigms. We first tested memory- versus expectation-based theories using a self-paced reading task. Results showed longer reading times for ORCs, supporting expectation-based theories, with difficulty localized at the relative clause noun phrase. We also found that misinterpretations were more frequent for ORCs, suggesting possible misreading as SRCs or good-enough and noisy-channel processing. To investigate this phenomenon, we conducted a recall task where participants re-wrote sentences word-for-word. Errors showed both ORCs being re-written as SRCs and vice versa, supporting good-enough and noisy-channel processing theories. We then explicitly tested the possibility of misreading versus good-enough or noisy-channel processing through eye-tracking. Findings indicated that readers were not misreading ORCs, but instead accepting noisy SRC interpretations. Finally, we explored the impact of grammatical cues versus statistical expectations in a second eye-tracking experiment. Results showed that increasing grammatical cues in favor of a veridical ORC interpretation did not significantly affect noisy interpretations or processing behaviors, indicating that grammatical cues were insufficient to override statistical expectations in a good-enough or noisy-channel framework.

Over the past 100 years, the perovskite structure-type has become ubiquitous in materials science. Although the conventional perovskite structure is simple, it can accommodate many different combinations of ions, producing a wide range of functional materials. Additionally, even ions that cannot form a conventional perovskite can form perovskite-derived structures such as 2D layered perovskites, double perovskites, or ordered-vacancy perovskites. In order to tailor these materials to specific applications, it is critical to develop an understanding of how the chemical makeup and crystal structures of these materials impact their properties. Additionally, the role of different synthetic approaches cannot be overlooked. In this work, I will discuss work connecting structure with properties in several perovskite-derived systems, with a focus on three different applications. Specifically, I will emphasize the use of both experimental and computational techniques to understand the specific origins of the material properties of interest.

First, I will discuss a series of compounds with the overall formula Cs 3 Bi 2 (Cl 1−x I x ) 9 . Interestingly, the compositions with a mixture of Cl and I take on a 2D ordered-vacancy perovskite structure which is distinct from the structures formed by the end members. Additionally, when synthesizing these compounds by solution-process methods, the products are unexpectedly iodine-rich compared to the initial stoichiometry of the reix action. The origin of the driving force for I incorporation and effect on optoelectronic properties was studied by experiment and computation, and appears to be closely connected to the formation of the 2D structure-type.

Next, I introduce vacancy-ordered perovskite structures based on W and Mo. First, I discuss the air-free and anhydrous synthesis and characterization of compounds with the composition A 2 WCl 6 . These compounds show unusual temperature-dependent magnetism which suggests a need for a better theoretical understanding of d 2 magnetic ions. Additionally, I compare my materials with those reported in the literature which were synthesized by hydrothermal methods. The hydrothermal compounds have the formula Cs 2 MO x X 6–x , where M is Mo or W and X is Cl or Br. These compounds show exceptional near-IR luminescence, and the origin of this emission has been examined in detail.

Finally, I discuss a screening process for the identification of materials with low dielectric constants (κ). Computational estimates suggested that the compound Al(HCOO) 3 , which has the ReO 3 structure-type, should have a favorable dielectric constant. However, experiments revealed that the true dielectric constant is larger than predicted. Explanations for the discrepancy between theory and experiment are discussed in order to further improve our guidelines for the identification of low-κ materials.