Search for: All records

The United States has a wide range of institutions of higher education, from two-year community colleges that focus primarily on job training to the research universities that train the next generation of Ph.D. scientists and produce a large share of knowledge. Some research universities are private, and others are public. Most states have a public flagship university or two, along with many more regional colleges where research has less emphasis and a slew of two-year community or technical colleges as well. The U.S. is also home to liberal arts colleges, which have no Ph.D. programs but where under- graduates benefit from small classes and intensive hands-on research experiences with the faculty. Most liberal arts colleges in the United States are private, although some states support a public liberal arts college as well. The nonflagship state and other private universities that do not have Ph.D. programs in chemistry and liberal arts colleges are collectively known as predominately undergraduate institutions or PUIs. PUIs play an important part in the United States scientific infrastructure, as they excel at providing the initial training of undergraduates, who learn the scientific method by hands-on research with their faculty mentors. 

Routine investigations of plasmonic phenomena at the quantum level present a formidable computational challenge due to the large system sizes and ultrafast timescales involved. This Feature Article highlights the use of density functional tight-binding (DFTB), particularly its real-time time-dependent formulation (RT-TDDFTB), as a tractable approach to study plasmonic nanostructures from a purely quantum mechanical purview. We begin by outlining the theoretical framework and limitations of DFTB, emphasizing its efficiency in modeling systems with thousands of atoms over picosecond timescales. Applications of RT-TDDFTB are then explored in the context of optical absorption, nonlinear harmonic generation, and plasmon-mediated photocatalysis. We demonstrate how DFTB can reconcile classical and quantum descriptions of plasmonic behavior, capturing key phenomena such as size-dependent plasmon shifts and plasmon coupling in nanoparticle assemblies. Finally, we showcase DFTB’s ability to model hot carrier generation and reaction dynamics in plasmon-driven H2 dissociation, underscoring its potential to model photocatalytic processes. Collectively, these studies establish DFTB as a powerful, yet computationally efficient tool to probe the emergent physics of materials at the limits of space and time. 

Aluminum nanocrystals offer a promising platform for plasmonic photocatalysis, yet a detailed understanding of their electron dynamics and consequent photocatalytic performance has been challenging thus far due to computational limitations. Here, we employ density functional tight-binding methods (DFTB) to investigate the optical properties and H2 dissociation dynamics of Al nanocrystals with varying sizes and geometries. Our real-time simulations reveal that Al’s unique free-electron nature enables efficient light-matter interactions and rapid electronic thermalization. Cubic and octahedral nanocrystals ranging from 0.5 to 4.5 nm exhibit size-dependent plasmon resonances in the UV, with distinct spectral features arising from the particle geometry and electronic structure. By simulating H2 dissociation near Al nanocrystals, we demonstrate that hot electrons generated through plasmon excitation can overcome the molecule’s strong chemical bond within tens of femtoseconds. The laser intensity threshold is comparable to previous reports for Ag nanocrystals, though significantly lower than that of Au. Notably, the dipolar plasmon mode demonstrates higher efficiency for this reaction than the localized interband transition for particles at these sizes. Taken together, this work provides mechanistic insights into plasmon-driven catalysis and showcases DFTB’s capability to study quantum plasmonics at unprecedented length and time scales. 

This work presents a new approach for simulating the interaction between molecular aggregate systems and multi-modal energy–time entangled light by solving the Lindblad master equation. The density matrix that describes both molecular and photonic states is propagated on a time grid, with excited-state dephasing included via the Lindblad superoperator. Molecular exciton entanglement, induced by entangled photons, is analyzed from the time-evolved density matrix. The calculations are based on a model of a molecular dimer introduced by Bittner et al. [J. Chem. Phys. 152, 071101 (2020)], along with entangled light that is approximated by a finite number of modes. Our results demonstrate that photonic entanglement plays a significant role in influencing molecular exciton entanglement, highlighting the interplay between the photonic and excitonic subsystems in such interactions. 

Photochemistry is a powerful tool for synthesizing important molecules which are challenging to create without light. We report compelling results which indicate that photochemical reaction rates (oxygenation and cycloaddition) can be notably enhanced by utilizing a very small number of entangled photons. Measurements with the same small number of classical photons show the rate of product formation is considerably lower. This suggests that the reaction rate with entangled photons is enhanced by many orders of magnitude. Theoretical calculations show that classical photons and entangled photons excite the photocatalyst to different final excited states. This chemical synthesis approach with entangled photons could have a large impact on our understanding of chemical reactivity and provide new insights into photochemical processes. 

Vertebrate life histories evolve in response to selection imposed by abiotic and biotic environmental conditions while being limited by genetic, developmental, physiological, demographic and phylogenetic processes that constrain adaptation. Despite the well-recognized shifts in selective pressures accompanying transitions among environments, the conditions driving innovation and the consequences for life-history evolution remain outstanding questions. Here we compare the traits of vertebrates that occupy aquatic or terrestrial environments as juveniles to infer shifts in evolutionary constraints that explain differences in their life-history traits and thus their fundamental demographic rates. Our results emphasize the reduced potential for life-history diversification on land, especially that of reproductive strategies, which limits the scope of viable life-history strategies. Moreover, our study reveals differences between the evolution of viviparity in aquatic and terrestrial realms. Transitions from egg laying to live birth represent a major shift across life-history space for aquatic organisms, whereas terrestrial egg-laying organisms evolve live birth without drastic changes in life-history strategy. Whilst trade-offs in the allocation of resources place fundamental constraints on the way life histories can vary, ecological setting influences the position of species within the viable phenotypic space available for adaptive evolution. 

Abstract This paper presents a virtual patient generator (VPG) intended to be used for preclinical in silico evaluation of autonomous vasopressor administration algorithms in the setting of experimentally induced vasoplegia. Our VPG consists of two main components: (i) a mathematical model that replicates physiological responses to experimental vasoplegia (induced by sodium nitroprusside (SNP)) and vasopressor resuscitation via phenylephrine (PHP) and (ii) a parameter vector sample generator in the form of a multidimensional probability density function (PDF) using which the parameters characterizing the mathematical model can be sampled. We developed and validated a mathematical model capable of predicting physiological responses to the administration of SNP and PHP. Then, we developed a parameter vector sample generator using a collective variational inference method. In a blind testing, the VPG developed by combining the two could generate a large number of realistic virtual patients (VPs), which could simulate physiological responses observed in all the experiments: on the average, 98.1% and 74.3% of the randomly generated VPs were physiologically legitimate and adequately replicated the test subjects, respectively, and 92.4% of the experimentally observed responses could be covered by the envelope formed by the subject-replicating VPs. In sum, the VPG developed in this paper may be useful for preclinical in silico evaluation of autonomous vasopressor administration algorithms.