Publications

Abstract Allosteric transcription factors (aTFs) have proven widely applicable for biotechnology and synthetic biology as ligand-specific biosensors enabling real-time monitoring, selection and regulation of cellular metabolism. However, both the biosensor specificity and the correlation between ligand concentration and biosensor output signal, also known as the transfer function, often needs to be optimized before meeting application needs. Here, we present a versatile and high-throughput method to evolve and functionalize prokaryotic aTF specificity and transfer functions in a eukaryote chassis, namely baker’s yeast Saccharomyces cerevisiae . From a single round of directed evolution of the effector-binding domain (EBD) coupled with various toggled selection regimes, we robustly select aTF variants of the cis, cis -muconic acid-inducible transcription factor BenM evolved for change in ligand specificity, increased dynamic output range, shifts in operational range, and a complete inversion of function from activation to repression. Importantly, by targeting only the EBD, the evolved biosensors display DNA-binding affinities similar to BenM, and are functional when ported back into a non-native prokaryote chassis. The developed platform technology thus leverages aTF evolvability for the development of new host-agnostic biosensors with user-defined small-molecule specificities and transfer functions.

High-valent multimetallic-oxo/oxyl species have been implicated as intermediates in oxidative catalysis involving proton-coupled electron transfer (PCET) reactions, but the reactive nature of these oxo species has hindered the development of an in-depth understanding of their mechanisms and multimetallic character. The mechanism of C-H oxidation by previously reported RuCo₃O₄ cubane complexes bearing a terminal Ru^V-oxo ligand, with significant oxyl radical character, was investigated. The rate-determining step involves H atom abstraction (HAA) from an organic substrate to generate a Ru-OH species and a carbon-centered radical. Radical intermediates are subsequently trapped by another equivalent of the terminal oxo to afford isolable radical-trapped cubane complexes. Density functional theory (DFT) reveals a barrierless radical combination step that is more favorable than an oxygen-rebound mechanism by 12.3 kcal mol^-1. This HAA reactivity to generate organic products is influenced by steric congestion and the C-H bond dissociation energy of the substrate. Tuning the electronic properties of the cubane (i.e., spin density localized on terminal oxo, basicity, and redox potential) by varying the donor ability of ligands at the Co sites modulates C-H activations by the Ru^V-oxo fragment and enables construction of structure-activity relationships. These results reveal a mechanistic pathway for C-H activation by high-valent metal-oxo species with oxyl radical character and provide insights into cooperative effects of multimetallic centers in tuning PCET reactivity.

Morphological control of nanocrystals has become increasingly important, as many of their physical and chemical properties are highly shape-dependent. Nanocrystal shape control for both single and multiple material systems, however, remains fairly empirical and challenging. New methods need to be explored for the rational synthetic design of heterostructures with controlled morphology. Overgrowth of a different material on well-faceted seeds, for example, allows for the use of the defined seed morphology to control nucleation and growth of the secondary structure. Here, we have used highly faceted cubic Pt seeds to direct the epitaxial overgrowth of a secondary metal. We demonstrate this concept with lattice matched Pd to produce conformal shape-controlled core-shell particles, and then extend it to lattice mismatched Au to give anisotropic growth. Seeding with faceted nanocrystals may have significant potential towards the development of shape-controlled heterostructures with defined interfaces.

An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Large language model (LLM) applications are evolving beyond simple chatbots into dynamic, general-purpose agentic programs, which scale LLM calls and output tokens to help AI agents reason, explore, and solve complex tasks. However, existing LLM serving systems ignore dependencies between programs and calls, missing significant opportunities for optimization. Our analysis reveals that programs submitted to LLM serving engines experience long cumulative wait times, primarily due to head-of-line blocking at both the individual LLM request and the program. To address this, we introduce Autellix, an LLM serving system that treats programs as first-class citizens to minimize their end-to-end latencies. Autellix intercepts LLM calls submitted by programs, enriching schedulers with program-level context. We propose two scheduling algorithms-for single-threaded and distributed programs-that preempt and prioritize LLM calls based on their programs' previously completed calls. Our evaluation demonstrates that across diverse LLMs and agentic workloads, Autellix improves throughput of programs by 4-15x at the same latency compared to state-of-the-art systems, such as vLLM.

In this paper, we propose a new model for practical, nano-scale, NbO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -based Mott memristors, which is based on a thorough analysis performed on a recently presented physics-based model for these devices. Our investigations revealed that the 3D Poole-Frenkel conduction mechanism adopted in the aforementioned model, can be well-approximated by a transport equation in which: a) memristor current is expressed as a linear function of memristor voltage and b) the device memductance is solely dependent on the device temperature which represents the memristor state. The resulting simplified mathematical form of the original differential algebraic equation set is not only more suitable for simulating large-scale, nano-scale NbO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -based memristor circuits, but is also ideal for circuit-theoretic investigations which may allow an in depth understanding of the peculiar nonlinear behaviors of these devices.

Author(s): Thompson, Mitchell G; Incha, Matthew R; Pearson, Allison N; Schmidt, Matthias; Sharpless, William A; Eiben, Christopher B; Cruz-Morales, Pablo; Blake-Hedges, Jacquelyn M; Liu, Yuzhong; Adams, Catharine A; Haushalter, Robert W; Krishna, Rohith N; Lichtner, Patrick; Blank, Lars M; Mukhopadhyay, Aindrila; Deutschbauer, Adam M; Shih, Patrick M; Keasling, Jay D

We report on temperature-dependent charge and magneto transport of chemically doped MoS2, p-type molybdenum disulfide degenerately doped with niobium (MoS2:Nb). The temperature dependence of the electrical resistivity is characterized by a power law, ρ(T) ∼ T−0.25, which indicates that the system resides within the critical regime of the metal-insulator (M-I) transition. By applying high magnetic field (∼7 T), we observed a 20% increase in the resistivity at 2 K. The positive magnetoresistance shows that charge transport in this system is governed by the Mott-like three-dimensional variable range hopping (VRH) at low temperatures. According to relationship between magnetic-field and temperature dependencies of VRH resistivity, we extracted a characteristic localization length of 19.8 nm for MoS2:Nb on the insulating side of the M-I transition.

In this paper, we present BlinkDB, a massively parallel, approximate query engine for running interactive SQL queries on large volumes of data. BlinkDB allows users to trade-off query accuracy for response time, enabling interactive queries over massive data by running queries on data samples and presenting results annotated with meaningful error bars. To achieve this, BlinkDB uses two key ideas: (1) an adaptive optimization framework that builds and maintains a set of multi-dimensional stratified samples from original data over time, and (2) a dynamic sample selection strategy that selects an appropriately sized sample based on a query's accuracy or response time requirements. We evaluate BlinkDB against the well-known TPC-H benchmarks and a real-world analytic workload derived from Conviva Inc., a company that manages video distribution over the Internet. Our experiments on a 100 node cluster show that BlinkDB can answer queries on up to 17 TBs of data in less than 2 seconds (over 200 x faster than Hive), within an error of 2-10%.

By controlling off-stoichiometry, LiFe_0.6Mn_0.4PO₄with non-crystalline surface phases is formed, enabling the material to achieve high power density.