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  1. Lactones are cyclic esters with extensive applications in materials science, medicinal chemistry, and the food and perfume industries. Nature’s strategy for the synthesis of many lactones found in natural products always relies on a single type of retrosynthetic strategy, a C−O bond disconnection. Here, we describe a set of laboratory-engineered enzymes that use a new-tonature C−C bond-forming strategy to assemble diverse lactone structures. These engineered “carbene transferases” catalyze intramolecular carbene insertions into benzylic or allylic C−H bonds, which allow for the synthesis of lactones with different ring sizes and ring scaffolds from simple starting materials. Starting from a serine-ligated cytochrome P450 variant previously engineered for other carbene-transfer activities, directed evolution generated a variant P411-LAS-5247, which exhibits a high activity for constructing a five-membered ε-lactone, lactam, and cyclic ketone products (up to 5600 total turnovers (TTN) and >99% enantiomeric excess (ee)). Further engineering led to variants P411-LAS-5249 and P411-LAS-5264, which deliver six-membered δ-lactones and seven-membered ε-lactones, respectively, overcoming the thermodynamically unfavorable ring strain associated with these products compared to the γ-lactones. This new carbene-transfer activity was further extended to the synthesis of complex lactone scaffolds based on fused, bridged, and spiro rings. The enzymatic platform developed here complements natural biosynthetic strategies for lactone assembly and expands the structural diversity of lactones accessible through C−H functionalization. 
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    Free, publicly-accessible full text available January 17, 2025
  2. Free, publicly-accessible full text available November 28, 2024
  3. Abstract

    Wearable devices benefit from the use of stretchable conjugated polymers (CPs). Traditionally, the design of stretchable CPs is based on the assumption that a low elastic modulus (E) is crucial for achieving high stretchability. However, this research, which analyzes the mechanical properties of 65 CP thin films, challenges this notion. It is discovered that softness alone does not determine stretchability; rather, it is the degree of entanglement that is critical. This means that rigid CPs can also exhibit high stretchability, contradicting conventional wisdom. To inverstigate further, the mechanical behavior, electrical properties, and deformation mechanism of two model CPs: a glassy poly(3‐butylthiophene‐2,5‐diyl) (P3BT) with anEof 2.2 GPa and a viscoelastic poly(3‐octylthiophene‐2,5‐diyl) (P3OT) with anEof 86 MPa, are studied. Ex situ transmission X‐ray scattering and polarized UV–vis spectroscopy revealed that only the initial strain (i.e., <20%) exhibits different chain alignment mechanisms between two polymers, while both rigid and soft P3ATs showed similarly behavior at larger strains. By challenging the conventional design metric of lowEfor high stretchability and highlighting the importance of entanglement, it is hoped to broaden the range of CPs available for use in wearable devices.

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    Free, publicly-accessible full text available December 1, 2024
  4. Free, publicly-accessible full text available August 4, 2024
  5. A warehouse delivery problem consists of a set of robots that undertake delivery jobs within a warehouse. Items are moved around the warehouse in response to events. A solution to a warehouse delivery problem is a collision-free schedule of robot movements and actions that ensures that all delivery jobs are completed and each robot is returned to its docking station. While the warehouse delivery problem is related to existing research, such as the study of multi-agent path finding (MAPF), the specific industrial requirements necessitated a novel approach that diverges from these other approaches. For example, our problem description was more suited to formalizing the warehouse in terms of a weighted directed graph rather than the more common grid-based formalization. We formalize and encode the warehouse delivery problem in Answer Set Programming (ASP) extended with difference constraints. We systematically develop and study different encoding variants, with a view to computing good quality solutions in near real-time. In particular, application specific criteria are contrasted against the traditional notion of makespan minimization as a measure of solution quality. The encoding is tested against both crafted and industry data and experiments run using the Hybrid ASP solver clingo[dl]. 
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  6. Silicon photonic nanostructures with massive Dirac dispersion offer an opportunity for emulating relativistic trapping of light. 
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  7. Molecular doping can increase the conductivity of organic semiconductors and plays an increasingly important role in emerging and established plastic electronics applications. 4-(1,3-Dimethyl-2,3-dihydro-1 H -benzimidazol-2-yl)- N , N -dimethylaniline (N-DMBI-H) and tris(pentafluorophenyl)borane (BCF) are established n- and p-dopants, respectively, but neither functions as a simple one-electron redox agent. Molecular hydrogen has been suggested to be a byproduct in several proposed mechanisms for doping using both N-DMBI-H and BCF. In this paper we show for the first time the direct detection of molecular hydrogen in the uncatalysed doping of a variety of polymeric and molecular semiconductors using these dopants. Our results provide insight into the doping mechanism, providing information complementary to that obtained from more commonly applied methods such as optical, electron spin resonance, and electrical measurements. 
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  8. Pinpointing the geographic location of an IP address is important for a range of location-aware applications spanning from targeted advertising to fraud prevention. The majority of traditional measurement-based and recent learning-based methods either focus on the efficient employment of topology or utilize data mining to find clues of the target IP in publicly available sources. Motivated by the limitations in existing works, we propose a novel framework named GraphGeo, which provides a complete processing methodology for street-level IP geolocation with the application of graph neural networks. It incorporates IP hosts knowledge and kinds of neighborhood relationships into the graph to infer spatial topology for high-quality geolocation prediction. We explicitly consider and alleviate the negative impact of uncertainty caused by network jitter and congestion, which are pervasive in complicated network environments. Extensive evaluations across three large-scale real-world datasets demonstrate that GraphGeo significantly reduces the geolocation errors compared to the state-of-the-art methods. Moreover, the proposed framework has been deployed on the web platform as an online service for 6 months. 
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  9. Abstract

    CRISPR-Cas12a is an RNA-guided, programmable genome editing enzyme found within bacterial adaptive immune pathways. Unlike CRISPR-Cas9, Cas12a uses only a single catalytic site to both cleave target double-stranded DNA (dsDNA) (cis-activity) and indiscriminately degrade single-stranded DNA (ssDNA) (trans-activity). To investigate how the relative potency of cis- versus trans-DNase activity affects Cas12a-mediated genome editing, we first used structure-guided engineering to generate variants of Lachnospiraceae bacterium Cas12a that selectively disrupt trans-activity. The resulting engineered mutant with the biggest differential between cis- and trans-DNase activity in vitro showed minimal genome editing activity in human cells, motivating a second set of experiments using directed evolution to generate additional mutants with robust genome editing activity. Notably, these engineered and evolved mutants had enhanced ability to induce homology-directed repair (HDR) editing by 2–18-fold compared to wild-type Cas12a when using HDR donors containing mismatches with crRNA at the PAM-distal region. Finally, a site-specific reversion mutation produced improved Cas12a (iCas12a) variants with superior genome editing efficiency at genomic sites that are difficult to edit using wild-type Cas12a. This strategy establishes a pipeline for creating improved genome editing tools by combining structural insights with randomization and selection. The available structures of other CRISPR-Cas enzymes will enable this strategy to be applied to improve the efficacy of other genome-editing proteins.

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