Closed-loop transfer enables artificial intelligence to yield chemical knowledge.

Artificial intelligence-guided closed-loop experimentation has emerged as a promising method for optimization of objective functions1,2, but the substantial potential of this traditionally black-box approach to uncovering new chemical knowledge has remained largely untapped. Here we report the integration of closed-loop experiments with physics-based feature selection and supervised learning, denoted as closed-loop transfer (CLT), to yield chemical insights in parallel with optimization of objective functions. CLT was used to examine the factors dictating the photostability in solution of light-harvesting donor-acceptor molecules used in a variety of organic electronics applications, and showed fundamental insights including the importance of high-energy regions of the triplet state manifold. This was possible following automated modular synthesis and experimental characterization of only around 1.5% of the theoretical chemical space. This physics-informed model for photostability was strengthened using multiple experimental test sets and validated by tuning the triplet excited-state energy of the solvent to break out of the observed plateau in the closed-loop photostability optimization process. Further applications of CLT to additional materials systems support the generalizability of this strategy for augmenting closed-loop strategies. Broadly, these findings show that combining interpretable supervised learning models and physics-based features with closed-loop discovery processes can rapidly provide fundamental chemical insights.

From Solution to Thin Film: Molecular Assembly of π-Conjugated Systems and Impact on (Opto)electronic Properties.

The assembly of conjugated organic molecules from solution to solid-state plays a critical role in determining the thin film morphology and optoelectronic properties of solution-processed organic electronics and photovoltaics. During evaporative solution processing, π-conjugated systems can assemble via various forms of intermolecular interactions, forming distinct aggregate structures that can drastically tune the charge transport landscape in the solid-state. In blend systems composed of donor polymer and acceptor molecules, assembly of neat materials couples with phase separation and crystallization processes, leading to complex phase transition pathways which govern the blend film morphology. In this review, we provide an in-depth review of molecular assembly processes in neat conjugated polymers and nonfullerene small molecule acceptors and discuss their impact on the thin film morphology and optoelectronic properties. We then shift our focus to blend systems relevant to organic solar cells and discuss the fundamentals of phase transition and highlight how the assembly of neat materials and processing conditions can affect blend morphology and device performance.

A novel copper (II) binding peptide for a colorimetric biosensor system design.

Filamentous bacteriophages are viruses infecting only bacteria. In this study, phage display technique was applied to identify highly selective Cu(II) binding peptides. After five rounds of positive screening against Cu(II) and various rounds of negative screenings against competitive metal ions (Al(III), Co(II), Fe(III), Ni(II) and Zn(II)), bacteriophages were enriched. Selective Cu(II) binding of final phages was confirmed by Enzyme Linked Immunosorbent Assay (ELISA), Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray spectroscopy (EDX) analyses. 15 phage plaques were randomly selected and sequenced. Cu-5 peptide (HGFANVA) with the highest frequency of occurrence and the strongest Cu(II) affinity was chosen for further Cu(II) detection and removal tests. Inductively Coupled Plasma-Mass Spectrometry (ICP-MS) confirmed the strong Cu(II) binding potential of engineered viruses. Cu-5 peptides were synthetically synthesized with three Cysteine units at C-terminal and a AuNP-peptide biosensor system was developed based on aggregation behavior of AuNPs upon Cu(II) ion treatment. AuNP-based Cu(II) sensor was selective for Cu(II) and the LOD was 91.15 nM (ca. 5.8 × 10-3 mg/L; 3σ/k, n = 5, R2 = 0.992) for the case study which is considerably lower than the WHO's accepted guideline of 1.3 mg/L. This study provides an interdisciplinary approach to apply short peptides as recognition units for biosensor studies which are user friendly, not bulky and cost-effective.

Direct Conjugation of Streptavidin to Encoded Hydrogel Microparticles for Multiplex Biomolecule Detection with Rapid Probe-Set Modification.

Encoded hydrogel microparticles synthesized via flow lithography have drawn attention for multiplex biomarker detection due to their high multiplex capability and solution-like hybridization kinetics. However, the current methods for preparing particles cannot achieve a flexible, rapid probe-set modification, which is necessary for the production of various combinations of target panels in clinical diagnosis. In order to accomplish the unmet needs, streptavidin was incorporated into the encoded hydrogel microparticles to take advantage of the rapid streptavidin-biotin interactions that can be used in probe-set modification. However, the existing methods suffer from low efficiency of streptavidin conjugation, cause undesirable deformation of particles, and impair the assay capability. Here, we present a simple and powerful method to conjugate streptavidin to the encoded hydrogel microparticles for better assay performance and rapid probe-set modification. Streptavidin was directly conjugated to the encoded hydrogel microparticles using the aza-Michael addition click reaction, which can proceed in mild, aqueous condition without catalysts. A highly flexible and sensitive assay was developed to quantify DNA and proteins using streptavidin-conjugated encoded hydrogel microparticles. We also validated the potential applications of our particles conducting multiplex detection of cancer-related miRNAs.

Affinity-Enhanced CTC-Capturing Hydrogel Microparticles Fabricated by Degassed Mold Lithography.

Technologies for the detection and isolation of circulating tumor cells (CTCs) are essential in liquid biopsy, a minimally invasive technique for early diagnosis and medical intervention in cancer patients. A promising method for CTC capture, using an affinity-based approach, is the use of functionalized hydrogel microparticles (MP), which have the advantages of water-like reactivity, biologically compatible materials, and synergy with various analysis platforms. In this paper, we demonstrate the feasibility of CTC capture by hydrogel particles synthesized using a novel method called degassed mold lithography (DML). This technique increases the porosity and functionality of the MPs for effective conjugation with antibodies. Qualitative fluorescence analysis demonstrates that DML produces superior uniformity, integrity, and functionality of the MPs, as compared to conventional stop flow lithography (SFL). Analysis of the fluorescence intensity from porosity-controlled MPs by each reaction step of antibody conjugation elucidates that more antibodies are loaded when the particles are more porous. The feasibility of selective cell capture is demonstrated using breast cancer cell lines. In conclusion, using DML for the synthesis of porous MPs offers a powerful method for improving the cell affinity of the antibody-conjugated MPs.