Engineering topics

Tsai, Esther R.

Publications and source records attributed to Tsai, Esther R..

5 records

DOE OSTI2024

Template-Assisted Growth of High-Quality α-Phase FAPbI 3 Crystals in Perovskite Solar Cells Using Thiol-Functionalized MoS 2 Nanosheets

Formamidinium lead iodide (FAPI) has gained attention for hybrid perovskite solar cell (PSC) applications due to its enhanced stability and narrow bandgap. However, a significant challenge remains in inducing and stabilizing the elusive perovskite “black phase”—photoactive cubic α-FAPI—as the relatively bulky FA + cations tend to favor the thermodynamically stable nonphotoactive “yellow phase”. Here, in this study, we present a templated growth strategy employing thiol-functionalized MoS 2 nanosheets as templates. By introduction of 3-mercaptopropionic acid (MPA)-functionalized MoS 2 as a growth template, precise control over crystal formation was achieved, favoring the growth of high-quality α-FAPI films. These advanced templated films exhibited substantial improvements in charge transport properties, efficient light absorption, and enhanced charge extraction. As a result, the PSCs achieved a significantly enhanced power conversion efficiency (PCE) compared to the nontemplated control device, increasing from 20.6 to 22.5%. The MoS 2 -incorporated device also demonstrated excellent shelf stability, maintaining 91% of the initial PCE even after 1600 h of storage without device encapsulation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Assembling Vertical Block Copolymer Nanopores via Solvent Vapor Annealing on Homopolymer-Functionalized Substrates

Utilizing the self-assembly of block copolymers with large Flory–Huggins interaction parameters (χ) for nanofabrication is a formidable challenge due to the attendant large surface energy differences between the blocks. This work reports a robust protocol for the fabrication of thin films with highly ordered cylindrical nanopore arrays via the self-assembly of an asymmetric poly(styrene-block-4-vinylpyridine) (PS-b-P4VP) diblock copolymer blended with a P4VP homopolymer. The desired vertical domain orientation is achieved at the air–polymer interface by controlled solvent vapor annealing (SVA) using acetone, a solvent with weak selectivity for PS over P4VP, and at the substrate interface by functionalization using a hydroxy-terminated poly(2-vinylpyridine) (P2VP-OH) homopolymer brush. In contrast, the vertical cylinder orientation is unstable during acetone SVA on substrates functionalized using hydroxy-terminated poly(methyl methacrylate) (PMMA-OH). Although PMMA exhibits more balanced interfacial energies between PS and P4VP than P2VP in the dry state, it is also swollen more selectively by acetone. We hypothesize that the nearly balanced solvent swelling of the three polymers (P2VP, P4VP, and PS) stabilizes the vertical cylinder orientation, while unbalanced swelling (PMMA > P4VP and PS) does not. Here we further characterize pore formation by addition of a P4VP homopolymer and its postassembly extraction using ethanol, revealing a narrow window of pore size tunability. Notably, minimal differences in nanopore morphologies are observed for P4VP volume fractions as high as 0.1, regardless of the P4VP molar mass. However, further increasing the P4VP volume fraction results in domain reorientation or macrophase separation when its molar mass is less than or greater than the P4VP block molar mass, respectively. Using a P4VP homopolymer that is nearly equal in length to the P4VP block enables the fabrication of well-ordered arrays of vertical, through-film nanopores with high aspect ratios (>10), small periods (<23 nm), and diameters less than 10 nm.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

Solutions Are the Problem: Ordered Two-Dimensional Covalent Organic Framework Films by Chemical Vapor Deposition

Covalent organic frameworks (COFs) are a promising class of crystalline polymer networks that are useful due to their high porosity, versatile functionality, and tunable architecture. Conventional solution-based methods of producing COFs are marred by slow reactions that produce powders that are difficult to process into adaptable form factors for functional applications, and there is a need for facile and fast synthesis techniques for making crystalline and ordered covalent organic framework (COF) thin films. In this work, we report a chemical vapor deposition (CVD) approach utilizing co-evaporation of two monomers onto a heated substrate to produce highly crystalline, defect-free COF films and coatings with hydrazone, imine, and ketoenamine COF linkages. Further, this all-in-one synthesis technique produces highly crystalline, 40 nm–1 μm-thick COF films on Si/SiO2 substrates in less than 30 min. Crystallinity and alignment were proven by using a combination of grazing-incidence wide-angle X-ray scattering (GIWAXS) and transmission electron microscopy (TEM), and successful conversion of the monomers to produce the target COF was supported by Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), and UV–vis measurements. Additionally, we used atomic force microscopy (AFM) to investigate the growth mechanisms of these films, showing the coalescence of triangular crystallites into a smooth film. To show the wide applicability and scope of the CVD process, we also prepared crystalline ordered COF films with imine and ketoenamine linkages. These films show potential as high-quality size exclusion membranes, catalytic platforms, and organic transistors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Crystallization of binary nanocrystal superlattices and the relevance of short-range attraction

The synthesis of binary nanocrystal superlattices (BNSLs) enables the targeted integration of orthogonal physical properties, such as photoluminescence and magnetism, into a single superstructure, unlocking a vast design space for multifunctional materials. However, the formation mechanism of BNSLs remains poorly understood, restricting the prediction of the structure and properties of superlattices. Here we use a combination of in situ scattering and molecular simulation to elucidate the self-assembly of two common BNSLs (AlB 2 and NaZn 13 ) through emulsion templating. Our self-assembly experiments reveal that no intermediate structures precede the formation of the final binary phases, indicating that their formation proceeds through classical nucleation. Using simulations, we find that, despite the formation of AlB 2 and NaZn 13 typically being attributed to entropy, their self-assembly is most consistent with the nanocrystals possessing short-range interparticle attraction, which we find can accelerate nucleation kinetics in BNSLs. Here, we also find homogeneous, classical nucleation in simulations, corroborating our experiments. These results establish a robust correspondence between experiment and theory, paving the way towards prediction of BNSLs.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Non-Blind Deblurring for Fluorescence: A Deformable Latent Space Approach with Kernel Parameterization

We report N\non-blind deblurring (NBD) is a modeling method of the image deblurring problem in computer vision, where the blurring kernel is known or can be externally estimated. In this paper, we attempt to solve a parametric NBD problem, inspired by the simultaneous acquisition of ptychography and fluorescent imaging (FI). Ptychography is an imaging method that favors larger probes, i.e. convolutional kernels, while FI relies on a small probe for high resolution. Also, the kernel can be solved during ptychographic reconstruction. With Ptycho-FI using the same larger kernel, we can perform NBD on the blurred fluorescent images to achieve high-resolution FI, and thus speed up the experiments. To this end, we design a deep latent space deformation network that is directly parameterized by the kernel. The network consists of three components: encoder, deformer, and decoder, where the deformer is specifically meant to rectify the latent space representations of blurred images to a standard latent space, regardless of the kernel. The deformation network is trained with a two-stage training scheme. We conduct extensive experiments to confirm that our parametric model can adapt to drastically different blurring kernels and perform robust deblurring.

77 NANOSCIENCE AND NANOTECHNOLOGY↗