Beyond Thin Films: Clarifying the Impact of c-Li15Si4 Formation in Thin Film, Nanoparticle, and Porous Si Electrodes.

The formation of the c-Li15Si4 phase has well-established detrimental effects on the capacity retention of thin film silicon electrodes. However, the role of this crystalline phase with respect to the loss of capacity is somewhat ambiguous in nanoscale morphologies. In this work, three silicon-based morphologies are examined, including planar films, porous planar films, and silicon nanoparticle composite powder electrodes. The cycling conditions are used as the lever to induce, or not induce, the formation of c-Li15Si4 through application of constant-current (CC) or constant-current constant-voltage (CCCV) steps. In this manner, the role of this phase on capacity retention and Coulombic efficiency can be determined with few other convoluting factors such as alteration of the composition or morphology of the silicon electrodes themselves. The results here confirm that the c-Li15Si4 phase increases the rate of capacity decay in planar films but has no major effect on capacity retention in half-cells based on porous silicon films or silicon nanoparticle composite powder electrodes, although this conclusion is nuanced. Besides using a constant-voltage step, formation of the c-Li15Si4 phase is influenced by the dimensions of the Si material and the lithiation cutoff voltage. Porous Si films, which, in this work, comprise primary Si particle sizes that are smaller than those in the preformed Si nanoparticle slurries, do not undergo the formation of c-Li15Si4 at 50 mV, whereas Si nanoparticle slurries are accompanied by the formation of c-Li15Si4 up to 80 mV. The solid-electrolyte interphase (SEI) formed from reaction of the c-Li15Si4 with the carbonate-based electrolyte causes polarization in both nanoparticle and porous film silicon electrodes and lowers the average Coulombic efficiency. A comparison of the cumulative irreversibilities due to SEI formation between different lithiation cutoff voltages in silicon nanoparticle slurry electrodes confirmed the connection between higher SEI buildup and formation of the c-Li15Si4 phase. This work indicates that concerns about the c-Li15Si4 phase in silicon nanoparticles and porous silicon electrodes should mainly focus on the stability of the SEI and a reduction of irreversible electrolyte reactions.

Solvent Vapor Annealing, Defect Analysis, and Optimization of Self-Assembly of Block Copolymers Using Machine Learning Approaches.

Self-assembly of block copolymers (BCPs) is an alternative patterning technique that promises high resolution and density multiplication with lower costs. The defectivity of the resulting nanopatterns remains too high for many applications in microelectronics and is exacerbated by small variations of processing parameters, such as film thickness, and fluctuations of solvent vapor pressure and temperature, among others. In this work, a solvent vapor annealing (SVA) flow-controlled system is combined with design of experiments (DOE) and machine learning (ML) approaches. The SVA flow-controlled system enables precise optimization of the conditions of self-assembly of the high Flory-Huggins interaction parameter (χ) hexagonal dot-array forming BCP, poly(styrene-b-dimethylsiloxane) (PS-b-PDMS). The defects within the resulting patterns at various length scales are then characterized and quantified. The results show that the defectivity of the resulting nanopatterned surfaces is highly dependent upon very small variations of the initial film thicknesses of the BCP, as well as the degree of swelling under the SVA conditions. These parameters also significantly contribute to the quality of the resulting pattern with respect to grain coarsening, as well as the formation of different macroscale phases (single and double layers and wetting layers). The results of qualitative and quantitative defect analyses are then compiled into a single figure of merit (FOM) and are mapped across the experimental parameter space using ML approaches, which enable the identification of the narrow region of optimum conditions for SVA for a given BCP. The result of these analyses is a faster and less resource intensive route toward the production of low-defectivity BCP dot arrays via rational determination of the ideal combination of processing factors. The DOE and machine learning-enabled approach is generalizable to the scale-up of self-assembly-based nanopatterning for applications in electronic microfabrication.

Bipolar Resistive Switching in Junctions of Gallium Oxide and p-type Silicon.

In this work, native GaOx is positioned between bulk gallium and degenerately doped p-type silicon (p+-Si) to form Ga/GaOx/SiOx/p+-Si junctions. These junctions show memristive behavior, exhibiting large current-voltage hysteresis. When cycled between -2.5 and 2.5 V, an abrupt insulator-metal transition is observed that is reversible when the polarity is reversed. The ON/OFF ratio between the high and low resistive states in these junctions can reach values on the order of 108 and retain the ON and OFF resistive states for up to 105 s with an endurance exceeding 100 cycles. The presence of a nanoscale layer of gallium oxide is critical to achieving reversible resistive switching by formation and dissolution of the gallium filament across the switching layer.

Optimization of the Bulk Heterojunction of All-Small-Molecule Organic Photovoltaics Using Design of Experiment and Machine Learning Approaches.

All-small-molecule organic photovoltaic (OPV) cells based upon the small-molecule donor, DRCN5T, and nonfullerene acceptors, ITIC, IT-M, and IT-4F, were optimized using Design of Experiments (DOE) and machine learning (ML) approaches. This combination enables rational sampling of large parameter spaces in a sparse but mathematically deliberate fashion and promises economies of precious resources and time. This work focused upon the optimization of the core layer of the OPV device, the bulk heterojunction (BHJ). Many experimental processing parameters play critical roles in the overall efficiency of a given device and are often correlated and thus are difficult to parse individually. DOE was applied to the (i) solution concentration of the donor and acceptor ink used for spin-coating, (ii) the donor fraction, (iii) the temperature, and (iv) duration of the annealing of these films. The ML-based approach was then used to derive maps of the power conversion efficiencies (PCE) landscape for the first and second rounds of optimization to be used as guides to determine the optimal values of experimental processing parameters with respect to PCE. This work shows that with little knowledge of a potential combination of components for a given BHJ, a large parameter space can be effectively screened and investigated to rapidly determine its potential for high-efficiency OPVs.

van der Waals Epitaxy of Soft Twisted Bilayers: Lattice Relaxation and Mass Density Waves.

Interfaces comprising incommensurate or twisted hexagonal lattices are ubiquitous and of great interest, from adsorbed organic/inorganic interfaces in electronic devices, to superlubricants, and more recently to van der Waals bilayer heterostructures (vdWHs) of graphene and other 2D materials that demonstrate a range of properties such as superconductivity and ferromagnetism. Here we show how growth of 2D crystalline domains of soft block copolymers (BCPs) on patterned hard hexagonal lattices provide fundamental insights into van der Waals heteroepitaxy. At moderate registration forces, it is experimentally found that these BCP-hard lattice vdWHs do not adopt a simple moiré superstructure, but instead adopt local structural relaxations known as mass density waves (MDWs). Simulations reveal that MDWs are a primary mechanism of energy minimization and are the origin of the observed preferential twist angle between the lattices.

Redox Flow Batteries: How to Determine Electrochemical Kinetic Parameters.

Redox flow batteries (RFBs) are promising energy storage candidates for grid deployment of intermittent renewable energy sources such as wind power and solar energy. Various new redox-active materials have been introduced to develop cost-effective and high-power-density next-generation RFBs. Electrochemical kinetics play critical roles in influencing RFB performance, notably the overpotential and cell power density. Thus, determining the kinetic parameters for the employed redox-active species is essential. In this Perspective, we provide the background, guidelines, and limitations for a proposed electrochemical protocol to define the kinetics of redox-active species in RFBs.

Water-soluble pH-switchable cobalt complexes for aqueous symmetric redox flow batteries.

A water soluble octahedral Co(ii) complex, BCPIP-Co(ii), with 4 appended carboxylic groups on the ligand periphery is utilized as both posolyte and negolyte in an aqueous, symmetric redox flow battery (RFB). The full RFB demonstrates coulombic efficiencies >99% for up to 100 cycles.

How To Optimize Materials and Devices via Design of Experiments and Machine Learning: Demonstration Using Organic Photovoltaics.

Most discoveries in materials science have been made empirically, typically through one-variable-at-a-time (Edisonian) experimentation. The characteristics of materials-based systems are, however, neither simple nor uncorrelated. In a device such as an organic photovoltaic, for example, the level of complexity is high due to the sheer number of components and processing conditions, and thus, changing one variable can have multiple unforeseen effects due to their interconnectivity. Design of Experiments (DoE) is ideally suited for such multivariable analyses: by planning one's experiments as per the principles of DoE, one can test and optimize several variables simultaneously, thus accelerating the process of discovery and optimization while saving time and precious laboratory resources. When combined with machine learning, the consideration of one's data in this manner provides a different perspective for optimization and discovery, akin to climbing out of a narrow valley of serial (one-variable-at-a-time) experimentation, to a mountain ridge with a 360° view in all directions.

Vapor-Phase Nanopatterning of Aminosilanes with Electron Beam Lithography: Understanding and Minimizing Background Functionalization.

Electron beam lithography (EBL) is a highly precise, serial method for patterning surfaces. Positive tone EBL resists enable patterned exposure of the underlying surface, which can be subsequently functionalized for the application of interest. In the case of widely used native oxide-capped silicon surfaces, coupling an activated silane with electron beam lithography would enable nanoscale chemical patterning of the exposed regions. Aminoalkoxysilanes are extremely useful due to their reactive amino functionality but have seen little attention for nanopatterning silicon surfaces with an EBL resist due to background contamination. In this work, we investigated three commercial positive tone EBL resists, PMMA (950k and 495k) and ZEP520A (57k), as templates for vapor-phase patterning of two commonly used aminoalkoxysilanes, 3-aminopropyltrimethoxysilane (APTMS) and 3-aminopropyldiisopropylethoxysilane (APDIPES). The PMMA resists were susceptible to significant background reaction within unpatterned areas, a problem that was particularly acute with APTMS. On the other hand, with both APTMS and APDIPES exposure, unpatterned regions of silicon covered by the ZEP520A resist emerged pristine, as shown both with SEM images of the surfaces of the underlying silicon and through the lack of electrostatically driven binding of negatively charged gold nanoparticles. The ZEP520A resist allowed for the highly selective deposition of these alkoxyaminosilanes in the exposed areas, leaving the unpatterned areas clean, a claim also supported by contact angle measurements with four probe liquids and X-ray photoelectron spectroscopy (XPS). We investigated the mechanistic reasons for the stark contrast between the PMMA resists and ZEP520A, and it was found that the efficacy of resist removal appeared to be the critical factor in reducing the background functionalization. Differences in the molecular weight of the PMMA resists and the resulting influence on APTMS diffusion through the resist films are unlikely to have a significant impact. Area-selective nanopatterning of 15 nm gold nanoparticles using the ZEP520A resist was demonstrated, with no observable background conjugation noted in the unexposed areas on the silicon surface by SEM.

Understanding the Effects of a High Surface Area Nanostructured Indium Tin Oxide Electrode on Organic Solar Cell Performance.

Organic solar cells (OSCs) are a complex assembly of disparate materials, each with a precise function within the device. Typically, the electrodes are flat, and the device is fabricated through a layering approach of the interfacial layers and photoactive materials. This work explores the integration of high surface area transparent electrodes to investigate the possible role(s) a three-dimensional electrode could take within an OSC, with a BHJ composed of a donor-acceptor combination with a high degree of electron and hole mobility mismatch. Nanotree indium tin oxide (ITO) electrodes were prepared via glancing angle deposition, structures that were previously demonstrated to be single-crystalline. A thin layer of zinc oxide was deposited on the ITO nanotrees via atomic layer deposition, followed by a self-assembled monolayer of C60-based molecules that was bound to the zinc oxide surface through a carboxylic acid group. Infiltration of these functionalized ITO nanotrees with the photoactive layer, the bulk heterojunction comprising PC71BM and a high hole mobility low band gap polymer (PDPPTT-T-TT), led to families of devices that were analyzed for the effect of nanotree height. When the height was varied from 0 to 50, 75, 100, and 120 nm, statistically significant differences in device performance were noted with the maximum device efficiencies observed with a nanotree height of 75 nm. From analysis of these results, it was found that the intrinsic mobility mismatch between the donor and acceptor phases could be compensated for when the electron collection length was reduced relative to the hole collection length, resulting in more balanced charge extraction and reduced recombination, leading to improved efficiencies. However, as the ITO nanotrees increased in height and branching, the decrease in electron collection length was offset by an increase in hole collection length and potential deleterious electric field redistribution effects, resulting in decreased efficiency.

Preferential Alignment of Incommensurate Block Copolymer Dot Arrays Forming Moiré Superstructures.

Block copolymer (BCP) self-assembly is of great interest as a cost-effective method for large-scale, high-resolution nanopattern fabrication. Directed self-assembly can induce long-range order and registration, reduce defect density, and enable access to patterns of higher complexity. Here we demonstrate preferential orientation of two incommensurate BCP dot arrays. A bottom layer of hexagonal silica dots is prepared via typical self-assembly from a PS-b-PDMS block copolymer. Self-assembly of a second, or top, layer of a different PS-b-PDMS block copolymer that forms a hexagonal dot pattern with different periodicity results in a predictable moiré superstructure. Four distinct moiré superstructures were demonstrated through a combination of different BCPs and different order of annealing. The registration force of the bottom layer of hexagonal dots is sufficient to direct the self-assembly of the top layer to adopt a preferred relative angle of rotation. Large-area helium ion microscopy imaging enabled quantification of the distributions of relative rotations between the two lattices in the moiré superstructures, yielding statistically meaningful results for each combination. It was also found that if the bottom layer dots were too large, the resulting moiré pattern was lost. A small reduction in the bottom layer dot size, however, resulted in large-area moiré superstructures, suggesting a specific size regime where interlayer registration forces can induce long-range preferential alignment of incommensurate BCP dot arrays.

Role of Interfacial Layers in Organic Solar Cells: Energy Level Pinning versus Phase Segregation.

Organic photovoltaics (OPVs) are assembled from a complex ensemble of layers of disparate materials, each playing a distinct role within the device. In this work, the role of the interface that bridges the transparent anode and the bulk heterojunction (BHJ) in an OPV device was investigated. The surface characteristics of the electrode interface affect the energy level alignment, phase segregation, and the local composition of the bulk heterojunction (BHJ), which is in close contact. The commonly used ITO/PEDOT:PSS electrode was tailored with a thin, low-band-gap polymer overlayer, called PBDTTPD-COOH, a variant of the established donor polymer, PBDTTPD. Three BHJs that were composed of a donor polymer and PC71BM, were examined, including the donor polymers PBDTTPD, PCDTBT, and PTB7, within the following OPV device stack: ITO/(interfacial layer or layers)/BHJ/LiF/Al/Mg. It was found that modification of the ITO/PEDOT:PSS electrode with PBDTTPD-COOH resulted in statistically significant increases of power conversion efficiency for the PBDTTPD- and PCDTBT-based donor polymer:PC71BM BHJs, but not for the PTB7:PC71BM BHJ. Ultraviolet photoelectron spectroscopy (UPS) enabled determination of the respective energy level diagrams for these three different polymers relative to the ITO/PEDOT:PSS/PBDTTPD-COOH electrode, and revealed no injection barrier in all three polymer/substrate pairs. The observed differences of efficiency were not, therefore, electronic in origin. ToF-SIMS depth profiling and detailed experiments to determine surface energies strongly suggested that the greatest factor influencing device performance was a significant change of the local composition of the BHJ at this interface. When favorable accumulation of the donor polymer at the PEDOT: PSS/interfacial layer was observed, the result was higher OPV device efficiencies. These results suggest that for each BHJ, the surface energies of the electrodes need to be carefully considered, as they will influence the local composition of the BHJ and resulting device performance.

Sequential Nanopatterned Block Copolymer Self-Assembly on Surfaces.

Bottom-up self-assembly of high-density block-copolymer nanopatterns is of significant interest for a range of technologies, including memory storage and low-cost lithography for on-chip applications. The intrinsic or native spacing of a given block copolymer is dependent upon its size (N, degree of polymerization), composition, and the conditions of self-assembly. Polystyrene-block-polydimethylsiloxane (PS-b-PDMS) block copolymers, which are well-established for the production of strongly segregated single-layer hexagonal nanopatterns of silica dots, can be layered sequentially to produce density-doubled and -tripled nanopatterns. The center-to-center spacing and diameter of the resulting silica dots are critical with respect to the resulting double- and triple-layer assemblies because dot overlap reduces the quality of the resulting pattern. The addition of polystyrene (PS) homopolymer to PS-b-PDMS reduces the size of the resulting silica dots but leads to increased disorder at higher concentrations. The quality of these density-multiplied patterns can be calculated and predicted using parameters easily derived from SEM micrographs of corresponding single and multilayer patterns; simple geometric considerations underlie the degree of overlap of dots and layer-to-layer registration, two important factors for regular ordered patterns, and clearly defined dot borders. Because the higher-molecular-weight block copolymers tend to yield more regular patterns than smaller block copolymers, as defined by order and dot circularity, this sequential patterning approach may provide a route toward harnessing these materials, thus surpassing their native feature density.

Nanoscale plasmonic stamp lithography on silicon.

Nanoscale lithography on silicon is of interest for applications ranging from computer chip design to tissue interfacing. Block copolymer-based self-assembly, also called directed self-assembly (DSA) within the semiconductor industry, can produce a variety of complex nanopatterns on silicon, but these polymeric films typically require transformation into functional materials. Here we demonstrate how gold nanopatterns, produced via block copolymer self-assembly, can be incorporated into an optically transparent flexible PDMS stamp, termed a plasmonic stamp, and used to directly functionalize silicon surfaces on a sub-100 nm scale. We propose that the high intensity electric fields that result from the localized surface plasmons of the gold nanoparticles in the plasmonic stamps upon illumination with low intensity green light, lead to generation of electron-hole pairs in the silicon that drive spatially localized hydrosilylation. This approach demonstrates how localized surface plasmons can be used to enable functionalization of technologically relevant surfaces with nanoscale control.

Hybrid device employing three-dimensional arrays of MnO in carbon nanosheets bridges battery-supercapacitor divide.

It is a challenge to meld the energy of secondary batteries with the power of supercapacitors. Herein, we created electrodes finely tuned for this purpose, consisting of a monolayer of MnO nanocrystallites mechanically anchored by pore-surface terminations of 3D arrays of graphene-like carbon nanosheets ("3D-MnO/CNS"). The biomass-derived carbon nanosheets should offer a synthesis cost advantage over comparably performing designer nanocarbons, such as graphene or carbon nanotubes. High Li storage capacity is achieved by bulk conversion and intercalation reactions, while high rates are maintained through stable ∼20 nm scale diffusion distances. For example, 1332 mAh g(-1) is reached at 0.1 A g(-1), 567 mAh g(-1) at 5 A g(-1), and 285 mAh g(-1) at 20 A g(-1) with negligible degradation at 500 cycles. We employed 3D-MnO/CNS (anode) and carbon nanosheets (cathode) to create a hybrid capacitor displaying among the most promising performances reported: based on the active materials, it delivers 184 Wh kg(-1) at 83 W kg(-1) and 90 Wh kg(-1) at 15 000 W kg(-1) with 76% capacity retention after 5000 cycles.

Carbon nanosheet frameworks derived from peat moss as high performance sodium ion battery anodes.

We demonstrate that peat moss, a wild plant that covers 3% of the earth's surface, serves as an ideal precursor to create sodium ion battery (NIB) anodes with some of the most attractive electrochemical properties ever reported for carbonaceous materials. By inheriting the unique cellular structure of peat moss leaves, the resultant materials are composed of three-dimensional macroporous interconnected networks of carbon nanosheets (as thin as 60 nm). The peat moss tissue is highly cross-linked, being rich in lignin and hemicellulose, suppressing the nucleation of equilibrium graphite even at 1100 °C. Rather, the carbons form highly ordered pseudographitic arrays with substantially larger intergraphene spacing (0.388 nm) than graphite (c/2 = 0.3354 nm). XRD analysis demonstrates that this allows for significant Na intercalation to occur even below 0.2 V vs Na/Na(+). By also incorporating a mild (300 °C) air activation step, we introduce hierarchical micro- and mesoporosity that tremendously improves the high rate performance through facile electrolyte access and further reduced Na ion diffusion distances. The optimized structures (carbonization at 1100 °C + activation) result in a stable cycling capacity of 298 mAh g(-1) (after 10 cycles, 50 mA g(-1)), with ∼150 mAh g(-1) of charge accumulating between 0.1 and 0.001 V with negligible voltage hysteresis in that region, nearly 100% cycling Coulombic efficiency, and superb cycling retention and high rate capacity (255 mAh g(-1) at the 210th cycle, stable capacity of 203 mAh g(-1) at 500 mA g(-1)).

Interconnected carbon nanosheets derived from hemp for ultrafast supercapacitors with high energy.

We created unique interconnected partially graphitic carbon nanosheets (10-30 nm in thickness) with high specific surface area (up to 2287 m(2) g(-1)), significant volume fraction of mesoporosity (up to 58%), and good electrical conductivity (211-226 S m(-1)) from hemp bast fiber. The nanosheets are ideally suited for low (down to 0 °C) through high (100 °C) temperature ionic-liquid-based supercapacitor applications: At 0 °C and a current density of 10 A g(-1), the electrode maintains a remarkable capacitance of 106 F g(-1). At 20, 60, and 100 °C and an extreme current density of 100 A g(-1), there is excellent capacitance retention (72-92%) with the specific capacitances being 113, 144, and 142 F g(-1), respectively. These characteristics favorably place the materials on a Ragone chart providing among the best power-energy characteristics (on an active mass normalized basis) ever reported for an electrochemical capacitor: At a very high power density of 20 kW kg(-1) and 20, 60, and 100 °C, the energy densities are 19, 34, and 40 Wh kg(-1), respectively. Moreover the assembled supercapacitor device yields a maximum energy density of 12 Wh kg(-1), which is higher than that of commercially available supercapacitors. By taking advantage of the complex multilayered structure of a hemp bast fiber precursor, such exquisite carbons were able to be achieved by simple hydrothermal carbonization combined with activation. This novel precursor-synthesis route presents a great potential for facile large-scale production of high-performance carbons for a variety of diverse applications including energy storage.