Suppressed Lone Pair Electrons Explain Unconventional Rise of Lattice Thermal Conductivity in Defective Crystalline Solids.

Manipulating thermal properties of materials can be interpreted as the control of how vibrations of atoms (known as phonons) scatter in a crystal lattice. Compared to a perfect crystal, crystalline solids with defects are expected to have shorter phonon mean free paths caused by point defect scattering, leading to lower lattice thermal conductivities than those without defects. While this is true in many cases, alloying can increase the phonon mean free path in the Cd-doped AgSnSbSe3 system to increase the lattice thermal conductivity from 0.65 to 1.05 W m-1 K-1 by replacing 18% of the Sb sites with Cd. It is found that the presence of lone pair electrons leads to the off-centering of cations from the centrosymmetric position of a cubic lattice. X-ray pair distribution function analysis reveals that this structural distortion is relieved when the electronic configuration of the dopant element cannot produce lone pair electrons. Furthermore, a decrease in the Grüneisen parameter with doping is experimentally confirmed, establishing a relationship between the stereochemical activity of lone pair electrons and the lattice anharmonicity. The observed "harmonic" behavior with doping suggests that lone pair electrons must be preserved to effectively suppress phonon transport in these systems.

Abnormal Silicon Etching Behaviors in Nanometer-Sized Channels.

Modern semiconductor fabrication is challenged by difficulties in overcoming physical and chemical constraints. A major challenge is the wet etching of dummy gate silicon, which involves the removal of materials inside confined spaces of a few nanometers. These chemical processes are significantly different in the nanoscale and bulk. Previously, electrical double-layer formation, bubble entrapment, poor wettability, and insoluble intermediate precipitation have been proposed. However, the exact suppression mechanisms remain unclear due to the lack of direct observation methods. Herein, we investigate limiting factors for the etching kinetics of silicon with tetramethylammonium hydroxide at the nanoscale by using liquid-phase transmission electron microscopy, three-dimensional electron tomography, and first-principles calculations. We reveal suppressed chemical reactions, unstripping phenomena, and stochastic etching behaviors that have never been observed on a macroscopic scale. We expect that solutions can be suggested from this comprehensive insight into the scale-dependent limiting factors of fabrication.

Surface-functionalized SERS platform for deep learning-assisted diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease is crucial to stall the deterioration of brain function, but conventional diagnostic methods require complicated analytical procedures or inflict acute pain on the patient. Then, label-free Surface-enhanced Raman spectroscopy (SERS) analysis of blood-based biomarkers is a convenient alternative to rapidly obtain spectral information from biofluids. However, despite the rapid acquisition of spectral information from biofluids, it is challenging to distinguish spectral features of biomarkers due to interference from biofluidic components. Here, we introduce a deep learning-assisted, SERS-based platform for separate analysis of blood-based amyloid ß (1-42) and metabolites, enabling the diagnosis of Alzheimer's disease. SERS substrates consisting of Au nanowire arrays are fabricated and functionalized in two characteristic ways to compare the validity of different Alzheimer's disease biomarkers measured on our SERS system. The 6E10 antibody is immobilized for the capture of amyloid ß (1-42) and analysis of its oligomerization process, while various self-assembled monolayers are attached for different dipole interactions with blood-based metabolites. Ultimately, SERS spectra of blood plasma of Alzheimer's disease patients and human controls are measured on the substrates and classified via advanced deep learning techniques that automatically extract informative features to learn generalizable representations. Accuracies up to 99.5% are achieved for metabolite-based analyses, which are verified with an explainable artificial intelligence technique that identifies key spectral features used for classification and for deducing significant biomarkers.

Illuminating Recent Progress in Nanotransfer Printing: Core Principles, Emerging Applications, and Future Perspectives.

As the demand for diverse nanostructures in physical/chemical devices continues to rise, the development of nanotransfer printing (nTP) technology is receiving significant attention due to its exceptional throughput and ease of use. Over the past decade, researchers have attempted to enhance the diversity of materials and substrates used in transfer processes as well as to improve the resolution, reliability, and scalability of nTP. Recent research on nTP has made continuous progress, particularly using the control of the interfacial adhesion force between the donor mold, target material, and receiver substrate, and numerous practical nTP methods with niche applications have been demonstrated. This review article offers a comprehensive analysis of the chronological advancements in nTP technology and categorizes recent strategies targeted for high-yield and versatile printing based on controlling the relative adhesion force depending on interfacial layers. In detail, the advantages and challenges of various nTP approaches are discussed based on their working mechanisms, and several promising solutions to improve morphological/material diversity are presented. Furthermore, this review provides a summary of potential applications of nanostructured devices, along with perspectives on the outlook and remaining challenges, which are expected to facilitate the continued progress of nTP technology and to inspire future innovations.

Wafer-Scale Fabrication of 2D Nanostructures via Thermomechanical Nanomolding.

With shrinking dimensions in integrated circuits, sensors, and functional devices, there is a pressing need to develop nanofabrication techniques with simultaneous control of morphology, microstructure, and material composition over wafer length scales. Current techniques are largely unable to meet all these conditions, suffering from poor control of morphology and defect structure or requiring extensive optimization or post-processing to achieve desired nanostructures. Recently, thermomechanical nanomolding (TMNM) has been shown to yield single-crystalline, high aspect ratio nanowires of metals, alloys, and intermetallics over wafer-scale distances. Here, TMNM is extended for wafer-scale fabrication of 2D nanostructures. Using In, Al, and Cu, nanomold nanoribbons with widths < 50 nm, depths ≈0.5-1 µm and lengths ≈7 mm into Si trenches at conditions compatible is successfully with back end of line processing . Through SEM cross-section imaging and 4D-STEM grain orientation maps, it is shown that the grain size of the bulk feedstock is transferred to the nanomolded structures up to and including single crystal Cu. Based on the retained microstructures of molded 2D Cu, the deformation mechanism during molding for 2D TMNM is discussed.

Advances in thermoelectric AgBiSe2: Properties, strategies, and future challenges.

Thermoelectric materials are attracting considerable attention to alleviate the global energy crisis by enabling the direct conversion of heat into electricity. As a class of I-V-VI2 semiconductors, AgBiSe2 is expected to be the potential thermoelectric material to replace conventional PbTe-based compounds due to its non-toxic and abundant nature of its constituent elements. This review article summarizes the fundamental properties of AgBiSe2, thermoelectric properties, the effect of different dopants on its transport properties and entropy engineering for cubic phase stabilization with the detailed description of related techniques used to analyze the properties of AgBiSe2. The current thermoelectric figure-of-merit and approaches to further improve performance and operational stability are also discussed.

Efficient and sustainable water electrolysis achieved by excess electron reservoir enabling charge replenishment to catalysts.

Suppressing the oxidation of active-Ir(III) in IrOx catalysts is highly desirable to realize an efficient and durable oxygen evolution reaction in water electrolysis. Although charge replenishment from supports can be effective in preventing the oxidation of IrOx catalysts, most supports have inherently limited charge transfer capability. Here, we demonstrate that an excess electron reservoir, which is a charged oxygen species, incorporated in antimony-doped tin oxide supports can effectively control the Ir oxidation states by boosting the charge donations to IrOx catalysts. Both computational and experimental analyses reveal that the promoted charge transfer driven by excess electron reservoir is the key parameter for stabilizing the active-Ir(III) in IrOx catalysts. When used in a polymer electrolyte membrane water electrolyzer, Ir catalyst on excess electron reservoir incorporated support exhibited 75 times higher mass activity than commercial nanoparticle-based catalysts and outstanding long-term stability for 250 h with a marginal degradation under a water-splitting current of 1 A cm-2. Moreover, Ir-specific power (74.8 kW g-1) indicates its remarkable potential for realizing gigawatt-scale H2 production for the first time.

Sub-30 nm 2D Perovskites Patterns via Block Copolymer Guided Self-Assembly for Color Conversion Optical Polarizer.

Despite the remarkable advances made in the development of 2D perovskites suitable for various high-performance devices, the development of sub-30 nm nanopatterns of 2D perovskites with anisotropic photoelectronic properties remains challenging. Herein, a simple but robust route for fabricating sub-30 nm 1D nanopatterns of 2D perovskites over a large area is presented. This method is based on nanoimprinting a thin precursor film of a 2D perovskite with a topographically pre-patterned hard poly(dimethylsiloxane) mold replicated from a block copolymer nanopattern consisting of guided self-assembled monolayered in-plane cylinders. 1D nanopatterns of various 2D perovskites (A'2 MAn -1 Pbn X3 n +1 ,A' = BA, PEA, X = Br, I) are developed; their enhanced photoluminescence (PL) quantum yields are approximately four times greater than those of the corresponding control flat films. Anisotropic photocurrent is observed because 2D perovskite nanocrystals are embedded in a topological 1D nanopattern. Furthermore, this 1D metal-coated nanopattern of a 2D perovskite is employed as a color conversion optical polarizer, in which polarized PL is developed. This is due to its capability of polarization of an incident light arising from the sub-30 nm line pattern, as well as the PL of the confined 2D perovskite nanocrystals in the pattern.

Ultrahigh-resolution quantum dot patterning for advanced optoelectronic devices.

Quantum dots have attracted significant scientific interest owing to their optoelectronic properties, which are distinct from their bulk counterparts. In order to fully utilize quantum dots for next generation devices with advanced functionalities, it is important to fabricate quantum dot colloids into dry patterns with desired feature sizes and shapes with respect to target applications. In this review, recent progress in ultrahigh-resolution quantum dot patterning technologies will be discussed, with emphasis on the characteristic advantages as well as the limitations of diverse technologies. This will provide guidelines for selecting suitable tools to handle quantum dot colloids throughout the fabrication of quantum dot based solid-state devices. Additionally, epitaxially fabricated single-particle level quantum dot arrays are discussed. These are extreme in terms of pattern resolution, and expand the potential application of quantum dots to quantum information processing.

Noninvasive and Direct Patterning of High-Resolution Full-Color Quantum Dot Arrays by Programmed Microwetting.

Although the commercialization of electroluminescent quantum-dot (QD) displays essentially demands multicolor patterning of QDs with sufficient scalability and uniformity, the implementation of QD patterning in a light-emitting diode device is highly challenging, mainly due to the innate vulnerability of QDs and charge-transport layers. Here, we introduce a noninvasive surface-wetting approach for patterning full-color QD arrays on a photoprogrammed hole-transport layer (HTL). To achieve noninvasiveness of QD patterning, surface-specific modification of HTLs was performed without degrading their performance. Moreover, engineering the solvent evaporation kinetics allows area-selective wetting of QD patterns with a uniform thickness profile. Finally, multicolor QD patterning was enabled by preventing cross-contamination between different QD colloids via partial fluoro-encapsulation of earlier-patterned QDs. Throughout the overall QD patterning process, the optoelectronic properties of QDs and hole-transport layers are well preserved, and prototype electroluminescent quantum dot light-emitting diode arrays with high current efficiency and brightness were realized.

Suppressing Charged Cation Antisites via Se Vapor Annealing Enables p-Type Dopability in AgBiSe2 -SnSe Thermoelectrics.

Cation disordering is commonly found in multinary cubic compounds, but its effect on electronic properties has been neglected because of difficulties in determining the ordered structure and defect energetics. An absence of rational understanding of the point defects present has led to poor reproducibility and uncontrolled conduction type. AgBiSe2 is a representative compound that suffers from poor reproducibility of thermoelectric properties, while the origins of its intrinsic n-type conductivity remain speculative. Here, it is demonstrated that cation disordering is facilitated by BiAg charged antisite defects in cubic AgBiSe2 which also act as a principal donor defect that greatly controls the electronic properties. Using density functional theory calculations and in situ Raman spectroscopy, how saturation annealing with selenium vapor can stabilize p-type conductivity in cubic AgBiSe2 alloyed with SnSe at high temperatures is elucidated. With stable and controlled hole concentration, a peak is observed in the weighted mobility and the density-of-states effective mass in AgBiSnSe3 , implying an increased valley degeneracy in this system. These findings corroborate the importance of considering the defect energetics for exploring the dopability of ternary thermoelectric chalcogenides and engineering electronic bands by controlling self-doping.

Heat-fueled enzymatic cascade for selective oxyfunctionalization of hydrocarbons.

Heat is a fundamental feedstock, where more than 80% of global energy comes from fossil-based heating process. However, it is mostly wasted due to a lack of proper techniques of utilizing the low-quality waste heat (<100 °C). Here we report thermoelectrobiocatalytic chemical conversion systems for heat-fueled, enzyme-catalyzed oxyfunctionalization reactions. Thermoelectric bismuth telluride (Bi2Te3) directly converts low-temperature waste heat into chemical energy in the form of H2O2 near room temperature. The streamlined reaction scheme (e.g., water, heat, enzyme, and thermoelectric material) promotes enantio- and chemo-selective hydroxylation and epoxidation of representative substrates (e.g., ethylbenzene, propylbenzene, tetralin, cyclohexane, cis-ß-methylstyrene), achieving a maximum total turnover number of rAaeUPO (TTNrAaeUPO) over 32000. Direct conversion of vehicle exhaust heat into the enantiopure enzymatic product with a rate of 231.4 µM h-1 during urban driving envisions the practical feasibility of thermoelectrobiocatalysis.

High-Capacity Ti3C2Tx MXene Electrodes Achieved by Eliminating Intercalated Water Molecules Using a Co-solvent System.

Synthesizing layered transition-metal carbides, MXenes, with a mesoporous structure remains challenging but is highly useful because it converts the laminated two-dimensional structures into versatile porous materials. Hydrogen bonds between intercalated H2O molecules and oxygen terminal groups on the surface are formed in aqueous solution processes, and this is a determining factor of surface area. We developed an extraction method to remove intercalated water molecules based on a simple intermolecular force attraction strategy in a co-solvent system using a combination of polar-protic/-aprotic and non-polar solvents. As a result, self-aggregated mesoporous Ti3C2Tx was realized without any additives. The dipole-dipole interaction between H2O and CHCl3 molecules under non-polar solvent conditions assists the extraction of intercalated H2O from the MXene suspension, which can form a self-aggregated morphology (not re-stacked horizontally). The process yields Ti3C2Tx with a layered structure of embedded mesopores and a specific surface area that is 13-fold higher than that of standard MXene. Electrodes made with the resulting MXene exhibited a larger specific capacitance of 224 F/g (1 A/g), with an improved cyclic retention of 96.4%@10,000 cycles. This intermolecular attraction-induced approach, involving the manipulation of morphology, is simple to mass-produce and can be used for MXene-based electrochemical applications.

Polychromatic Quantum Dot Array to Compose a Community Signal Ensemble for Multiplexed miRNA Detection.

We herein describe a polychromatic quantum dot array (PQDA) to compose a community signal ensemble enabling accurate and precise quantification of miRNAs in a multiplexed manner. Advanced multicomponent ultrahigh-resolution patterning technique achieved by capsulation-assisted transfer printing following self-assembly-based poly(methyl methacrylate) (PMMA) patterning is utilized to manufacture the PQDA, which is designed to discharge a target miRNAs-specific set of fluorescent quantum dots (QDs) through the activity of duplex-specific nuclease (DSN). On the basis of the community signal ensemble produced by the discharged QD profiles, target miRNAs are very specifically identified down to a femtomolar level (1.27 fM) in a multiplexed manner over a wide dynamic range of up to 6 orders of magnitude. The practical diagnostic capability of this strategy is also demonstrated by reliably identifying breast cancer-specific miRNAs from heterogeneous cancer cell lysates.

Self-Induced Solutal Marangoni Flows Realize Coffee-Ring-Less Quantum Dot Microarrays with Extensive Geometric Tunability and Scalability.

Currently, quantum dot light-emitting diodes (QD-LEDs) are receiving extensive attention. To maximize their luminous performance, the uniformity of the QD-LEDs is crucial. Although the spontaneously self-induced solutal Marangoni flow of an evaporating binary mixture droplet has been widely investigated and used to suppress coffee-ring patterns in ink-jet printing technology, unfortunately, ring shapes are still present at the edges, and the Marangoni flow generated by the selective evaporation of volatile liquid components cannot be controlled due to its nonlinear instabilities. In this work, polygonal coffee-ring-less QD microarrays are created using two spontaneous and sequential solutal Marangoni flows. During the initial evaporation, internal circulating flows are controlled by polygonal-shaped droplets. After that, sequential interfacial flows are generated by the captured volatile vapors. A theoretical model and scaling analysis are provided to explain the working mechanisms. It is expected that the newly designed printing system can be applied to the mass production of QD-LEDs.

Comparative Study of Thermoelectric Properties of Sb2Si2Te6 and Bi2Si2Te6.

Charge carrier transport and corresponding thermoelectric properties are often affected by several parameters, necessitating a thorough comparative study for a profound understanding of the detailed conduction mechanism. Here, as a model system, we compare the electronic transport properties of two layered semiconductors, Sb2Si2Te6 and Bi2Si2Te6. Both materials have similar grain sizes and morphologies, yet their conduction characteristics are significantly different. We found that phase boundary scattering can be one of the main factors for Bi2Si2Te6 to experience significant charge carrier scattering, whereas Sb2Si2Te6 is relatively unaffected by the phenomenon. Furthermore, extensive point defect scattering in Sb2Si2Te6 significantly reduces its lattice thermal conductivity and results in high zT values across a broad temperature range. These findings provide novel insights into electron transport within these materials and should lead to strategies for further improving their thermoelectric performance.

Metal oxide charge transfer complex for effective energy band tailoring in multilayer optoelectronics.

Metal oxides are intensively used for multilayered optoelectronic devices such as organic light-emitting diodes (OLEDs). Many approaches have been explored to improve device performance by engineering electrical properties. However, conventional methods cannot enable both energy level manipulation and conductivity enhancement for achieving optimum energy band configurations. Here, we introduce a metal oxide charge transfer complex (NiO:MoO3-complex), which is composed of few-nm-size MoO3 domains embedded in NiO matrices, as a highly tunable carrier injection material. Charge transfer at the finely dispersed interfaces of NiO and MoO3 throughout the entire film enables effective energy level modulation over a wide work function range of 4.47 - 6.34 eV along with enhanced electrical conductivity. The high performance of NiO:MoO3-complex is confirmed by achieving 189% improved current efficiency compared to that of MoO3-based green OLEDs and also an external quantum efficiency of 17% when applied to blue OLEDs, which is superior to 1,4,5,8,9,11-hexaazatriphenylene-hexacarbonitrile-based conventional devices.

Separation-free bacterial identification in arbitrary media via deep neural network-based SERS analysis.

Universal and fast bacterial detection technology is imperative for food safety analyses and diagnosis of infectious diseases. Although surface-enhanced Raman spectroscopy (SERS) has recently emerged as a powerful solution for detecting diverse microorganisms, its widespread application has been hampered by strong signals from surrounding media that overwhelm target signals and require time-consuming and tedious bacterial separation steps. By using SERS analysis boosted with a newly proposed deep learning model named dual-branch wide-kernel network (DualWKNet), a markedly simpler, faster, and effective route to classify signals of two common bacteria E. coli and S. epidermidis and their resident media without any separation procedures is demonstrated. With outstanding classification accuracies up to 98%, the synergistic combination of SERS and deep learning serves as an effective platform for "separation-free" detection of bacteria in arbitrary media with short data acquisition times and small amounts of training data.

Current-induced manipulation of exchange bias in IrMn/NiFe bilayer structures.

The electrical control of antiferromagnetic moments is a key technological goal of antiferromagnet-based spintronics, which promises favourable device characteristics such as ultrafast operation and high-density integration as compared to conventional ferromagnet-based devices. To date, the manipulation of antiferromagnetic moments by electric current has been demonstrated in epitaxial antiferromagnets with broken inversion symmetry or antiferromagnets interfaced with a heavy metal, in which spin-orbit torque (SOT) drives the antiferromagnetic domain wall. Here, we report current-induced manipulation of the exchange bias in IrMn/NiFe bilayers without a heavy metal. We show that the direction of the exchange bias is gradually modulated up to ±22 degrees by an in-plane current, which is independent of the NiFe thickness. This suggests that spin currents arising in the IrMn layer exert SOTs on uncompensated antiferromagnetic moments at the interface which then rotate the antiferromagnetic moments. Furthermore, the memristive features are preserved in sub-micron devices, facilitating nanoscale multi-level antiferromagnetic spintronic devices.

Unconventional grain growth suppression in oxygen-rich metal oxide nanoribbons.

Nanograined metal oxides are requisite for diverse applications that use large surface area, such as gas sensors and catalysts. However, nanoscale grains are thermodynamically unstable and tend to coarsen at elevated temperatures. Here, we report effective grain growth suppression in metal oxide nanoribbons annealed at high temperature (900°C) by tuning the metal-to-oxygen ratio and confining the nanoribbons. Despite the high annealing temperatures, the average grain size was maintained at ~6 nm, which also retained their structural integrity. We observe that excess oxygen in amorphous tin oxide nanoribbons prevents merging of small grains during crystallization, leading to suppressed grain growth. As an exemplary application, we demonstrate a gas sensor using grain growth­suppressed tin oxide nanoribbons, which exhibited both high sensitivity and unusual long-term operation stability. Our findings provide a previously unknown pathway to simultaneously achieve high performance and excellent thermal stability in nanograined metal oxide nanostructures.