Potential In Many Applications Research Articles

Data-driven design of orthogonal protein-protein interactions

Engineering protein-protein interactions to generate new functions presents a challenge with great potential for many applications, ranging from therapeutics to synthetic biology. To avoid unwanted cross-talk with preexisting protein interaction networks in a cell, the specificity and selectivity of newly engineered proteins must be controlled. Here, we developed a computational strategy that mimics gene duplication and the divergence of preexisting interacting protein pairs to design new interactions. We used the bacterial PhoQ-PhoP two-component system as a model system to demonstrate the feasibility of this strategy and validated the approach with known experimental results. The designed protein pairs are predicted to exclusively interact with each other and to be insulated from potential cross-talk with their native partners. Thus, our approach enables exploration of uncharted regions of the protein sequence space and the design of new interacting protein pairs.

Learning Explicit and Implicit Dual Common Subspaces for Audio-visual Cross-modal Retrieval

Audio-visual tracks in video contain rich semantic information with potential in many applications and research. Since the audio-visual data have inconsistent distributions and because of the heterogeneous nature of representations, the heterogeneous gap between modalities makes them impossible to compare directly. To bridge the modality gap, a frequently adopted approach is to simultaneously project audio-visual data into a common subspace to capture the commonalities and characteristics of modalities for measurement, which has been extensively studied in relation to the issues of modality-common and modality-specific feature learning in previous research. However, it is difficult for existing methods to address the tradeoff between both issues; e.g., the modality-common feature is learned from the latent commonalities of audio-visual data or the correlated features as aligned projections, in which the modality-specific feature can be lost. To solve the tradeoff, we propose a novel end-to-end architecture, which synchronously projects audio-visual data into the explicit and the implicit dual common subspaces. The explicit subspace is used to learn modality-common features and reduce the modality gap of explicitly paired audio-visual data, where the representation-specific details are abandoned to retain the common underlying structure of audio-visual data. The implicit subspace is used to learn modality-specific features, where each modality privately pulls apart the feature distances between different categories to maintain the category-based distinctions, by minimizing the distance between audio-visual features and corresponding labels. The comprehensive experimental results on two audio-visual datasets, VEGAS and AVE, demonstrate that our proposed model for using two different common subspaces for audio-visual cross-modal learning is effective and significantly outperforms the state-of-the-art cross-modal models that learn features from a single common subspace by 4.30% and 2.30% in terms of average MAP on the VEGAS and AVE datasets, respectively.

Additive manufacturing of ductile refractory high-entropy alloys via phase engineering

Refractory high-entropy alloys (RHEAs) are developed for superior elevated-temperature strength and softening resistance. Additive manufacturing of RHEAs is attracting extensive attention because of their commendable potential in many applications. Yet, most additively manufactured RHEAs are brittle and their tensile properties at room temperature have rarely been reported. Here, tensile ductile RHEAs are fabricated by laser melting deposition for the first time. In the model TiZrHfNbx (x = 0.6, 0.8, 1.0, in molar ratios) RHEAs, the as-printed alloys have an equiaxed-grained microstructure without any special process control or additional treatment. Increasing Nb contents stabilizes the body-centered cubic phase and suppresses the ω phase formation. Such phase engineering strategy transforms the mechanical performance from brittle to ductile fracture. As a result, the as-printed TiZrHfNb variant exhibits a room temperature tensile yield strength of ∼1034 MPa and ductility of ∼18.5%. The solid-solution strengthening contributes to the high tensile yield strength, the local chemical fluctuations promote dislocation interactions and give rise to the large ductility. This work offers a new avenue for additive manufacturing of ductile RHEAs, which is conducive to their industrial application.

PhysFormer++: Facial Video-Based Physiological Measurement with SlowFast Temporal Difference Transformer

Remote photoplethysmography (rPPG), which aims at measuring heart activities and physiological signals from facial video without any contact, has great potential in many applications (e.g., remote healthcare and affective computing). Recent deep learning approaches focus on mining subtle rPPG clues using convolutional neural networks with limited spatio-temporal receptive fields, which neglect the long-range spatio-temporal perception and interaction for rPPG modeling. In this paper, we propose two end-to-end video transformer based architectures, namely PhysFormer and PhysFormer++, to adaptively aggregate both local and global spatio-temporal features for rPPG representation enhancement. As key modules in PhysFormer, the temporal difference transformers first enhance the quasi-periodic rPPG features with temporal difference guided global attention, and then refine the local spatio-temporal representation against interference. To better exploit the temporal contextual and periodic rPPG clues, we also extend the PhysFormer to the two-pathway SlowFast based PhysFormer++ with temporal difference periodic and cross-attention transformers. Furthermore, we propose the label distribution learning and a curriculum learning inspired dynamic constraint in frequency domain, which provide elaborate supervisions for PhysFormer and PhysFormer++ and alleviate overfitting. Comprehensive experiments are performed on four benchmark datasets to show our superior performance on both intra- and cross-dataset testings. Unlike most transformer networks needed pretraining from large-scale datasets, the proposed PhysFormer family can be easily trained from scratch on rPPG datasets, which makes it promising as a novel transformer baseline for the rPPG community.

Advances in the Production of Olfactory Receptors for Industrial Use.

In biological olfactory systems, olfactory receptors (ORs) can recognize and discriminate between thousands of volatile organic compounds with very high sensitivity and specificity. The superior properties of ORs have led to the development of OR-based biosensors that have shown promising potential in many applications over the past two decades. In particular, newly designed technologies in gene synthesis, protein expression, solubilization, purification, and membrane mimetics for membrane proteins have greatly opened up the previously inaccessible industrial potential of ORs. In this review, gene design, expression and solubilization strategies, and purification and reconstitution methods available for modern industrial applications are examined, with a focus on ORs. The limitations of current OR production technology are also estimated, and future directions for further progress are suggested.

Ultra-Broadband Tunable Terahertz Absorber of Graphene and Hierarchical Plasmonic Metamaterials

Broadband metamaterial-based perfect absorbers (MPAs) have significant potential in many applications. However, the design and fabrication of ultra-broadband terahertz MPAs pose considerable challenges. Most terahertz MPAs reported rely on complex, multilayer, or three-dimensional structures that are difficult to fabricate and hard to meet the miniaturization and integration requirements. In this study, we propose and investigate a novel tunable, ultra-broadband terahertz MPA of atomically thin monolayer graphene and hierarchically structured plasmonic metamaterials. The metamaterial MPA consists of alternating T-shaped gold bars, a dielectric layer, and a graphene layer on the bottom gold layer. These near-perfect absorbers exhibit an exceptional absorption of nearly 90% over an ultra-broad frequency range from 20.8 to 39.7 THz; the bandwidth is as high as 18.9 THz. Furthermore, a quantitative analysis of the impact of geometrical parameters on the absorption spectra is conducted. Additionally, the modulation of the absorption window by tuning the Fermi level of graphene is investigated, and the potential applications are discussed.

Unambiguous spectral characterization on triplet energy transfer from quantum dots mediated by hole transfer competing with other carrier dynamics.

Triplet generation by quantum dots (QDs)-sensitized molecules emerges great potential in many applications. However, the mechanism of triplet energy transfer (TET) is still fuzzy especially due to the complicated energy level alignment of QDs and molecules or trap states in QDs. Here, CdSe QDs and 5-tetracene carboxylic acid (TCA) molecules are selected as the triplet donor and acceptor, respectively, to form a TET system. By tuning the band gap of CdSe, the CdSe-TCA complex is exactly designed to present a Type-II like alignment of relative energetics. Coupling the transient absorption and time-resolved fluorescence spectra, all carrier dynamics is distinctly elucidated. Quantitative analysis demonstrates that hole transfer persisting for ∼ 2 ps outcompetes all other carrier dynamics such as electron trapping (∼100 ps level), charge recombination (∼ 5 ns) and the so-called "back transfer charge recombination" (∼50 ns), and thus leads to a hole-transfer-mediated TET process. The low TET yield (∼34.0%) ascribed to electron behavior can be further improved if electron trapping and charge recombination are efficiently suppressed. The observation on distinguishable carrier dynamics attributed to legitimate design of energy level alignment facilitates a better understanding of the TET mechanism from QDs to molecules as well as further development of photoelectronic devices based on such TET systems.

Stimuli‐responsive polypeptoid block copolymers containing o‐nitrobenzyl groups with extremely sharp transition

AbstractBioinspired thermoresponsive polymers have received increasing attention for many applications. Here, we report a series of thermoresponsive polypeptoid block copolymers containing o‐nitrobenzyl groups, that is, poly(ethylene glycol)‐b‐poly[N‐[2‐[N‐(o‐nitrobenzyloxycarbonyl)‐amino]‐ethyl]‐glycine] (PEG‐b‐PN[oNB]G), prepared by ring‐opening polymerization. The polypeptoid block copolymers show reversible lower critical solution temperature (LCST)‐type behavior in water with tunable phase transition properties dependent on the pH values, chemical compositions, and concentrations of the copolymers. The dynamic light scattering results reveal the formation of spherical micelles and temperature‐induced aggregation of PEG‐b‐PN(oNB)G. Notably, the phase transition of the block copolymer solution upon heating appears extremely sharp (∆T < 1°C), superior to bench mark poly(N‐isopropylacrylamide). In addition, we present the removal of photo‐responsive o‐nitrobenzyl groups can result in the increased clouding point and even the loss of phase transition properties, acting as an excellent regulator to tune the LCST behavior. We demonstrate that the hydrogen‐bonding interaction may play a critical part on the LCST behavior. The prepared diblock copolymers show great potential for many applications and its structure–property may shed light on highly designable stimuli‐responsive polymeric materials.

Laser etching of 2D materials with single-layer precision up to ten layers

Patterned 2D materials with layer-controlled thickness and precise lateral resolution are of great potential for many applications. Laser etching is a promising technique for large-scale patterning of 2D materials, but better control in film thickness is strongly desired. Here, we explore the dynamic characteristics in the laser etching process in which a local temperature lock phenomenon is observed as laser power reaches the etching threshold. A layer-by-layer etching strategy is then developed based on the temporal evolution of the local temperature as measured by in-situ Raman spectroscopy. Employing such a method in a typical layered material MoS2, we demonstrate thickness control up to ten layers in layer-by-layer laser etching. The local temperature lock during laser etching is explained by thermodynamic simulation of temperature distribution within the 2D material under laser illumination. The influence of substrate thermal conductivity on the thickness of the controlled laser etching has been revealed. The results are valuable for potential applications of 2D material devices built with complex layered structures.

Comprehensive Study of Electronic, Optical, and Thermophysical Properties of Metavanadates CaV2O6 and MgV2O6.

Calcium metavanadate (CaV2O6) and magnesium metavanadate (MgV2O6) have received considerable attention due to their great potential for many practical applications; however, a fundamental understanding of their intrinsic physical properties is still not well established. Here, we present a comprehensive experimental and theoretical study of the optical, electronic, and lattice dynamic properties of CaV2O6 and MgV2O6. We find that both compounds are semiconductors with indirect band gaps and exhibit visible light-emitting properties, which are thus expected to be the ideal candidates for phosphors or optoelectronic devices. Through density functional theory (DFT) calculations, we further show that CaV2O6 exhibits negative thermal expansion (NTE) below 80 K due to the flexible or intense coupled rocking of the CaO6 octahedra. Moreover, using the dual-phonon model, we disclose the hierarchical thermal transport features of these two compounds, in which diffusive channels make a significant contribution to the thermal conductivity κ, resulting in the weak temperature dependence of κ deviating from the typical κ ∼T-1 given by the phonon gas model. With the consideration of normal and diffusive phonons, we predict the ultralow and large anisotropic thermal conductivities of CaV2O6 and MgV2O6. This work provides a fundamental understanding of the optical, electronic, and thermal properties of metal-ion-intercalated layered vanadium oxides, which may promote the functional applications of metavanadates.

Thermal management of portable photovoltaic systems using novel phase change materials with efficiently enhanced thermal conductivity

Solar cells are gradually becoming a common substitute for fossil fuels in order to address the escalating energy crisis and environmental change. Many wearable or outdoor electronic devices are powered by portable solar cells, but due to structural limitations and dramatic increases in heat dissipation, portable solar cell efficiency declines sharply with heat accumulation and temperature rises, and thermal non-uniformity reduces device reliability. An efficient thermal management solution is needed to address these crucial thermal issues. In this study, a novel composite PCM with efficiently enhanced thermal conductivity (ETC-PCM) has been created using graphene, epoxy resin (EP), and polyethylene glycol (PEG) by strong cross-linking and thermally induced structural rearrangement. Compared to the composite PCM with normally enhanced thermal conductivity (NTC-PCM) by traditional mechanical mixing, enhancements are made to ETC-PCM's cutability, flexibility, and latent heat. More significantly, the thermal conductivity of ETC-PCM increased by 157% to 0.51 W/m·K with the inclusion of a 1.5% effective thermal conductivity filler component. In a composite PV system with direct integration of flexible solar cells and ETC-PCM, the ETC-PCM also exhibited superior thermal management in both time and space dimensions, with enhanced thermal uniformity and long-term reliability of the PV system. The outstanding thermal and mechanical properties of ETC-PCM have shown tremendous potential in many applications, such as solar cell thermal management, solar/electric energy harvesting, thermal energy storage, etc. • A novel PEG/EP/graphene composite PCM with efficiently enhanced thermal conductivity was fabricated. • ETC-PCM was synthesized with strong cross-linking and thermally induced structural rearrangement. • Both long-term reliability and thermal uniformity of normal or aged PV-PCM systems were investigated.

Insight into the Evolution of Ordered Mesoporous sp2 Carbonaceous Material Derived from Self-Assembly of a Block Copolymer.

Block-copolymer-derived ordered mesoporous carbon (OMC) materials have great potential in many applications, such as adsorption, catalysis, and energy conversions; however, their formation process and the kinetic mechanism remain unclear. Herein, a N-doped OMC (N-OMC) with sp2-bonded C atoms is developed via self-assembly of the polystyrene-block-poly(4-vinyl pyridine) block copolymer. By correlating the external morphologies with the internal chemical states, the formation process can be concluded as follows: (1) pore evolution via polystyrene domain degradation and (2) regularization and graphitization of the residual carbon via the removal of sp3 C atoms. In addition, the thickness of the N-OMC shows a power function relationship with the spin-coating rate, and the N content can be incredibly increased up to 26.34 at. % in an NH3 carbonization atmosphere. With the as-prepared N-OMC as the support for loading of the pseudo-atomic-scale Pt (Pt/N-OMC), a high electrochemical active surface area value of 99.64 m2·g-1 and a half-wave potential (E1/2) of 0.850 VRHE are achieved, showing great potential in developing single-atom electrocatalysts.

Forecasting the crowd: An effective and efficient neural network for citywide crowd information prediction at a fine spatio-temporal scale

Modelling and forecasting citywide crowd information (e.g., crowd volume of a region, the inflow of crowds into a region, outflow of crowds from a region) at a fine spatio-temporal scale is crucial for urban and transport planning, city management, public safety, and traffic management. However, this is a challenging task due to its complex spatial and temporal dependences. This paper proposes an effective and efficient model to reduce the training time cost while maintaining predictive accuracy in forecasting citywide crowd information at a fine spatio-temporal scale. Our model integrates Gated Recurrent Unit (GRU), convolutional neural network (CNN), and k-nearest neighbors (k-NN) to jointly capture the spatial and temporal dependences between two regions in a city. The evaluation with two different datasets in two different cities shows that compared to the state-of-the-art baselines, our model has better predictive accuracy (reducing the mean absolute errors MAEs by 20.99% on average) and a lower training time cost (reducing the time cost to only 26.16% on average of that of the baselines). Our model also has better abilities in making accurate predictions with low time cost under the influences of large-scale special events (when massive crowds of people are gathering in a short time) and for regions with high and irregular crowd changes. In summary, our model is an effective, efficient, and reliable method for forecasting citywide crowd information at a fine spatio-temporal scale, and has a high potential for many applications, such as city management, public safety, and transportation.

Durable superhydrophobic coating with a self-replacing mechanism of surface roughness based on multiple Pickering emulsion templating

Superhydrophobic coatings have remarkable potential for applications in different fields. With the availability of either nano-structural templates or simple methodology, the search for superhydrophobic coatings that are easy to prepare and durable remains challenging for both academia and industry. This study presents a novel durable superhydrophobic coating formulation based on oil-in-oil-in-oil (O/O/O) multiple Pickering emulsions. After applying the emulsions on a polypropylene surface, a hierarchical structure is formed, leading to superhydrophobicity. The resulting hierarchical surface morphology leads to a self-replacing mechanism of the coating’s surface roughness and unique structure of the multiple Pickering emulsion templates, which restores its superhydrophobicity during abrasion. This self-replacing mechanism leads to highly durable superhydrophobic coatings. The structural complexity of the multiple emulsions is translated to a complex hierarchical structure of the coating, which involves the formation of concave compartments with spherical/deflated structures lying inside them. During abrasion, the concave structure will be removed at the first stage, exposing the deflated structure, which is the new rough surface geometry that will maintain the superhydrophobicity. The multiple O/O/O Pickering emulsions developed in this study are composed of acetone-in-mineral oil-in-acetone (A/MO/A), mineral oil-in-acetone-in-mineral oil (MO/A/MO), acetone-in-mineral oil (A/MO), and mineral oil-in-acetone (MO/A). The studied multiple emulsions were prepared by a one-step procedure. Multi-functional silica nanoparticles were used as stabilizers in all these emulsions with both alkane and PTFE functional groups. Before emulsification, polyacrylate/polyvinyl chloride (PA/PVC) was dissolved in the acetone phase. This rapid simple technique is easy to apply and yields a multi-functional surface with self-replacing superhydrophobic properties that have great potential for many applications in diverse fields.

Improved Ferroelectricity and Endurance of Hf0.5Zr0.5O2 Thin Films in Low Thermal Budget with Novel Bottom Electrode Doping Technology

AbstractHfO2‐based ferroelectric memory is one of the most attractive candidates for embedded memory in future monolithic‐M3D integrated‐circuit (IC). However, ferroelectricity and endurance will degrade at lower annealing temperatures due to the limitation of the M3D‐IC in thermal budget, which significantly inhibits its potential for many applications. In this work, a novel process technology using As5+ implantation (As‐imp) at the bottom electrode (BE) in TiN/Hf0.5Zr0.5O2(HZO)/TiN capacitors is proposed. The HZO film shows excellent ferroelectricity and improves endurance at the annealing temperatures of 350 and 400 °C, especially when the dose of As‐imp is 1 × 1016, where the endurance of the HZO film is up to 1.5 × 1011, and the remnant polarization (Pr) far exceeds the reference capacitor without BE As‐imp, where 2Pr is greater than 40 °C cm−2 after 1.5 × 1011 cycles. The underlying physical mechanism is that the oxidation reaction of introduced As5+ during the film deposition releases extra oxygen atoms to fill the oxygen vacancies (Vo) near the BE interface due to the occurrence of the thermal reduction reaction in the subsequent annealing process. This study paves the way for the integration of HZO‐based ferroelectric embedded memory in future high‐performance and energy‐efficient 3D‐ICs.

Programmable Anisotropic Hydrogels with Localized Photothermal/Magnetic Responsive Properties.

Programmable smart materials that can respond locally to specific stimuli hold great potential for many applications, but controllable fabrication of these materials remains challenging. This work reports the development of novel programmable anisotropic materials with both magnetic and photothermal stimuli‐responsiveness, which are fabricated by anchoring thermosensitive poly(N‐isopropyl acrylamide) (PNIPAm) and magnetic Fe3O4 nanoparticles on the surface of MoS2 nanosheets. Further embedding PNIPAm‐MoS2/Fe3O4 into 3D‐printed hydrogel cubes results in stimuli‐responsive building blocks, and the magnetic field can precisely control their orientation and near‐infrared (NIR) light absorbing property. Particularly, the variation of the orientation of MoS2/Fe3O4 block results in obvious changes of their photothermal efficiency and optical property. By exploiting the anisotropy of MoS2/Fe3O4 and their NIR light responsiveness, thermally‐induced phase transitions in individual 3D printed hydrogel building block can be locally controlled for magnetic field‐assisted programming a quick response (QR) code. Alternatively, fluorescent QR code with high contrast and security level can be achieved by photothermal‐induced release of fluorescent dyes. These 3D printed magnetically programmed hydrogels hold great potential for application in information storage, intelligent materials, and precise therapy.

Modulating CRISPR-Cas Genome Editing Using Guide-Complementary DNA Oligonucleotides.

Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) has revolutionized genome editing and has great potential for many applications, such as correcting human genetic disorders. To increase the safety of genome editing applications, CRISPR-Cas may benefit from strict control over Cas enzyme activity. Previously, anti-CRISPR proteins and designed oligonucleotides have been proposed to modulate CRISPR-Cas activity. In this study, we report on the potential of guide-complementary DNA oligonucleotides as controlled inhibitors of Cas9 ribonucleoprotein complexes. First, we show that DNA oligonucleotides inhibit Cas9 activity in human cells, reducing both on- and off-target cleavage. We then used in vitro assays to better understand how inhibition is achieved and under which conditions. Two factors were found to be important for robust inhibition: the length of the complementary region and the presence of a protospacer adjacent motif-loop on the inhibitor. We conclude that DNA oligonucleotides can be used to effectively inhibit Cas9 activity both ex vivo and in vitro.

Gelatin-based cellular solids: Fabrication, structure and properties

Although most cellular polymers are made from thermoplastics using different foaming technologies, gelatin and many other natural polymers can form hydrogels and convert them to cellular solids using various techniques, many of which differ from traditional plastic foaming, and so does their resulting structures. Cellular solids from natural hydrogels are porous materials that often exhibit a combination of desirable properties, including high specific surface area, biochemical activity, as well as thermal and acoustic insulation properties. Among natural hydrogels, gelatin-based porous materials are widely explored due to their availability, biocompatibility, biodegradability and relatively low cost. In addition, gelatin-based cellular solids have outstanding properties and are currently subject to increasing scientific research due to their potential in many applications, such as biocompatible cellular materials or biofoams to facilitate waste treatment. This article aims at providing a comprehensive review of gelatin cellular solids processing and their processing-properties-structure relationship. The fabrication techniques covered include aerogels production, mechanical foaming, blowing agents use, 3D printing, electrospinning and particle leaching methods. It is hoped that the assessment of their characteristics provides compiled information and guidance for selecting techniques and optimization of processing conditions to control material structure and properties to meet the needs of the finished products.

Temperature-Dependent Luminescence and Anisotropic Optical Properties of Centimeter-Sized One-Dimensional Perovskite Trimethylammonium Lead Iodide Single Crystals.

Low-dimensional hybrid halide perovskite materials with self-trapped exciton (STE) emissions and anisotropic properties are highly attractive for their great potential in many applications. However, to date, reports on large one-dimensional (1D) perovskite single crystals have been limited. Here, centimeter-sized 1D single crystals of trimethylammonium lead iodide (TMAPbI3) with typical STE emission are synthesized by an antisolvent vapor-assisted crystallization method. Thermal quenching and antiquenching with a high relative sensitivity of photoluminescence (PL) are observed and studied via temperature-dependent photoluminescence spectroscopy. Further analysis indicates that the temperature-dependent PL behaviors are influenced by the self-trapping of the free exciton and the migrations between self-trapped excitons and intermediate nonradiative states. The TMAPbI3 single crystal also exhibits a linearly polarized emission and a large birefringence that is higher than those of commercial birefringent crystals. This 1D perovskite with high structural anisotropy has promise for applications in versatile optical- and luminescence-related fields.

Ion Implantation Enhanced Exfoliation Efficiency of V2AlC Single Crystals: Implications for Large V2CTz Nanosheet Production

MXenes are two-dimensional transition-metal carbides and nitrides with an attractive combination of physicochemical properties, gaining notable potential in many applications. Currently, MXene synthesis is mainly performed from powder precursors whose purity and grain size define the quality and flake size of 2D sheets, typically not exceeding 2–3 μm. In this work, we successfully synthesize macroscopic nanolayered V2CTz MXenes with lateral dimensions larger than 25 μm from a V2AlC single crystal by exploiting a new strategy based on ion implantation. Ne2+ ion implantation of the single-crystal precursor is applied to introduce defects in the crystal structure of V2AlC, which facilitates chemical etching and drastically reduces the etching time down to 8 h (∼10 times lower as compared to conventional synthesis from powder precursors). The quality and morphology of exfoliated macroscopic MXene multilayers have been comprehensively studied by performing detailed analyses based on different kinds of microscopies and spectroscopies. The obtained macroscopic flakes are ideal objects to study the intrinsic physical properties of V2CTz MXenes and explore their potential application, in particular, as membranes.