Programmed multimaterial assembly by synergized 3D printing and freeform laser induction.

In nature, structural and functional materials often form programmed three-dimensional (3D) assembly to perform daily functions, inspiring researchers to engineer multifunctional 3D structures. Despite much progress, a general method to fabricate and assemble a broad range of materials into functional 3D objects remains limited. Herein, to bridge the gap, we demonstrate a freeform multimaterial assembly process (FMAP) by integrating 3D printing (fused filament fabrication (FFF), direct ink writing (DIW)) with freeform laser induction (FLI). 3D printing performs the 3D structural material assembly, while FLI fabricates the functional materials in predesigned 3D space by synergistic, programmed control. This paper showcases the versatility of FMAP in spatially fabricating various types of functional materials (metals, semiconductors) within 3D structures for applications in crossbar circuits for LED display, a strain sensor for multifunctional springs and haptic manipulators, a UV sensor, a 3D electromagnet as a magnetic encoder, capacitive sensors for human machine interface, and an integrated microfluidic reactor with a built-in Joule heater for nanomaterial synthesis. This success underscores the potential of FMAP to redefine 3D printing and FLI for programmed multimaterial assembly.

A two-sorbent system for fast uptake of arsenate from water: Batch and column studies.

There is a critical need to use decentralized and/or point-of-use systems to address some challenging water quality issues in society. Sorption-based approaches are uniquely suitable for such applications because of their simplicity in operation; however, the sorbents must possess fast contaminant uptake kinetics to overcome short hydraulic contact times often encountered in small systems. Here we designed a two-sorbent system consisting of Fe2O3-coated mesoporous carbon (FeMC) and nano-Fe2O3-coated activated carbon (FeAC) and demonstrated its ability to remove arsenate with a < 1 min empty bed contact time (EBCT) by a capture-and-storage process. Batch experiments showed rapid capture of arsenate by FeMC, likely occurred on the rod-like structures protruding to the liquid film. The captured arsenate could subsequently be relocated to FeAC for storage, which had a higher apparent sorption capacity. Column studies, operated with a 10 h running time followed by a 14 h pump-off time, showed that with a 102 µg-As/L influent concentration and at 0.85 min EBCT, the column treated 20,022 bed volumes until the 10 µg-As/L breakthrough, corresponding to a sorption density of 2.36 mg-As/g. This capture-and-storage technique resulted in a rapid and high-capacity arsenate removal through a combined effect of facile access to sorption sites on one sorbent and dynamic equilibrium in the two-sorbent system possessing a large total sorption capacity.

Sustainable 3D Printing of Recyclable Biocomposite Empowered by Flash Graphene.

Sustainability of 3D printing can be reflected in three main aspects: deployment of renewable inks, recycling of printed products, and applications for energy- and materials- savings. In this work, we demonstrated sustainable vat-photopolymerization (VPP)-based 3D printing in a whole life-cycle process by developing a renewable ink made of soybean oil and natural polyphenols and recycling the ink for reprinting or converting printed biocomposite to flash graphene (FG) as reinforcing nanofillers in the biocomposite. We also realized its applications in fabricating lightweight, materials-saving 3D structures, acoustic metamaterials, and disposable microreactors for time-saving and efficiency-improving synthesis of metal-organic framework nanostructures. In addition to enhancing the tensile strength and Young's modulus of the biopolymers by 42% and 232% with only 0.6 wt % FG nanofillers, respectively, FG improved the printability of the ink in forming 3D tubular structures, which are usually very hard to be achieved in transparent resin. Success of this work will inspire further development for sustainability in 3D printing.

Machine Learning Guided Synthesis of Flash Graphene.

Advances in nanoscience have enabled the synthesis of nanomaterials, such as graphene, from low-value or waste materials through flash Joule heating. Though this capability is promising, the complex and entangled variables that govern nanocrystal formation in the Joule heating process remain poorly understood. In this work, machine learning (ML) models are constructed to explore the factors that drive the transformation of amorphous carbon into graphene nanocrystals during flash Joule heating. An XGBoost regression model of crystallinity achieves an r2 score of 0.8051 ± 0.054. Feature importance assays and decision trees extracted from these models reveal key considerations in the selection of starting materials and the role of stochastic current fluctuations in flash Joule heating synthesis. Furthermore, partial dependence analyses demonstrate the importance of charge and current density as predictors of crystallinity, implying a progression from reaction-limited to diffusion-limited kinetics as flash Joule heating parameters change. Finally, a practical application of the ML models is shown by using Bayesian meta-learning algorithms to automatically improve bulk crystallinity over many Joule heating reactions. These results illustrate the power of ML as a tool to analyze complex nanomanufacturing processes and enable the synthesis of 2D crystals with desirable properties by flash Joule heating.

Accelerate Synthesis of Metal-Organic Frameworks by a Robotic Platform and Bayesian Optimization.

Synthesis of materials with desired structures, e.g., metal-organic frameworks (MOFs), involves optimization of highly complex chemical and reaction spaces due to multiple choices of chemical elements and reaction parameters/routes. Traditionally, realizing such an aim requires rapid screening of these nonlinear spaces by experimental conduction with human intuition, which is quite inefficient and may cause errors or bias. In this work, we report a platform that integrates a synthesis robot with the Bayesian optimization (BO) algorithm to accelerate the synthesis of MOFs. This robotic platform consists of a direct laser writing apparatus, precursor injecting and Joule-heating components. It can automate the MOFs synthesis upon fed reaction parameters that are recommended by the BO algorithm. Without any prior knowledge, this integrated platform continuously improves the crystallinity of ZIF-67, a demo MOF employed in this study, as the number of operation iterations increases. This work represents a methodology enabled by a data-driven synthesis robot, which achieves the goal of material synthesis with targeted structures, thus greatly shortening the reaction time and reducing energy consumption. It can be easily generalized to other material systems, thus paving a new route to the autonomous discovery of a variety of materials in a cost-effective way in the future.

Data-driven algorithms for inverse design of polymers.

The ever-increasing demand for novel polymers with superior properties requires a deeper understanding and exploration of the chemical space. Recently, data-driven approaches to explore the chemical space for polymer design have emerged. Among them, inverse design strategies for designing polymers with specific properties have evolved to be a significant materials informatics platform by learning hidden knowledge from materials data as well as smartly navigating the chemical space in an optimized way. In this review, we first summarize the progress in the representation of polymers, a prerequisite step for the inverse design of polymers. Then, we systematically introduce three data-driven strategies implemented for the inverse design of polymers, i.e., high-throughput virtual screening, global optimization, and generative models. Finally, we discuss the challenges and opportunities of the data-driven strategies as well as optimization algorithms employed in the inverse design of polymers.

Laser reprogramming magnetic anisotropy in soft composites for reconfigurable 3D shaping.

Responsive soft materials capable of exhibiting various three-dimensional (3D) shapes under the same stimulus are desirable for promising applications including adaptive and reconfigurable soft robots. Here, we report a laser rewritable magnetic composite film, whose responsive shape-morphing behaviors induced by a magnetic field can be digitally and repeatedly reprogrammed by a facile method of direct laser writing. The composite film is made from an elastomer and magnetic particles encapsulated by a phase change polymer. Once the phase change polymer is temporarily melted by transient laser heating, the orientation of the magnetic particles can be re-aligned upon change of a programming magnetic field. By the digital laser writing on selective areas, magnetic anisotropies can be encoded in the composite film and then reprogrammed by repeating the same procedure, thus leading to multimodal 3D shaping under the same actuation magnetic field. Furthermore, we demonstrated their functional applications in assembling multistate 3D structures driven by the magnetic force-induced buckling, fabricating multistate electrical switches for electronics, and constructing reconfigurable magnetic soft robots with locomotion modes of peristalsis, crawling, and rolling.

Rapid Identification of X-ray Diffraction Patterns Based on Very Limited Data by Interpretable Convolutional Neural Networks.

Large volumes of data from material characterizations call for rapid and automatic data analysis to accelerate materials discovery. Herein, we report a convolutional neural network (CNN) that was trained based on theoretical data and very limited experimental data for fast identification of experimental X-ray diffraction (XRD) patterns of metal-organic frameworks (MOFs). To augment the data for training the model, noise was extracted from experimental data and shuffled; then it was merged with the main peaks that were extracted from theoretical spectra to synthesize new spectra. For the first time, one-to-one material identification was achieved. Theoretical MOFs patterns (1012) were augmented to a whole data set of 72 864 samples. It was then randomly shuffled and split into training (58 292 samples) and validation (14 572 samples) data sets at a ratio of 4:1. For the task of discriminating, the optimized model showed the highest identification accuracy of 96.7% for the top 5 ranking on a test data set of 30 hold-out samples. Neighborhood component analysis (NCA) on the experimental XRD samples shows that the samples from the same material are clustered in groups in the NCA map. Analysis on the class activation maps of the last CNN layer further discloses the mechanism by which the CNN model successfully identifies individual MOFs from the XRD patterns. This CNN model trained by the data augmentation technique would not only open numerous potential applications for identifying XRD patterns for different materials, but also pave avenues to autonomously analyze data by other characterization tools such as FTIR, Raman, and NMR spectroscopies.

Machine Learning Assisted Synthesis of Metal-Organic Nanocapsules.

Herein, we report machine learning algorithms by training data sets from a set of both successful and failed experiments for studying the crystallization propensity of metal-organic nanocapsules (MONCs). Among a variety of studied machine learning algorithms, XGBoost affords the highest prediction accuracy of >90%. The derived chemical feature scores that determine importance of reaction parameters from the XGBoost model assist to identify synthesis parameters for successfully synthesizing new hierarchical structures of MONCs, showing superior performance to a well-trained chemist. This work demonstrates that the machine learning algorithms can assist the chemists to faster search for the optimal reaction parameters from many experimental variables, whose features are usually hidden in the high-dimensional space.

Stimulus Responsive 3D Assembly for Spatially Resolved Bifunctional Sensors.

3D electronic/optoelectronic devices have shown great potentials for various applications due to their unique properties inherited not only from functional materials, but also from 3D architectures. Although a variety of fabrication methods including mechanically guided assembly have been reported, the resulting 3D devices show no stimuli-responsive functions or are not free standing, thereby limiting their applications. Herein, the stimulus responsive assembly of complex 3D structures driven by temperature-responsive hydrogels is demonstrated for applications in 3D multifunctional sensors. The assembly driving force, compressive buckling, arises from the volume shrinkage of the responsive hydrogel substrates when they are heated above the lower critical solution temperature. Driven by the compressive buckling force, the 2D-formed membrane materials, which are pre-defined and selectively bonded to the substrates, are then assembled to 3D structures. They include "tent," "tower," "two-floor pavilion," "dome," "basket," and "nested-cages" with delicate geometries. Moreover, the demonstrated 3D bifunctional sensors based on laser induced graphene show capability of spatially resolved tactile sensing and temperature sensing. These multifunctional 3D sensors would open new applications in soft robotics, bioelectronics, micro-electromechanical systems, and others.

Transforming lignin into porous graphene via direct laser writing for solid-state supercapacitors.

Cost-effective valorization of lignin into carbon-based electrode materials remains a challenge. Here we reported a facile and ultrafast laser writing technique to convert lignin into porous graphene as active electrode material for solid-state supercapacitors (SCs). During laser writing, alkaline lignin experienced graphitization. By controlling laser parameters such as power the porous structure and graphitization degree can be well modulated. Graphene obtained at 80% of laser power setting (LIG-80) had higher graphene quality and more porous structure than that obtained at the lower power levels (i.e., 50%, 70%). TEM images revealed that LIG-80 had few-layer graphene structure with fringe-like patterns. LIG-80 proved to be an active electrode material for SCs with a specific capacitance as high as 25.44 mF cm-2 in a H2SO4/PVA gel electrolyte, which is comparable or even superior to SCs based on pristine LIG obtained from other carbon precursors. Taken together, our proposed technical route for lignin-based LIG and subsequent application in SCs would not only open a new avenue to lignin valorization, but also produce porous graphene from a renewable carbon precursor for energy storage applications.

A Supramolecular Coordination-Polymer-Derived Electrocatalyst for the Oxygen Evolution Reaction.

An iron oxide decorated nickel iron alloy nanoparticle/porous graphene hybrid exhibits high electrocatalytic activity and excellent durability toward oxygen evolution reaction (OER). It displays a low overpotential of 274 mV at 10 mA cm-2 , and low Tafel slope of 37 mV dec-1 , showing a superior performance to the state-of-the-art RuO2 OER electrocatalyst.

Rapid Synthesis of Zeolitic Imidazole Frameworks in Laser-Induced Graphene Microreactors.

Various approaches to synthesize zeolitic imidazole frameworks (ZIFs) have been developed, such as solvothermal, sonochemical, microfluidic, and mechanochemical reactions. However, most of them are time consuming and involve complex processing steps, thus they cannot rapidly screen potential candidates to obtain ZIFs on demand. Such a challenge calls for efficient synthetic approaches. Herein, this challenge is overcome by employing two nonconventional heating strategies, that is, microwave and Joule heating, which are induced by laser-induced graphene (LIG) microreactors, to rapidly synthesize ZIFs. In the first reaction, the LIG acts as a susceptor that absorbs electromagnetic energy, which is converted into heat. In the latter one, LIG acts an electrical conductor that converts electrical energy to heat. Both of them can rapidly heat up the reactor, accelerating the crystal growth for synthesizing ZIFs with well-controlled morphology and crystallinity. To demonstrate a conceptual application, a ZIF-67/LIG composite was converted into Co/CoNC/LIG by a CO2 laser-induced process. It showed excellent performance in the oxygen reduction reaction with a half-wave potential (E1/2 ) of 0.798 V, and superior methanol tolerance and long-term stability. These rapid and facile synthesis methodologies will enable quick optimization of reaction conditions and fast screening of compound libraries for searching new materials, paving the way to high-throughput and autonomous nanomanufacturing.

Mechanically Assembled, Three-Dimensional Hierarchical Structures of Cellular Graphene with Programmed Geometries and Outstanding Electromechanical Properties.

Three-dimensional (3D) cellular graphene structures have wide applications in energy storage, catalysis, polymer composites, electromagnetic shielding, and many others. However, the current strategies to form cellular graphene are only able to realize limited structure control and are hard to achieve the construction of 3D hierarchical architectures with complex, programmed configurations, limiting the design capabilities to satisfy various next-generation device applications. In addition, cellular graphene usually exhibits limited electromechanical properties, and its electrical and electrochemical performances are dramatically affected by mechanical deformations, constraining its applications in emerging wearable electronics and energy devices. Herein, we report a simple, general, and effective route to 3D hierarchical architectures of cellular graphene with desired geometries through the use of a mechanically guided, 3D assembly approach to overcome the aforementioned two challenges. Demonstrations include more than 10 3D hierarchical architectures with diverse configurations, ranging from mixed tables and tents, to double-floor helices, to kirigami/origami-inspired structures, and to fully separated multilayer architectures. The LED arrays interconnected with 3D helical coils and 3D interdigital supercapacitors fabricated with solid-state electrolytes provide prototypic examples of wearable devices that exhibit outstanding electromechanical properties and can maintain stable performances with little change in the electrical and electrochemical responses under extreme deformations, in both the static and cyclic loading conditions.

Bioinspired multi-responsive soft actuators controlled by laser tailored graphene structures.

By exploiting aligned cellulose fibrils as geometrically constraining structures, plants can achieve a complex programmable shape change in response to environmental stimuli. Inspired by this natural prototype, a series of manmade materials with aligned structures have been developed and employed in self-morphing materials. However, in these cases, the constraining materials are fabricated and aligned in separate processes. In botanic systems, a more efficient way is adopted, in which the aligned microstructures are simultaneously synthesized and aligned in one bottom-up process. Herein, we report a bioinspired bottom-up approach to fabricate laser induced graphene (LIG) structures which resemble the aligned microstructures of the cellulose fibrils in plants. Such LIG structures serve as geometrically constraining materials to precisely control the shape changing behaviors of soft actuators made from polymer and LIG layers. Meanwhile, the LIG structures also serve as functional materials to absorb photo and electrical energy to stimulate motions of the soft actuators. Taking advantage of the geometrically constraining effect from the aligned LIG structures, a series of programmable actuations stimulated by electricity, light, organic vapor, and moisture were demonstrated. Furthermore, the soft actuators also act as soft grippers and walking robots upon different stimuli, indicating their potential applications in soft robotics, electronics, microelectromechanical systems, and others.

Reversible Self-Assembly of 3D Architectures Actuated by Responsive Polymers.

An assembly of three-dimensional (3D) architectures with defined configurations has important applications in broad areas. Among various approaches of constructing 3D structures, a stress-driven assembly provides the capabilities of creating 3D architectures in a broad range of functional materials with unique merits. However, 3D architectures built via previous methods are simple, irreversible, or not free-standing. Furthermore, the substrates employed for the assembly remain flat, thus not involved as parts of the final 3D architectures. Herein, we report a reversible self-assembly of various free-standing 3D architectures actuated by the self-folding of smart polymer substrates with programmed geometries. The strategically designed polymer substrates can respond to external stimuli, such as organic solvents, to initiate the 3D assembly process and subsequently become the parts of the final 3D architectures. The self-assembly process is highly controllable via origami and kirigami designs patterned by direct laser writing. Self-assembled geometries include 3D architectures such as "flower", "rainbow", "sunglasses", "box", "pyramid", "grating", and "armchair". The reported self-assembly also shows wide applicability to various materials including epoxy, polyimide, laser-induced graphene, and metal films. The device examples include 3D architectures integrated with a micro light-emitting diode and a flex sensor, indicting the potential applications in soft robotics, bioelectronics, microelectromechanical systems, and others.

Bioinspired Programmable Polymer Gel Controlled by Swellable Guest Medium.

Responsive materials with functions of forming three-dimensional (3D) origami and/or kirigami structures have a broad range of applications in bioelectronics, metamaterials, microrobotics, and microelectromechanical (MEMS) systems. To realize such functions, building blocks of actuating components usually possess localized inhomogeneity so that they respond differently to external stimuli. Previous fabrication strategies lie in localizing nonswellable or less-swellable guest components in their swellable host polymers to reduce swelling ability. Herein, inspired by ice plant seed capsules, we report an opposite strategy of implanting swellable guest medium inside nonswellable host polymers to locally enhance the swelling inhomogeneity. Specifically, we adopted a skinning effect induced surface polymerization combined with direct laser writing to control gradient of swellable cyclopentanone (CP) in both vertical and lateral directions of the nonswellable SU-8. For the first time, the laser direct writing was used as a novel strategy for patterning programmable polymer gel films. Upon stimulation of organic solvents, the dual-gradient gel films designed by origami or kirigami principles exhibit reversible 3D shape transformation. Molecular dynamics (MD) simulation illustrates that CP greatly enhances diffusion rates of stimulus solvent molecules in the SU-8 matrix, which offers the driving force for the programmable response. Furthermore, this bioinspired strategy offers unique capabilities in fabricating responsive devices such as a soft gripper and a locomotive robot, paving new routes to many other responsive polymers.

Monolithic and Flexible ZnS/SnO2 Ultraviolet Photodetectors with Lateral Graphene Electrodes.

A continuing trend of miniaturized and flexible electronics/optoelectronic calls for novel device architectures made by compatible fabrication techniques. However, traditional layer-to-layer structures cannot satisfy such a need. Herein, a novel monolithic optoelectronic device fabricated by a mask-free laser direct writing method is demonstrated in which in situ laser induced graphene-like materials are employed as lateral electrodes for flexible ZnS/SnO2 ultraviolet photodetectors. Specifically, a ZnS/SnO2 thin film comprised of heterogeneous ZnS/SnO2 nanoparticles is first coated on polyimide (PI) sheets by a solution process. Then, CO2 laser irradiation ablates designed areas of the ZnS/SnO2 thin film and converts the underneath PI into highly conductive graphene as the lateral electrodes for the monolithic photodetectors. This in situ growth method provides good interfaces between the graphene electrodes and the semiconducting ZnS/SnO2 resulting in high optoelectronic performance. The lateral electrode structure reduces total thickness of the devices, thus minimizing the strain and improving flexibility of the photodetectors. The demonstrated lithography-free monolithic fabrication is a simple and cost-effective method, showing a great potential for developement into roll-to-roll manufacturing of flexible electronics.

Template-Free Synthesis and Enhanced Photocatalytic Performance of Uniform BiOCI Flower-Like Microspheres.

Preparation of uniform BiOCI flower-like microspheres was facilely accomplished through a sim- ple protocol involving regulation of pH value in aqueous with sodium hydroxide in the presence of n-propanol. The as-prepared samples were characterized by a collection of techniques, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray spectroscopy (EDX), UV-vis diffuse reflectance spectroscopy (UV-vis DRS), and nitrogen adsorption-desorption isotherms. Based upon the SEM analyses, uniform microspheres could be formed with coexistence of some fragments of BiOCI nanosheets without n-propanol. The addition of appropriate amount of n-propanol was beneficial to provide BiOCI samples containing only flower-like microspheres, which were further subjected to the photocatalytic measurements towards Rhodamine B in aqueous under visible light irradiation and exhibited the best catalytic performance among all samples tested. In addition, the photocatalytic process was confirmed to undergo through a photosensitization pathway, in which superoxide radicals (.O-) played critical roles.

Poly(vinyl pyrrolidone)-assisted hydrothermal synthesis and enhanced visible-light photocatalytic performance of oxygen-rich bismuth oxychlorides.

A series of novel oxygen-rich bismuth oxychloride (Bi12O17Cl2) were synthesized through a facile poly(vinyl pyrrolidone) (PVP)-assisted hydrothermal route. These obtained Bi12O17Cl2 samples were characterized by various physicochemical techniques. It was found that a proper addition amount of PVP could promote the transformation of Bi12O17Cl2 morphology from irregular clusters to three-dimensional hierarchical flower-like microspheres that were nominated as sample BP2. As-synthesized samples were subjected to a photocatalytic degradation of dye Rhodamine B (RhB) or 2,4-dichlorophenol (2,4-DCP) under visible light. Among all candidates, the sample BP2 with a hierarchical flower-like morphology showed the best degradation efficiency for RhB and 2,4-DCP. The apparent rate constant of sample BP2 in terms of degradation of RhB was nearly 5.7 and 45 times that of unmodified BP0 and N-TiO2. The enhanced photocatalytic performance could be ascribed to synergetic effects including unique hierarchical morphologies, large specific surface area, small particle size, good crystallinity, and suitable band structures. A possible mechanism of catalytic degradation was finally proposed basing upon the active species trapping experiments.