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This review analyses the design, mechanical behaviors, manufacturability, and application of gradient lattice structures manufactured via metallic additive manufacturing technology. By varying the design parameters such as cell size, strut length, and strut diameter of the unit cells in lattice structures, a gradient property is obtained to achieve different levels of functionalities and optimize strength-to-weight ratio characteristics. Gradient lattice structures offer variable densification and porosities; and can combine more than one type of unit cells with different topologies which results in different performances in mechanical behavior layer-by-layer compared to non-gradient lattice structures. Additive manufacturing techniques are capable of manufacturing complex lightweight parts such as uniform and gradient lattice structures and hence offer design freedom for engineers. Despite these advantages, additive manufacturing has its own unique drawbacks in manufacturing lattice structures. The rules and strategies in overcoming the constraints are discussed and recommendations for future work were proposed.

To achieve efficient development of high-quality product, manufacturing constraints must be fully taken into account at the early design stage. However, designers lack in-depth knowledge of manufacturing and production. Many time-consuming iterations of design changes are required between designers and manufacturing engineers. In order to minimize this knowledge gap, this paper presents an ontology-based product design framework for manufacturability verification and knowledge reuse to support the sharing and reuse of design and manufacturing knowledge. It aims at providing advices and feedback of restraints of manufacturing processes to the designers during the design process. The proposed framework consists of three major layers which include a foundation layer, a domain layer, and an instance layer. We use the Web Ontology Language (OWL), a standard of ontology representation language, to formalize the foundation layer. It contains the core product model and the standard ISO 10303 AP224 application protocol. The domain layer comprises extensional concepts and relationships for design and manufacturing integration and a rule base for manufacturability verification, which is represented in Semantic Web Rule Language (SWRL). In the instance layer, an inference engine is developed based on ontology and rule inference. It provides recommendations of manufacturability. Two case studies are provided as application examples to demonstrate the effectiveness of the framework.

Optical metasurfaces, planar artificial media capable of controlling light propagation, are transitioning from laboratory curiosity to commercial applications. This shift requires advanced meta-atom and metasurface designs, considering manufacturability and enhancing optical performance with post-processing algorithms. Artificial-Intelligence(AI), particularly machine-learning(ML) and optimization, offers solutions to these demands. This perspective systematically reviews AI’s potential impact in three critical areas: AI-enabled metasurface design-for-manufacturing(DFM), design beyond the classical local phase approximation, and AI-empowered computational backend.

The article provides a methodology for the experimental determination of the concentration coefficients ασ and the gradients of the principal stresses. The effectiveness of the experimental method of photoelasticityis shown for studying the stress-strain state of parts of complex shape in the presence of stress concentrators, as well as for solving problems of brittle strength by methods of linear fracture mechanics.

Achieving solid superlubricity in high-humidity environments is of great practical importance yet remains challenging nowadays, due to the complex physicochemical roles of water and concomitant oxidation on solid surfaces. Here we report a facile way to access humidity-insensitive solid superlubricity (coefficient of friction 0.0035) without detectable wear and running-in at a humidity range of 2–80%. Inspired by the concept of structural superlubricity, this is achieved between Au-capped microscale graphite flake and graphene nanoflake-covered hydrogen-free amorphous carbon (GNC a-C). Such GNC a-C exhibits reduced pinning effects of water molecules and weak oxidation, which demonstrates stable structural superlubricity even after air exposure of the surfaces for 365 days. The manufacturability of such design enables the macroscopic scale-up of structural superlubricity, achieving the leap from 4 μm × 4 μm contact to 3 mm ball-supported contact with a wide range of materials. Our results suggest a strategy for the macroscale application of structural superlubricity under ambient condition. Grain boundary hardening and precipitation hardening are important mechanisms for enhancing the strength of metals. Here, these two effects are amplified simultaneously, by adding a suitable alloying element, leading to near-theoretical strength.

Tungsten (W) materials are gaining more and more attention due to the extended applications of metallic systems in the extreme environments. Given W’s unique characteristics like room-temperature brittleness, additive manufacturing (AM) techniques could give them a higher design flexibility and manufacturability. With the growing focus and thriving development of W-faced AM techniques, since the mechanical performance of additively manufactured W parts is still unsatisfactory, a critical review to further explore the possibilities of combining W and AM processes is urgently needed. In this review, we systematically explain the fundamentals of AM processes for W materials. Following the traditional classification, we further discuss the widely used AM processes including wire arc additive manufacturing (WAAM), electron beam melting (EBM), laser powder bed fusion (LPBF), laser direct energy deposition (laser DED), and other modified yet emergent AM techniques. Accordingly, since additively manufacturing W materials is processing parameter-sensitive, we illustrated the effects of various important processing parameters on the AM process control and final parts’ quality. With this detailed understanding, various categories of AM-compatible W materials (i.e., pure W, W alloys, and W composites) were presented, and their general mechanical performance, distinct role (particularly the role of different alloying elements and added secondary-phase particles in W), and application-oriented benefits have been summarized. After clarifying the current status, main challenges, and triumphant successes for additively manufacturing W materials, we further provide a concise prospect into the development of additively manufactured (AMed) W materials by integrating potential fabrication, measurement, alloy design, and application’s considerations. In summary, this critical review investigates the fundamental and practical problems crucially limiting the applications of AMed W materials, and the comprehensive discussion concentrates the history of the development and combination between AM techniques and W design. All the understanding is of great importance to achieving foreseeable successful future applications of AMed W materials.

Organic photodetectors (OPDs) are promising for applications in flexible electronics due to their advantages of excellent photodetection performance, cost‐effective solution‐fabrication capability, flexible device design, and adaptivity to manufacturability. This review outlines the recent advances in the development of high‐performance OPDs and their applications in flexible electronics. The approaches to developing different noise reduction methods, filter‐free spectral selective detection, flexible OPDs, and scale‐up production of flexible OPDs through solution‐fabrication processes are discussed. Applications of the OPD technology ultimately result in the materialization of wearable units, flexible and compact information sensors at commercially viable costs, including wearable health self‐monitoring devices, flexible optical communication systems, and flexible large‐area image sensors. Recent advances in organic photodetectors (OPDs) and applications in flexible electronics are summarized. The advantages and the performance of the OPDs with novel device designs, e.g., filter‐free spectral selective OPDs, are discussed. Practical solution‐fabrication and printing techniques are also reviewed.

Chip floorplanning is the engineering task of designing the physical layout of a computer chip. Despite five decades of research 1 , chip floorplanning has defied automation, requiring months of intense effort by physical design engineers to produce manufacturable layouts. Here we present a deep reinforcement learning approach to chip floorplanning. In under six hours, our method automatically generates chip floorplans that are superior or comparable to those produced by humans in all key metrics, including power consumption, performance and chip area. To achieve this, we pose chip floorplanning as a reinforcement learning problem, and develop an edge-based graph convolutional neural network architecture capable of learning rich and transferable representations of the chip. As a result, our method utilizes past experience to become better and faster at solving new instances of the problem, allowing chip design to be performed by artificial agents with more experience than any human designer. Our method was used to design the next generation of Google’s artificial intelligence (AI) accelerators, and has the potential to save thousands of hours of human effort for each new generation. Finally, we believe that more powerful AI-designed hardware will fuel advances in AI, creating a symbiotic relationship between the two fields. Machine learning tools are used to greatly accelerate chip layout design, by posing chip floorplanning as a reinforcement learning problem and using neural networks to generate high-performance chip layouts.

Recent advances in mRNA technology and its delivery have enabled mRNA-based therapeutics to enter a new era in medicine. The rapid, potent, and transient nature of mRNA-encoded proteins, without the need to enter the nucleus or the risk of genomic integration, makes them desirable tools for treatment of a range of diseases, from infectious diseases to cancer and monogenic disorders. The rapid pace and ease of mass-scale manufacturability of mRNA-based therapeutics supported the global response to the COVID-19 pandemic. Nonetheless, challenges remain with regards to mRNA stability, duration of expression, delivery efficiency, and targetability, to broaden the applicability of mRNA therapeutics beyond COVID-19 vaccines. By learning from the rapidly expanding preclinical and clinical studies, we can optimise the mRNA platform to meet the clinical needs of each disease. Here, we will summarise the recent advances in mRNA technology; its use in vaccines, immunotherapeutics, protein replacement therapy, and genomic editing; and its delivery to desired specific cell types and organs for development of a new generation of targeted mRNA-based therapeutics.

Active metasurfaces promise reconfigurable optics with drastically improved compactness, ruggedness, manufacturability and functionality compared to their traditional bulk counterparts. Optical phase-change materials (PCMs) offer an appealing material solution for active metasurface devices with their large index contrast and non-volatile switching characteristics. Here we report a large-scale, electrically reconfigurable non-volatile metasurface platform based on optical PCMs. The optical PCM alloy used in the devices, Ge 2 Sb 2 Se 4 Te (GSST), uniquely combines giant non-volatile index modulation capability, broadband low optical loss and a large reversible switching volume, enabling notably enhanced light–matter interactions within the active optical PCM medium. Capitalizing on these favourable attributes, we demonstrated quasi-continuously tuneable active metasurfaces with record half-octave spectral tuning range and large optical contrast of over 400%. We further prototyped a polarization-insensitive phase-gradient metasurface to realize dynamic optical beam steering. An electrically reconfigurable optical metasurface using a Ge 2 Sb 2 Se 4 Te phase change material shows half an octave spectral tuning and promising performances for optical beam steering applications.