Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization

Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MOCOPs). However, they are still struggling to achieve high learning efficiency and solution quality. To tackle this issue, we propose an efficient meta neural heuristic (EMNH), in which a meta-model is first trained and then fine-tuned with a few steps to solve corresponding single-objective subproblems. Specifically, for the training process, a (partial) architecture-shared multi-task model is leveraged to achieve parallel learning for the meta-model, so as to speed up the training; meanwhile, a scaled symmetric sampling method with respect to the weight vectors is designed to stabilize the training. For the fine-tuning process, an efficient hierarchical method is proposed to systematically tackle all the subproblems. Experimental results on the multi-objective traveling salesman problem (MOTSP), multi-objective capacitated vehicle routing problem (MOCVRP), and multi-objective knapsack problem (MOKP) show that, EMNH is able to outperform the state-of-the-art neural heuristics in terms of solution quality and learning efficiency, and yield competitive solutions to the strong traditional heuristics while consuming much shorter time.Comment: Accepted at NeurIPS 202

Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement

Most of existing neural methods for multi-objective combinatorial optimization (MOCO) problems solely rely on decomposition, which often leads to repetitive solutions for the respective subproblems, thus a limited Pareto set. Beyond decomposition, we propose a novel neural heuristic with diversity enhancement (NHDE) to produce more Pareto solutions from two perspectives. On the one hand, to hinder duplicated solutions for different subproblems, we propose an indicator-enhanced deep reinforcement learning method to guide the model, and design a heterogeneous graph attention mechanism to capture the relations between the instance graph and the Pareto front graph. On the other hand, to excavate more solutions in the neighborhood of each subproblem, we present a multiple Pareto optima strategy to sample and preserve desirable solutions. Experimental results on classic MOCO problems show that our NHDE is able to generate a Pareto front with higher diversity, thereby achieving superior overall performance. Moreover, our NHDE is generic and can be applied to different neural methods for MOCO.Comment: Accepted at NeurIPS 202

A high energy output and low onset temperature nanothermite based on three-dimensional ordered macroporous nano-NiFe2O4

Three-dimensional ordered macroporous (3DOM) Al/NiFe2O4 nanothermite has been obtained by colloidal crystal templating method combined with magnetron sputtering processing. Owing to the superior material properties and unique 3DOM structural characteristics of composite metal oxides, the heat output of the Al/NiFe2O4 nanothermite is up to 2921.7 J g− 1, which is more than the values of Al/NiO and Al/Fe2O3 nanothermites in literature. More importantly, by comparison to the other two nanothermites, the onset temperature of 298.2 °C from Al/NiFe2O4 is remarkably low, which means it can be ignited more easily. Laser ignition experiment indicate that the synthesized Al/NiFe2O4 nanothermite can be easily ignited by laser. In addition, the preparation process is highly compatible with the MEMS technology. These exciting achievements have great potential to expand the scope of nanothermite applications

3D ordered macroporous NiO/Al nanothermite film with significantly improved higher heat output, lower ignition temperature and less gas production

The performances of nanothermites largely rely on a meticulous design of nanoarchitectures and the close assembly of components. Three-dimensionally ordered macroporous (3DOM) NiO/Al nanothermite film has been successfully fabricated by integrating colloidal crystal template (CCT) method and controllable magnetron sputtering. The as-prepared NiO/Al film shows uniform structure and homogeneous dispersity, with greatly improved interfacial contact between fuel and oxidizer at the nanoscale. The total heat output of 3DOM NiO/Al nanothermite has reached 2461.27 J·g−1 at optimal deposition time of 20 min, which is significantly more than the values of other NiO/Al structural systems that have been reported before. Intrinsic reduced ignition temperature (onset temperature) and less gas production render the wide applications of 3DOM NiO/Al nanothermite. Moreover, this design strategy can also be readily generalized to realize diverse 3DOM structured nanothermites

From concept to action: a united, holistic and One Health approach to respond to the climate change crisis

It is unequivocal that human influence has warmed the planet, which is seriously affecting the planetary health including human health. Adapting climate change should not only be a slogan, but requires a united, holistic action and a paradigm shift from crisis response to an ambitious and integrated approach immediately. Recognizing the urgent needs to tackle the risk connection between climate change and One Health, the four key messages and recommendations that with the intent to guide further research and to promote international cooperation to achieve a more climate-resilient world are provided

Novel Approach to the Preparation of Organic Energetic Film for Microelectromechanical Systems and Microactuator Applications

An activated RDX–Fe2O3 xerogel in a Si-microchannel plate (MCP) has been successfully prepared by a novel propylene epoxide-mediated sol–gel method. A decrease of nearly 40 °C in decomposition temperature has been observed compared with the original cyclotrimethylene trinitramine (RDX). The RDX–Fe2O3 xerogel can release gas and solid matter simultaneously, and the ratio of gas to solid can be tailored easily by changing the initial proportions of RDX and FeCl3·6H2O, which significantly enhances the explosive and propulsion effects and is of great benefit to the applications. The approach, which is simple, safe, and fully compatible with MEMS technology, opens a new route to the introduction of organic energetic materials to a silicon substrate

In Situ Electrochemical Construction of CuN₃@CuCl Hybrids for Controllable Energy Release and Self-Passivation Ability

Advanced energetic materials (EMs) play a crucial role in the advancement of microenergetic systems as actuation parts, igniters, propulsion units, and power. The sustainable electrosynthesis of EMs has gained momentum and achieved substantial improvements in the past decade. This study presents the facile synthesis of a new type of high-performance CuN3@CuCl hybrids via a co-electrodeposition methodology utilizing porous Cu as the sacrificial template. The composition, morphology, and energetic characteristics of the CuN3@CuCl hybrids can be easily tuned by adjusting the deposition times. The resulting hybrids demonstrate remarkable energy output (1120 J·g–1) and good laser-induced initiating ability. As compared with porous CuN3, the uniform doping of inert CuCl enhances the electrostatic safety of the hybridized material without compromising its overall energetic characteristics. Notably, the special oxidizing behavior of CuCl gradually lowers the susceptibility of the hybrid material to laser and electrostatic stimulation. This has significant implications for the passivation or self-destruction of highly sensitive EMs. Overall, this study pioneers a new path for the development of MEMS-compatible EMs, facilitating further microenergetic applications