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This papers aims to study lattice structures in terms of geometric variables, manufacturing variables and material-based variants and their correlation with compressive behaviour for their application in a methodology for the design and development of personalized elastic therapeutic products.

Lattice samples were designed and manufactured using extrusion-based additive manufacturing technologies. Mechanical tests were carried out on lattice samples for elasticity characterization purposes. The relationships between sample stiffness and key geometric and manufacturing variables were subsequently used in the case study on the design of a pressure cushion model for validation purposes. Differentiated areas were established according to patient’s pressure map to subsequently make a correlation between the patient’s pressure needs and lattice samples stiffness.

A substantial and wide variation in lattice compressive behaviour was found depending on the key study variables. The proposed methodology made it possible to efficiently identify and adjust the pressure of the different areas of the product to adapt them to the elastic needs of the patient. In this sense, the characterization lattice samples turned out to provide an effective and flexible response to the pressure requirements.

This study provides a generalized foundation of lattice structural design and adjustable stiffness in application of pressure cushions, which can be equally applied to other designs with similar purposes. The relevance and contribution of this work lie in the proposed methodology for the design of personalized therapeutic products based on the use of individual lattice structures that function as independent customizable cells.

Mitigating the energy trilemma (ET) is of great importance for dealing with climate change and realizing carbon neutrality. To this end, effectively assessing the level of the ET is essential. The purpose of this study is to evaluate the current situation and the spatio-temporal changes of the ET in the whole of China.

Moreover, based on provincial-level data in China for the period 2002–2017, and by using the dynamic estimation model, we aim to determine the specific marginal impacts of smart transportation (ST) on the ET, and the possible channels through which ST works on the ET.

We thus present the following findings: (1) The performance of both ET and its three pillars is gradually improving in China. Moreover, the situation tends to vary dramatically among various regions and provinces, and the gap between the best performers and the worst is large. (2) ST plays a significant role in inhibiting the ET, a finding that remains robust after a series of tests. And (3) the ET eradication effect of ST is caused mainly by improved innovation, advanced technical efficiency, and the increasing energy scale.

Accordingly, we put forward some policy recommendations to help tackle ET and accelerate ST in China.