Synthetic tabular data is crucial for sharing and augmenting data across silos, especially for enterprises with proprietary data. However, existing synthesizers are designed for centrally stored data. Hence, they struggle with real-world scenarios where features are distributed across multiple silos, necessitating on-premise data storage. We introduce SiloFuse, a novel generative framework for high-quality synthesis from cross-silo tabular data. To ensure privacy, SiloFuse utilizes a distributed latent tabular diffusion architecture. Through autoencoders, latent representations are learned for each client's features, masking their actual values. We employ stacked dis-tributed training to improve communication efficiency, reducing the number of rounds to a single step. Under SiloFuse, we prove the impossibility of data reconstruction for vertically partitioned synthesis and quantify privacy risks through three attacks using our benchmark framework. Experimental results on nine datasets showcase SiloFuse's competence against centralized diffusion-based synthesizers. Notably, SiloFuse achieves 43.8 and 29.8 higher percentage points over GANs in resemblance and utility. Experiments on communication show stacked training's fixed cost compared to the growing costs of end-to-end training as the number of training iterations increases. Additionally, SiloFuse proves robust to feature permutations and varying numbers of clients.

In the past decades, Zirconia (ZrO₂) has emerged as a promising technical ceramic, both as high temperature structural material and electrolyte for fuel cells, etc. The traditional synthesis of ZrO₂ with spark plasma sintering (SPS) usually requires a sintering temperature as high as 1200 °C. General interest in lowering the sintering temperature to reduce energy consumption and thermal stresses has led to research on two promising routes – cold sintering via temperature-dependent chemical reactivity and sintering aids, which facilitates mass transport and improves densification. Here we combine both by developing a single-step sintering process benefitting from both water vapor through the in-situ conversion of Zr(OH)₄ to ZrO₂ and liquid phase Bi₂O₃ as a sintering aid. The resultant ZrO₂ has a relative density above 80% with a sintering temperature as low as 900 °C, significantly higher than that of ZrO₂ without sintering aids, which had a relative density of 54%, both sintered at 50 MPa. The dependence of porosity of sintered samples as a function of sintering pressure (range: 50 MPa–300 MPa) and temperature (range 400 °C–1200 °C) is mapped out as guidance for further material property design. A linear relationship between hardness and relative density was found, with a maximal hardness of 6.6 GPa achieved in samples with 30% porosity. In addition to sintered density, phase stabilization of tetragonal ZrO₂ is enhanced at sintering temperature of 900 °C with water vapor and Bi₂O₃, respectively.