arXiv subjects

Mengru Zhang

Publications and source records attributed to Mengru Zhang.

3 recordsLinked to original sources

arXiv2026

High-Throughput Computational Exploration of MOFs for Short-Chain PFAS Removal

Short-chain per- and polyfluoroalkyl substances (PFASs) are increasingly replacing regulated long-chain PFASs, yet they remain challenging to remove from water due to their high persistence, mobility, and weak affinity toward conventional adsorbents. In this work, we developed a hybrid high-throughput computational screening (HTCS) strategy to identify high-performance MOFs for the selective adsorption of perfluorobutanoic acid (PFBA), a representative short-chain PFAS, from water. The workflow begins with a curated MOF dataset and employs Monte Carlo (MC) simulations based on synergistic use of a classical universal force field (UFF) and a universal machine-learned interatomic potential (u-MLIP), enabling scalable and quantitatively accurate prediction of adsorption across large MOF databases. A set of promising MOFs initially identified using UFF-based HTCS, that combine strong PFBA affinity and high PFBA/H2O selectivity were re-evaluated with u-MLIP to refine adsorption predictions and to assess guest-induced framework flexibility, enabling the exclusion of materials with unfavourable high water-framework interactions. Ultimately, four high-performance MOFs were identified that optimally balance strong PFBA interactions, high PFBA selectivity over water, and practical considerations including sustainability, water stability, and synthetic feasibility. This study demonstrates that combining classical force fields with u-MLIPs enables scalable, quantitatively accurate MOF adsorption screening and establishes transferable principles for the rational design of adsorbents targeting short-chain PFAS.

cond-mat.mtrl-sci↗

arXiv2023

Cryogenic quasi-static embedded DRAM for energy-efficient compute-in-memory applications

Compute-in-memory (CIM) presents an attractive approach for energy-efficient computing in data-intensive applications. However, the development of suitable memory designs to achieve high-performance CIM remains a challenging task. Here, we propose a cryogenic quasi-static embedded DRAM to address the logic-memory mismatch of CIM. Guided by the re-calibrated cryogenic device model, the designed four-transistor bit-cell achieves full-swing data storage, low power consumption, and extended retention time at cryogenic temperatures. Combined with the adoption of cryogenic write bitline biasing technique and readout circuitry optimization, our 4Kb cryogenic eDRAM chip demonstrates a 1.37$\times$10$^6$ times improvement in retention time, while achieving a 75 times improvement in retention variability, compared to room-temperature operation. Moreover, it also achieves outstanding power performance with a retention power of 112 fW and a dynamic power of 108 $μ$W at 4.2 K, which can be further decreased by 7.1% and 13.6% using the dynamic voltage scaling technique. This work reveals the great potential of cryogenic CMOS for high-density data storage and lays a solid foundation for energy-efficient CIM implementations.

cs.ET↗

arXiv2013

Describe the Fibonacci map by principal nests

In this paper,we studied some properties of the Fibonacci map and find a property of this map related to the notation of principal nest. And weproved this property with some additional conditions equals the original definition of Fibonacci map. Therefore give us a new method to describe Fibonacci map.

math.DS↗