Although heavy metal contamination is an ancient problem, it remains a global concern in isolated areas. Herein, we report the design of a novel thiol-rich Zr(IV) metal-organic framework (BCM-5), assembled from meso-2,3-dimercaptosuccinic acid (Succimer), a commercially available thiol-rich metal-chelating agent used in the treatment of heavy metal poisoning. BCM-5 has been subsequently integrated into porous PVDF-HFP membranes processed via salt-leaching. The non-immobilized BCM-5 and the BCM-5@PVDF-HFP membranes were systematically evaluated for Pb(II), Cd(II), and Hg(II) capture.The results demonstrate that the metal-chelating functionalities of Succimer linker are effectively preserved within the BCM-5 framework, while immobilization of BCM-5 into PVDF-HFP membranes significantly enhances the material's dispersibility and improves its capacity for the efficient capture of the targeted heavy metals. A detailed structural, chemical, and DFT characterization of post-adsorption BCM-5 suggests that metal immobilization proceeds via chemisorption within hydrophobic, hydrophilic, and amphiphilic pore regions of BCM-5, depending on the nature of the heavy metal. Overall, this work introduces a novel approach to use metal-chelator molecules as building blocks for MOFs construction targeted to the recovery of heavy metals, while also detailing strategies for their immobilization into polymeric structures with interconnected macroporosity.
Sign-switching dark energy provides a novel mechanism for modifying the late-time expansion history of the Universe without invoking additional fields or finely tuned initial conditions. In this work, we investigate a class of background-level cosmological models in which the dark energy contribution changes sign at a transition redshift z dagger, producing a sharp deviation from standard ACDM dynamics. We confront these models with a comprehensive set of cosmological observations, including compressed Planck 18 cosmic microwave background (CMB) measurements, DESI DR2 Baryonic Acoustic Oscillation (BAO) data and the Pantheon+ & SH0ES Type Ia supernova sample (SN). Using a full Markov Chain Monte Carlo (MCMC) analysis, we find that the sign-switching scenario significantly alleviates the Hubble tension while obtaining better results when statistically comparing with ACDM, as quantified by the Akaike and Bayesian information Criteria. Although the model is explored only at the background level, the improvement in the inferred Hubble constant demonstrates that sign-switching dark energy offers a promising and physically economical pathway toward resolving late-universe discrepancies.
3-forms are natural candidates for describing the late-time accelerated expansion of the Universe, as they can inherently reproduce a positive cosmological constant when lacking an evolving potential. When such a potential is present, a 3-form field may exhibit either quintessence-like or phantom-like behaviour. In this paper, we consider a late-time effective dark energy model described by a 3-form with a Gaussian potential, stable during the dark-energy-dominated era. We constrain this model observationally by performing a Markov Chain Monte Carlo (MCMC) analysis employing a comprehensive cosmological dataset, including Planck PR4 cosmic microwave background (CMB) data, DESI DR1 baryon acoustic oscillation (BAO) measurements, Pantheon+ Type Ia supernovae data, low-z Cepheid calibrators, and DES Y1 large-scale structure observations. We demonstrate that the 3-form model successfully increases the predicted Hubble parameter of CMB and BAO data from 67.89 +/- 0.36km/s/Mpc of Lambda CDM model to 68.29+0.56-0.61km/s/Mpc by approaching the potential peak at the right time, thus mildly reducing the tension with the late-time observation. Overall, the 3-form field serves as a promising candidate of phantom-like dark energy from both theoretical and observational points of view.
The Quantum Twisting Microscope (QTM) is a groundbreaking instrument that enables energy- and momentum-resolved measurements of quantum phases via tunneling spectroscopy across twistable van der Waals heterostructures. In this work, we significantly enhance the QTMs resolution and extend its measurement capabilities to higher energies and twist angles by incorporating hexagonal boron nitride (hBN) as a tunneling dielectric. This advancement unveils previously inaccessible signatures of the dispersion in the tunneling between two monolayer graphene (MLG) sheets, features consistent with a logarithmic correction to the linear Dirac dispersion arising from electron-electron (e-e) interactions with a fine-structure constant of alpha = 0.32. Remarkably, we find that this effect, for the first time, can be resolved even at room temperature, where these corrections are extremely faint. Our results underscore the exceptional resolution of the QTM, which, through interferometric interlayer tunneling, can amplify even subtle modifications to the electronic band structure of two-dimensional materials. Our findings reveal that strong e-e interactions persist even in symmetric, nonordered graphene states and emphasize the QTMs unique ability to probe spectral functions and their excitations of strongly correlated ground states across a broad range of twisted and untwisted systems.
Variational quantum eigensolvers (VQEs) are among the most promising quantum algorithms for solving electronic structure problems in quantum chemistry, particularly during the noisy intermediate-scale quantum (NISQ) era. In this study, we investigate the capabilities and limitations of VQE algorithms implemented on current quantum hardware for determining molecular ground-state energies, focusing on the adaptive derivative-assembled pseudo-Trotter ansatz VQE (ADAPT-VQE). To address the significant computational challenges posed by molecular Hamiltonians, we explore various well known strategies to simplify the Hamiltonian, optimize the ansatz, and improve classical parameter optimization through modifications of the COBYLA optimizer. These enhancements are integrated into a tailored quantum computing implementation designed to minimize the circuit depth and computational cost. Using benzene as a benchmark system, we demonstrate the application of these optimizations on an IBM quantum computer. Despite these improvements, our results highlight the limitations imposed by current quantum hardware, particularly the impact of quantum noise on state preparation and energy measurement. The noise levels in today's devices prevent meaningful evaluations of molecular Hamiltonians with sufficient accuracy to produce reliable quantum chemical insights. Finally, we extrapolate the requirements for future quantum hardware to enable practical and scalable quantum chemistry calculations using VQE algorithms. This work provides an assessment of current quantum algorithms for molecular modeling on real quantum hardware, highlighting the impact of noise and hardware limitations on the achievable accuracy.
