arXiv subjects

Ben Zhong Tang

Publications and source records attributed to Ben Zhong Tang.

4 recordsLinked to original sources

arXiv2026

The Same and Not the Same: A Machine-Checked Genealogy of Photochemical Theory

Chemistry's phenomenological theories multiply with its observables: the same physical reality is repeatedly named in different measurement contexts, and the relations among theories have never had an auditable carrier. Here we present PhotoLean, a machine-checked genealogy of seventeen photochemical and photophysical theories formalized in Lean 4 over a shared kernel. Every pair of theories carries either a verified relation (equivalence, implication, composition with registered premises, definitional certificate) or a registered reason for its absence, covering all 136 pairs. Three adjudications resolve inherited conflations with if-and-only-if boundaries and witnesses: the symmetry factor $β$ equals one-half exactly when reactant and product force constants coincide; Kasha's rule and the Kasha-Vavilov rule agree only under closed quantification with a loss channel; and intensity-only Stern-Volmer data cannot distinguish static from dynamic quenching, whereas the lifetime channel discriminates exactly. As proposition generation shifts to machines, such machine-checked relational ledgers offer a replicable audit layer for theory itself.

physics.chem-ph↗

arXiv2026

Closing the Prior-Posterior Loop: Self-Reflective Molecular Design with Analysis-Driven LLM Iteration

Can a general-purpose large language model design molecules with the precision of a seasoned chemist? Current LLM-based frameworks answer this question with scalar feedback loops - generate, score, reject - that amount to informed trial-and-error. Here we show that replacing a single number with the full physicochemical rationale from first-principles calculations transforms the LLM from a stochastic sampler into a causal reasoner. Our system couples retrieval-augmented generation with a self-reflection module that feeds orbital energies, atomic charges, and electron densities - rather than compressed scores - back into the design loop. On HOMO-LUMO gap targets from 2.0 to 5.0 eV, this structure-property-relationship (SPR) reflection achieves a deviation as low as 0.0014 eV with a 100% success rate under the SPR+RAG configuration, consistently outperforming scalar-feedback and non-reflective baselines in median and mean deviation. The framework generalizes seamlessly to dipole-moment design, synthetic accessibility optimization, and molecular docking, and proves robust across 7 distinct LLM backbones. These results establish a new paradigm: when the model understands not only that a molecule fails, but why, iterative molecular design becomes genuinely mechanistic.

physics.chem-ph↗

arXiv2025

Frequency-Domain Denoising-Based in Vivo Fluorescence Imaging

The second near-infrared window (NIR-II, 900-1,880 nm) has been pivotal in advancing in vivo fluorescence imaging due to its superior penetration depth and contrast. Yet, its clinical utility remains limited by insufficient imaging temporal-spatial resolution and the absence of U.S. Food and Drug Administration (FDA)-approved NIR-II contrast agents. This work presents a frequency-domain denoising (FDD)-based in vivo fluorescence imaging technique, which can improve signal-to-background ratio (SBR) and signal-to-noise ratio (SNR) by more than 2,500-fold and 300-fold, respectively. The great enhancement yields a doubled penetration depth and a 95% reduction in contrast agent dosage or excitation light intensity for mouse vascular imaging. Additionally, we achieved a SBR far exceeded the Rose criterion in the observation of tumor margins and vessels in mice using Indocyanine Green (ICG), demonstrating the feasibility of NIR-II surgical navigation with FDA-approved agents. Furthermore, a 600 Hz real-time video enables visualization of the entire contrast agent diffusion process within the mouse body and differentiation between arteries and veins. This innovative technique, characterized by exceptional sensitivity, efficiency, and robustness, presents a promising solution for clinical applications, particularly in NIR-II surgical navigation.

physics.bio-ph↗

arXiv2024

Artificially built Kondo chains with organic radicals on metallic surfaces: new model system of heavy fermion quantum criticality

Heavy fermion quantum criticality is an extremely rich domain of research which represents a framework to understand strange metals as a consequence of a Kondo breakdown transition. Here we provide an experimental realization of such systems in terms of organic radicals on a metallic surface. The ground state of organic radicals is a Kramer's doublet that can be modeled by a spin 1/2 degree of freedom. Using on-surface synthesis and scanning tunneling microscopy (STM) tip manipulation, one can controllably engineer and characterize chains of organic radicals on a Au(111) surface. The spatial-resolved differential conductance reveals site-dependent low-energy excitations, which support the picture of emergent many-body Kondo physics. Using quantum Monte Carlo simulations, we show that a Kondo lattice model of spin chains on a metallic surface reproduces accurately the experimental results. This allows us to interpret the experimental results in terms of a heavy fermion metal, below the coherence temperature. We foresee that the tunability of these systems will pave the way to realize quantum simulators of heavy fermion criticality.

cond-mat.mes-hall↗