标题： 基于聚合物的概率位用于热力学计算 显示英文标题

标题： Polymer-based probabilistic bits for thermodynamic computing

摘要： 概率位（p-位）是随机硬件元素，其输出概率可通过输入偏置进行调节，为利用而非抑制波动的节能架构提供了一条途径。 在这里，我们报告了有机忆阻器器件中的p-位生成，确立了聚合物作为实现概率硬件的第一类软物质系统。 活性元件是一种带有侧链三苯胺（TPA）基团的二噻吩[3,2-b:2',3'-d]吡咯（DTP）骨架聚合物，其随机电阻波动通过一个简单的电压分压器/比较器电路转换为二进制输出。 产生的概率分布遵循逻辑传输函数，这是随机二进制神经元的特征。 另外，对脉冲IV测量的集合进行了分析，以构建分组电流分布，从中计算出离散香农熵。 此熵的峰值与使忆阻器电压降变化最大的偏置条件一致，直接将器件级的随机性与材料的本征特性联系起来。 介电分析表明，侧链TPA单元提供了动态活跃的弛豫模式，而能量分辨电化学阻抗谱和密度泛函理论计算表明，DTP、TPA和ITO的前线轨道在传输间隙内对齐，以产生分叉的渗流网络。 微观弛豫动力学、电子能量学和宏观概率响应之间的对应关系突显了有机半导体如何作为化学可调的熵源，为基于聚合物的热力学计算开辟了一条路径。 显示英文摘要

摘要： Probabilistic bits (p-bits) are stochastic hardware elements whose output probability can be tuned by an input bias, offering a route to energy-efficient architectures that exploit, rather than suppress, fluctuations. Here we report p-bit generation in an organic memristive device, establishing polymers as the first class of soft-matter systems to realize probabilistic hardware. The active element is a dithieno[3,2-b:2',3'-d]pyrrole (DTP)-backbone polymer with pendant triphenylamine (TPA) groups, whose stochastic resistance fluctuations are converted into binary outputs by a simple voltage-divider/comparator circuit. The resulting probability distributions follow logistic transfer functions, characteristic of stochastic binary neurons. Separately, ensembles of pulsed IV measurements were analyzed to construct binned current distributions, from which the discrete Shannon entropy was calculated. Peaks in this entropy coincide with bias conditions that maximize variability in the memristor voltage drop, directly linking device-level stochasticity to intrinsic material properties. Dielectric analysis shows that pendant TPA units provide dynamically active relaxation modes, while energy-resolved electrochemical impedance spectroscopy and density functional theory calculations indicate that the frontier orbitals of DTP, TPA and ITO align within the transport gap to produce a bifurcated percolation network. The correspondence between microscopic relaxation dynamics, electronic energetics and macroscopic probabilistic response highlights how organic semiconductors can serve as chemically tunable entropy sources, opening a polymer-based pathway toward thermodynamic computing.