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Machine learning models are poised to make a transformative impact on chemical sciences by dramatically accelerating computational algorithms and amplifying insights available from computational chemistry methods. However, achieving this…

Electrical engineering and molecular programming share many of the same mathematical foundations. In this paper, we show how to send multiple signals through a single pair of chemical species using modulation and demodulation techniques…

Emerging Technologies · Computer Science 2020-09-16 Titus H. Klinge , James I. Lathrop

Disentangling the mechanistic details of a chemical reaction pathway is a hard problem that often requires a considerable amount of chemical intuition and a component of luck. Experiments struggle in observing short-life metastable…

Chemical Physics · Physics 2019-08-01 Valerio Rizzi , Dan Mendels , Emilia Sicilia , Michele Parrinello

This work presents a new multi-chemical experimental platform for molecular communication where the transmitter can release different chemicals. This platform is designed to be inexpensive and accessible, and it can be expanded to simulate…

Emerging Technologies · Computer Science 2017-04-18 Nariman Farsad , David Pan , Andrea Goldsmith

SMILES is a linear representation of chemical structures which encodes the connection table, and the stereochemistry of a molecule as a line of text with a grammar structure denoting atoms, bonds, rings and chains, and this information can…

Machine Learning · Computer Science 2018-12-03 Arindam Paul , Dipendra Jha , Reda Al-Bahrani , Wei-keng Liao , Alok Choudhary , Ankit Agrawal

In this demonstration, we will present the world's first molecular multiple-input multiple-output (MIMO) communication link to deliver two data streams in a spatial domain. We show that chemical signals such as concentration gradients could…

Emerging Technologies · Computer Science 2015-03-20 Changmin Lee , Bonhong Koo , Na-Rae Kim , Birkan Yilmaz , Nariman Farsard , Andrew Eckford , Chan-Byoung Chae

Over the past decade, Artificial Intelligence has significantly advanced, mostly driven by large-scale neural approaches. However, in the chemical process industry, where safety is critical, these methods are often unsuitable due to their…

Machine Learning · Computer Science 2026-03-24 Julien Amblard , Niklas Groll , Matthew Tait , Mark Law , Gürkan Sin , Alessandra Russo

Scientists perform diverse manual procedures that are tedious and laborious. Such procedures are considered a bottleneck for modern experimental science, as they consume time and increase burdens in fields including material science and…

The main purpose of this paper is to provide a summary of the fundamental methods for analyzing delay differential equations arising in biology and medicine. These methods are employed to illustrate the effects of time delay on the behavior…

Dynamical Systems · Mathematics 2017-01-17 Majid Bani-Yaghoub

We describe a method to model nonlinear dynamical systems using periodic solutions of delay-differential equations. We show that any finite-time trajectory of a nonlinear dynamical system can be loaded approximately into the initial…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Alexander N. Jourjine

Delays are an important phenomenon arising in a wide variety of real world systems. They occur in biological models because of diffusion effects or as simplifying modeling elements. We propose here to consider delayed stochastic reaction…

Optimization and Control · Mathematics 2020-04-27 Corentin Briat , Mustafa Khammash

Isologous diversification theory for cell differentiation is proposed, based on simulations of interacting cells with biochemical networks and cell division process following consumption of some chemicals. According to the simulations of…

adap-org · Physics 2008-02-03 Kunihiko Kaneko , Tetsuya Yomo

Nonlinear photonic delay systems present interesting implementation platforms for machine learning models. They can be extremely fast, offer great degrees of parallelism and potentially consume far less power than digital processors. So far…

Neural and Evolutionary Computing · Computer Science 2016-03-24 Michiel Hermans , Miguel Soriano , Joni Dambre , Peter Bienstman , Ingo Fischer

Prediction of complete step-by-step chemical reaction mechanisms (CRMs) remains a major challenge. Whereas the traditional approaches in CRM tasks rely on expert-driven experiments or costly quantum chemical computations, contemporary deep…

Chemical Physics · Physics 2025-12-11 Manajit Das , Ajnabiul Hoque , Mayank Baranwal , Raghavan B. Sunoj

Sampled structure sequences obtained, for instance, from real-time reactivity explorations or first-principles molecular dynamics simulations contain valuable information about chemical reactivity. Eventually, such sequences allow for the…

Chemical Physics · Physics 2018-04-25 Michael A. Heuer , Alain C. Vaucher , Moritz P. Haag , Markus Reiher

In molecular communications, the direct detection of signaling molecules may be challenging due to a lack of suitable sensors and interference in the environment. Motivated by research in molecular biology, we investigate an indirect…

Information Theory · Computer Science 2022-04-25 Trang Ngoc Cao , Vahid Jamali , Wayan Wicke , Phee Lep Yeoh , Nikola Zlatanov , Jamie S Evans , Robert Schober

Machine learning techniques applied to chemical reactions has a long history. The present contribution discusses applications ranging from small molecule reaction dynamics to platforms for reaction planning. ML-based techniques can be of…

Chemical Physics · Physics 2021-01-12 M. Meuwly

A variety of natural phenomena comprises a huge number of competing reactions and short-lived intermediates. Any study of such processes requires the discovery and accurate modeling of their underlying reaction network. However, this task…

Chemical Physics · Physics 2014-05-27 Paolo Elvati , Angela Violi

Communication in the presence of bounded timing asynchronism which is known to the receiver but cannot be easily compensated is studied. Examples of such situations include point-to-point communication over inter-symbol interference (ISI)…

Information Theory · Computer Science 2014-11-18 Ping-Chung Wang , Yu-Chih Huang , Krishna R. Narayanan

Large language models (LLMs) have demonstrated broad utility across molecular domains, spanning drug discovery and materials design. Analyzing LLMs' latent representations is crucial for elucidating their underlying mechanisms, improving…

Machine Learning · Computer Science 2026-02-03 Zhuoran Li , Xu Sun , Wanyu Lin , Jiannong Cao