About

Dr. James K. Gimzewski is a Distinguished Professor of Chemistry at the University of California, Los Angeles, and serves as the Director of the Nano & Pico Characterization Core Facility of the California NanoSystems Institute. His research has a strong focus on the convergence and application of nanoscale science and technology, encompassing physics, chemistry, engineering, life sciences, medicine, and art. He has pioneered research on mechanical and electrical contacts with single atoms and molecules using scanning tunneling microscopy (STM), and was among the first to image molecules with STM. His notable achievements include the first STM-based fabrication of molecular suprastructures at room temperature, the discovery of single molecule rotors, and the development of nanotechnology-based micromechanical sensors that explore the limits of sensitivity and measurement, with recent applications in biochemical recognition through nanomechanics.

Research topics

• Materials science
• Nanotechnology
• Chemistry
• Computer science
• Biology

Selected publications

• Ionic nanoarchitectonics for electronic information devices

  JuSER Publikationsportal · 2025-01-01

  articleOpen access
  PublisherDOI

• Ionic Nanoarchitectonics for Electronic Information Devices

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access
  PublisherDOI

• Ionic nanoarchitectonics for electronic information devices

  Solid State Ionics · 2025-08-26 · 4 citations

  articleOpen access

  Today's scientific and technological growth relies on rapid advances in electronic information technologies. Semiconductor devices such as transistors are essential to these technologies, and they are constantly being improved by being made smaller and more integrated. However, there is a concern that these improvements may slow down in the near future. Thus, creating new types of devices that can overcome the problems and/or enhance the capabilities of traditional semiconductor devices has become an important challenge. In particular, solid-state ionic devices can potentially meet this challenge. In this review, we describe the design of such devices using ionic nanoarchitectonics techniques that locally control ion conduction and electrochemical behavior in ion conductors and mixed conductors. In addition, we describe solid-state ionic devices developed for electronic information technology as well as the electrical, magnetic, optical, and brain-inspired neuromorphic functionalities of these devices. • Ionic nanoarchitectonics for control ion transport and electrochemical phenomena • Electronic information devices enhanced by ionic nanoarchitectonics. • Ionic devices enable performance unattainable with conventional semiconductor devices. • Quantized conductance atomic switch operating by atomic-scale ion transport. • Brain-mimicking neuromorphic ionic devices.

  PublisherDOI

• Advanced Interferometry with 3-D Structured Illumination Reveals the Surface Fine Structure of Complex Biospecimens

  The Journal of Physical Chemistry Letters · 2024-01-23 · 4 citations

  articleOpen access

  Interference reflection microscopy (IRM) is a powerful, label-free technique to visualize the surface structure of biospecimens. However, stray light outside a focal plane obscures the surface fine structures beyond the diffraction limit (dxy ≈ 200 nm). Here, we developed an advanced interferometry approach to visualize the surface fine structure of complex biospecimens, ranging from protein assemblies to single cells. Compared to 2-D, our unique 3-D structure illumination introduced to IRM enabled successful visualization of fine structures and the dynamics of protein crystal growth under lateral (dx-y ≈ 110 nm) and axial (dx-z ≤ 5 nm) resolutions and dynamical adhesion of microtubule fiber networks with lateral resolution (dx-y ≈ 120 nm), 10 times greater than unstructured IRM (dx-y ≈ 1000 nm). Simultaneous reflection/fluorescence imaging provides new physical fingerprints for studying complex biospecimens and biological processes such as myogenic differentiation and highlights the potential use of advanced interferometry to study key nanostructures of complex biospecimens.

  PublisherOA PDFDOI

• The Radical Atom: Mechanosynthetic 3D Printing of an Atomically Precise SPM Tip

  2024-10-16

  reportOpen accessSenior author

  This research effort sought to overcome current limitations in scanning probe-based atomic manipulation to enable atomically precise manufacturing (APM). Previous theoretical and experimental works on atom by atom and molecule by molecule fabrication of precise structures are limited to essentially to two-dimensions. APM will enable a paradigm shift in 21st century manufacturing practices in which every single atom in a electronic chip, device or machine can be placed in an exact and predefined position in three-dimensions. By providing a general method for generating reproducible SPM tip structure, this project will drive forward the entire field of atomically precise scanning probe microscopy, opening the door to positional control of nearly arbitrary covalent chemistry. Such control could, for example, be used in applications such as novel 2.5 or 3D microchip fabrication. The creation of a unique manufacturing method through APM has the potential to impact technologies at the theoretical limits of performance, weight, and utility including: solid-state quantum and spintronic computing systems, high efficiency optical antenna, solar power systems, defect engineered materials and extremely efficient catalysts. Although this experiment focused on pick-and-place non-scalable APM, the better understanding of the chemistry is crucial to the eventual goal of scalable APM. To place individual atoms into a specified location is a seminal aspiration of researchers and engineers in the many fields and may have early premium applications in medical devices and microelectronics.

  PublisherOA PDFDOI

• Thermally Stable Ag₂Se Nanowire Network as an Effective In‐Materio Physical Reservoir Computing Device

  Advanced Electronic Materials · 2024-11-27 · 15 citations

  articleOpen accessCorresponding

  Abstract The artificial intelligence (AI) paradigm shifts from software to implementing general‐purpose or application‐specific hardware systems with lower power requirements. This study explored a material physical reservoir consisting of a material random network, called in‐materio physical reservoir computing (RC) to achieve efficient hardware systems. The device, made up of a random, highly interconnected network of nonlinear Ag 2 Se nanojunctions as reservoir nodes, demonstrated the requisite characteristics of an in‐materio physical reservoir, including but not limited to nonlinear switching, memory, and higher harmonic generation. The power consumption of the in‐materio physical reservoir is 0.07 nW per nanojunctions, confirming its highly efficient information processing system. As a hardware reservoir, the devices successfully performed waveform generation tasks. Finally, a voice classification by an in‐materio physical reservoir is achieved over 80%, comparable to an RC software simulation. In‐materio physical RC with rich nonlinear dynamics has huge potential for next‐generation hardware‐based AI.

  PublisherOA PDFDOI

• Metal doped polyaniline as neuromorphic circuit elements for in-materia computing

  Science and Technology of Advanced Materials · 2023-02-13 · 11 citations

  articleOpen accessCorresponding

  Polyaniline-based atomic switches are material building blocks whose nanoscale structure and resultant neuromorphic character provide a new physical substrate for the development next-generation, nanoarchitectonic-enabled computing systems. Metal ion-doped devices consisting of a Ag/metal ion doped polyaniline/Pt sandwich structure were fabricated using an in situ wet process. The devices exhibited repeatable resistive switching between high (ON) and low (OFF) conductance states in both Ag+ and Cu2+ ion-doped devices. The threshold voltage for switching was>0.8 V and average ON/OFF conductance ratios (30 cycles for 3 samples) were 13 and 16 for Ag+ and Cu2+ devices, respectively. The ON state duration was determined by the decay to an OFF state after pulsed voltages of differing amplitude and frequency. The switching behaviour is analagous to short-term (STM) and long-term (LTM) memories of biological synapses. Memristive behaviour and evidence of quantized conductance were also observed and interpreted in terms of metal filament formation bridging the metal doped polymer layer. The successful realization of these properties within physical material systems indicate polyaniline frameworks as suitable neuromorphic substrates for in materia computing.

  PublisherDOI

• Metal doped polyaniline as neuromorphic circuit elements for in-materia computing

  Figshare · 2023-01-01

  datasetOpen access

  Polyaniline-based atomic switches are material building blocks whose nanoscale structure and resultant neuromorphic character provide a new physical substrate for the development next-generation, nanoarchitectonic-enabled computing systems. Metal ion-doped devices consisting of a Ag/metal ion doped polyaniline/Pt sandwich structure were fabricated using an <i>in situ</i> wet process. The devices exhibited repeatable resistive switching between high (ON) and low (OFF) conductance states in both Ag⁺ and Cu²⁺ ion-doped devices. The threshold voltage for switching was&gt;0.8 V and average ON/OFF conductance ratios (30 cycles for 3 samples) were 13 and 16 for Ag⁺ and Cu²⁺ devices, respectively. The ON state duration was determined by the decay to an OFF state after pulsed voltages of differing amplitude and frequency. The switching behaviour is analagous to short-term (STM) and long-term (LTM) memories of biological synapses. Memristive behaviour and evidence of quantized conductance were also observed and interpreted in terms of metal filament formation bridging the metal doped polymer layer. The successful realization of these properties within physical material systems indicate polyaniline frameworks as suitable neuromorphic substrates for <i>in materia</i> computing.

  PublisherDOI

• Online dynamical learning and sequence memory with neuromorphic nanowire networks

  Nature Communications · 2023-11-01 · 51 citations

  articleOpen access

  Nanowire Networks (NWNs) belong to an emerging class of neuromorphic systems that exploit the unique physical properties of nanostructured materials. In addition to their neural network-like physical structure, NWNs also exhibit resistive memory switching in response to electrical inputs due to synapse-like changes in conductance at nanowire-nanowire cross-point junctions. Previous studies have demonstrated how the neuromorphic dynamics generated by NWNs can be harnessed for temporal learning tasks. This study extends these findings further by demonstrating online learning from spatiotemporal dynamical features using image classification and sequence memory recall tasks implemented on an NWN device. Applied to the MNIST handwritten digit classification task, online dynamical learning with the NWN device achieves an overall accuracy of 93.4%. Additionally, we find a correlation between the classification accuracy of individual digit classes and mutual information. The sequence memory task reveals how memory patterns embedded in the dynamical features enable online learning and recall of a spatiotemporal sequence pattern. Overall, these results provide proof-of-concept of online learning from spatiotemporal dynamics using NWNs and further elucidate how memory can enhance learning.

  PublisherOA PDFDOI

• Data from Identification of a Human Airway Epithelial Cell Subpopulation with Altered Biophysical, Molecular, and Metastatic Properties

  2023-04-03

  preprintOpen access

  &lt;div&gt;Abstract&lt;p&gt;Lung cancers are documented to have remarkable intratumoral genetic heterogeneity. However, little is known about the heterogeneity of biophysical properties, such as cell motility, and its relationship to early disease pathogenesis and micrometastatic dissemination. In this study, we identified and selected a subpopulation of highly migratory premalignant airway epithelial cells that were observed to migrate through microscale constrictions at up to 100-fold the rate of the unselected immortalized epithelial cell lines. This enhanced migratory capacity was found to be Rac1-dependent and heritable, as evidenced by maintenance of the phenotype through multiple cell divisions continuing more than 8 weeks after selection. The morphology of this lung epithelial subpopulation was characterized by increased cell protrusion intensity. In a murine model of micrometastatic seeding and pulmonary colonization, the motility-selected premalignant cells exhibit both enhanced survival in short-term assays and enhanced outgrowth of premalignant lesions in longer-term assays, thus overcoming important aspects of “metastatic inefficiency.” Overall, our findings indicate that among immortalized premalignant airway epithelial cell lines, subpopulations with heritable motility-related biophysical properties exist, and these may explain micrometastatic seeding occurring early in the pathogenesis of lung cancer. Understanding, targeting, and preventing these critical biophysical traits and their underlying molecular mechanisms may provide a new approach to prevent metastatic behavior. &lt;i&gt;Cancer Prev Res; 10(9); 514–24. ©2017 AACR&lt;/i&gt;.&lt;/p&gt;&lt;p&gt;&lt;i&gt;See related editorial by Hynds and Janes, p. 491&lt;/i&gt;&lt;/p&gt;&lt;/div&gt;

  PublisherDOI

Recent grants

• NIH Grant R21GM074509

  NIH · $376k · 2007

• The role of electromechanical cue on cardiomyocyte maturation

  NIH · $407k · 2015–2018

• NIH Grant R21GM080999

  NIH · $690k · 2011

Frequent coauthors

• Adam Z. Stieg

  California NanoSystems Institute

  331 shared

• Shivani Sharma

  California NanoSystems Institute

  251 shared

• Valerie Zgonc

  Center for Cancer Research

  98 shared

• Malini Harigopal

  Yale University

  98 shared

• Mark J. Roth

  98 shared

• Iskender Sinan Genco

  Lenox Hill Hospital

  98 shared

• Raffit Hassan

  The University of Texas MD Anderson Cancer Center

  98 shared

• Patricia Fetsch

  98 shared

Awards & honors

• Carnegie Centenary Professorship from the Universities of Sc…
• Dr. Honoris Causa, Université de la Méditerranée, Aix-Marsei…
• Benjamin Meaker Visiting Professorship, Department of Physic…
• Royal Society Elected Fellow
• International Society for Nanoscale Science, Computation and…